First Break January 2026 - Land Seismic

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SPECIAL TOPIC

Land Seismic EAGE NEWS Association celebrates 75th anniversary CROSSTALK Predictions for 2026 TECHNICAL ARTICLE Passive real-time geophysical monitoring of cities

HANNOVER GERMANY

SAVE THE DATE! 2-6 NOVEMBER 2026 EAGEGET.ORG #E AGEGE T 2026

FIRST BREAK® An EAGE Publication www.firstbreak.org ISSN 0263-5046 (print) / ISSN 1365-2397 (online) CHAIR EDITORIAL BOARD Clément Kostov (cvkostov@icloud.com) EDITOR Damian Arnold (arnolddamian@googlemail.com) MEMBERS, EDITORIAL BOARD • Philippe Caprioli, SLB (caprioli0@slb.com) • Satinder Chopra, SamiGeo (satinder.chopra@samigeo.com) • Anthony Day, NORSAR (anthony.day@norsar.no) • Kara English, University College Dublin (kara.english@ucd.ie) • Hamidreza Hamdi, University of Calgary (hhamdi@ucalgary.ca) • Fabio Marco Miotti, Baker Hughes (fabiomarco.miotti@bakerhughes.com) • Roderick Perez Altamar, OMV (roderick.perezaltamar@omv.com) • Susanne Rentsch-Smith, Shearwater (srentsch@shearwatergeo.com) • Martin Riviere, Retired Geophysicist (martinriviere@btinternet.com) • Angelika-Maria Wulff, Consultant (gp.awulff@gmail.com) EAGE EDITOR EMERITUS Andrew McBarnet (andrew@andrewmcbarnet.com) PUBLICATIONS MANAGER Hang Pham (publications@eage.org) MEDIA PRODUCTION Saskia Nota (firstbreakproduction@eage.org) Ivana Geurts (firstbreakproduction@eage.org)

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Redefining transition-zone 3D seismic acquisition: Flexible land-nodal methods applied to the Kalundborg-Gassum CCS site, Denmark

Editorial Contents 3

EAGE News

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Personal Record Interview — Henk Kombrink

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Crosstalk

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Industry News

Technical Articles 33

Transforming cities with real-time passive geophysical monitoring Jie Zhang

EAGE EUROPE OFFICE Kosterijland 48 3981 AJ Bunnik The Netherlands • +31 88 995 5055 • eage@eage.org • www.eage.org

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Automated realistic labelled DAS data synthesis using CycleGANs and their application to phase arrival picking William Tegtow, Nepomuk Boitz, Serge A. Shapiro and Andres Chavarria

EAGE MIDDLE EAST OFFICE EAGE Middle East FZ-LLC Dubai Knowledge Village PO Box 501711 Dubai, United Arab Emirates • +971 4 369 3897 • middle_east@eage.org • www.eage.org

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Land seismic node technology: Current capabilities and future directions Tim Dean and Matt Grant

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Data download and transcription in nodal seismic acquisition systems Dennis Pavel

EAGE ASIA PACIFIC OFFICE EAGE Asia Pacific Sdn. Bhd. UOA Centre Office Suite 19-15-3A No. 19, Jalan Pinang 50450 Kuala Lumpur Malaysia • +60 3 272 201 40 • asiapacific@eage.org • www.eage.org

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Redefining transition-zone 3D seismic acquisition: Flexible land-nodal methods applied to the Kalundborg-Gassum CCS site, Denmark Piotr Potepa, Karim Souissi, Manuel Beitz, Ewa Zubrzycka and Jerzy Trela

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Forty years of deep geothermal experience in Switzerland: lessons learnt and looking forward Andrea Moscariello and Ladislaus Rybach

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Bridging acquisition and processing: A practical data-driven approach Nabil Khadiri Yazami, Van Chuong Do, Guillaume Friess and Stéphane Laroche

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Enhanced seismic imaging in the Midland Basin with multiparameter full-waveform inversion James Sheng, Guanghui Huang, Terence Krishnasamy, Andrew Peterson, Jaime Ramos-Martínez and Carlos Calderón-Macías

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Calendar

ADVERTISING INQUIRIES corporaterelations@eage.org

EAGE LATIN AMERICA OFFICE EAGE Americas SAS Av Cra 19 #114-65 - Office 205 Bogotá, Colombia • +57 310 8610709 • americas@eage.org • www.eage.org EAGE MEMBERS’ CHANGE OF ADDRESS Update via your MyEAGE account, or contact the EAGE Membership Dept at membership@eage.org COPYRIGHT & PHOTOCOPYING © 2026 EAGE All rights reserved. First Break or any part thereof may not be reproduced, stored in a retrieval system, or transcribed in any form or by any means, electronically or mechanically, including photocopying and recording, without the prior written permission of the publisher.

PAPER The publisher’s policy is to use acid-free permanent paper (TCF), to the draft standard ISO/DIS/9706, made from sustainable forests using chlorine-free pulp (Nordic-Swan standard).

Special Topic: Land Seismic

cover: GTG International SA deploys Stryde nodes for a Swiss geothermal exploration seismic survey commissioned by EnergeÔ SA and GEOOL SA. This month we put the spotlight on the Swiss geothermal sector while Stryde and other companies’ nodes are put their paces in an overview of the sector. (Photo courtesy of Stryde).

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European Association of Geoscientists & Engineers

Board 2025-2026

Environment, Minerals & Infrastructure Circle Andreas Aspmo Pfaffhuber Chair Florina Tuluca Vice-Chair Esther Bloem Immediate Past Chair Micki Allen Liaison EEGS Martin Brook Liaison Asia Pacific Ruth Chigbo Liaison Young Professionals Community Deyan Draganov Technical Programme Representative Madeline Lee Liaison Women in Geoscience and Engineering Community Gaud Pouliquen Liaison Industry and Critical Minerals Community Eduardo Rodrigues Liaison First Break Mark Vardy Editor-in-Chief Near Surface Geophysics

Oil & Gas Geoscience Circle Sanjeev Rajput President

Mike Branston Vice-President

Johannes Wendebourg Chair Timothy Tylor-Jones Vice-Chair Yohaney Gomez Galarza Immediate Past Chair Alireza Malehmir Editor-in-Chief Geophysical Prospecting Adeline Parent Member Jonathan Redfern Editor-in-Chief Petroleum Geoscience Robert Tugume Member Anke Wendt Member Martin Widmaier Technical Programme Officer

Sustainable Energy Circle Christian Henke Secretary-Treasurer

Diego Rovetta Membership and Cooperation Officer

Eric Verschuur Publications Officer

Maren Kleemeyer Education Officer

Martin Widmaier Technical Programme Officer

Andreas Aspmo Pfaffhuber Chair Environment, Minerals & Infrastructure Circle

Giovanni Sosio Chair Benjamin Bellwald Vice-Chair Carla Martín-Clavé Immediate Past Chair Emer Caslin Liaison Technical Communities Sebastian Geiger Editor-in-Chief Geoenergy Maximilian Haas Publications Assistant Dan Hemingway Technical Programme Representative Carrie Holloway Liaison Young Professionals Community Adeline Parent Liaison Education Committee Longying Xiao Liaison Women in Geoscience and Engineering Community Martin Widmaier Technical Programme Officer

SUBSCRIPTIONS First Break is published monthly online. It is free to EAGE members.

The membership fee of EAGE is € 90.00 a year including First Break, EarthDoc (EAGE’s geoscience database), Learning Geoscience (EAGE’s Education platform) and online access to a scientific journal.

Companies can subscribe to First Break via an institutional subscription. Every subscription includes online access to the full First Break archive for the requested number of online users.

Orders for current subscriptions and back issues should be sent to First Break B.V., Journal Subscriptions, Kosterijland 48, 3981 AJ Bunnik, The Netherlands. Tel: +31 (0)88 9955055, E-mail: corporaterelations@eage.org, www.firstbreak.org.

Johannes Wendebourg Chair Oil & Gas Geoscience Circle

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First Break is published by First Break B.V., The Netherlands.

However, responsibility for the opinions given and the statements made rests with the authors.

Giovanni Sosio Chair Sustainable Energy Circle

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HIGHLIGHTS

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Hannover to host GET 2026

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Klaus Helbig remembered

ECMOR venue for 2026

EAGE at 75: From waves on paper to intelligence in the Cloud As we begin 2026, Dr Sanjeev Rajput, president, EAGE reflects on the Association’s role in the geoscience community over the past 75 years and how it will evolve in the future.

President Sanjeev Rajput (middle) with CEO Marcel van Loon on his right and EAGE colleagues.

Seventy-five years ago, geoscientists across Europe gathered around long rolls of analogue seismic paper, tracing the Earth’s secrets with pencils and rulers. The tools were simple, but the ambition was vast.

Today, many of our youngest members encounter the subsurface for the first time through an AI dashboard running on a cloud cluster. In many ways, the story of EAGE is the journey between those two images, between waves captured on paper and intelligence emerging in silicon.

The Association’s 75th anniversary offers us a moment to reflect on how far we have travelled, and how much further we must go. The world around us

is changing rapidly. Energy systems are evolving unevenly: some technologies are accelerating at extraordinary speed, while others remain stuck in the hardest physical and industrial bottlenecks. Independent global analyses converge on one truth, the transition is real and advancing, but still moving at roughly half the pace required to meet long-term climate goals. The easier challenges, such as solar, wind, EVs and critical minerals, are growing quickly. The hardest ones, deep industrial decarbonisation, long-duration storage, hydrogen scale-up, subsurface integrity for CCS, and the interplay of grids and geoscience, remain the places where progress is slowest, yet most essential.

If that sounds familiar, it is because these domains demand exactly the type of thinking that defines EAGE: physics-based, measurement-driven, multi-disciplinary, and grounded in real-world complexity.

The next phase of the global transition is not just about deploying technologies, it is about solving the ‘hard stuff’ through integrated subsurface knowledge, engineering excellence, and intelligent systems. That is where we stand, and where we must lead.

As we celebrate 75 years, it is worth remembering the arc that brought us here.

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In the 1950s and ’60s, our community shaped the foundations of modern exploration geophysics. The 1970s and ’80s brought digital seismic and the first great computational leaps. The 1990s integrated reservoir engineering, rock physics, inversion and quantitative interpretation into a common scientific language. The 2000s expanded our reach into near-surface, environmental geoscience and monitoring. And over the past decade, EAGE has become a platform where digitalisation, machine learning, CCUS, geothermal, offshore wind and energy systems are not ‘new topics’ but natural extensions of our scientific DNA. This heritage is visible across our entire ecosystem. Our Annual Conference & Exhibition has become one of the largest global gatherings of geoscientists and engineers. Our journals and First Break provide a shared intellectual backbone. EarthDoc now forms part of the world’s scientific memory, housing more than 85,000 papers curated across generations. Our education tours, Learning Geoscience platform, short courses and student programmes continue to democratise access and accelerate professional development. The creation of the Sustainable Energy Circle in 2023 formalised what the community already knew: that I

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EAGE NEWS

geothermal, hydrogen, CCUS and offshore wind are core disciplines for the decades ahead, not peripheral subjects.

This forward momentum was on full display this year through two deeply meaningful engagements: SPG India and SBGf Brazil. When I walked into SPG India, what struck me first was the sheer energy of transformation. India’s geoscience ecosystem is evolving at remarkable speed, not only technologically but culturally.

ship: inclusion. Standing with colleagues in Rio during the panel on empowering diverse talent, I was reminded that scientific progress is inseparable from human progress. Brazil’s openness, academic strength and deepwater leadership make it a global reference point. Technical sessions on pre-salt imaging, OBN processing, environmental geophysics, offshore wind and CCS illustrated the country’s unique blend of frontier complexity and system-level

Sanjeev Rajput participated in the Plenary Session ‘Data to Discovery: AI for Subsurface Insights’ at SPG India 2025.

Conversations there were unambiguously AI-native: cloud-scale seismic processing, ontology-driven intelligence frameworks, and digital workflows where data, physics and expert knowledge merge into a unified semantic fabric. Start-ups such as Aureon Energy demonstrated how an intelligence-first philosophy can reduce uncertainty, accelerate evaluation cycles and support sustainability-focused decisions.

Larger technology players showcased breakthroughs in GPU computing, bringing near real-time imaging and simulation into the realm of practical operations. And through initiatives such as the BP India– EAGE Student Challenge, we are ensuring that students engage with authentic datasets and real subsurface problems, not hypothetical exercises but industry-grade challenges.

At the same time, emerging economies like India, Brazil and Indonesia are installing solar and wind capacity at unprecedented rates. EV adoption in these markets is rising sharply. These shifts matter, because they show that innovation is no longer concentrated in a handful of regions, it is distributed, dynamic and often led by young professionals who are defining the subsurface’s role in the broader energy system.

Our engagement with SBGf Brazil highlighted another dimension of leader4

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innovation. The renewed MoU between EAGE and SBGf is more than a signature, it is a commitment to building a globally connected, fair and future-ready scientific community.

Across all these interactions, a unifying theme emerged: EAGE’s unique value is to act as a connector. Our partner societies are like a constellation of lighthouses, each illuminating its region, and together guiding a global fleet. Through conferences, workshops, joint publications, student chapters, webinars, hackathons, and EarthDoc, we ensure that ideas do not stay locked in one basin, one company or one country.

Knowledge moves, and when it moves, progress accelerates.

This spirit underpinning our diamond anniversary is also what drives the Global Energy Transition Conference & Exhibition (GET). Since its in-person launch in 2022, GET has evolved into a cross-disciplinary platform where geoscience meets policy, finance, digitalisation and engineering.

GET 2024 and GET 2025 in Rotterdam brought together four full technical conferences on offshore wind, CCUS, geothermal and hydrogen, placing the subsurface at the very heart of renewable and low-carbon development. The events also serve as laboratories for testing new engagement models, from digitalization hubs to AI nav-

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igation tools that help attendees explore programmes more intuitively. This is exactly the kind of experimentation we must embrace to remain relevant for the next 75 years.

Looking ahead, three priorities stand out for me. First, to double down on scientific excellence, especially in the hardest domains of the transition, where rigorous physics, trusted measurements, long-term monitoring and integrated modelling remain essential. These are areas where EAGE can make a global impact, not just a disciplinary one.

Second, to widen the bridge for the next generation. The professionals who will lead EAGE in 2051 are students today.

Their world will be more electrified, more digital, more data-rich and more sustainability-driven than any generation before them. We must equip them not only with technical depth but with ethical, social and inter-disciplinary awareness.

Third, to embrace AI-native geoscience with ambition and humility. AI will increasingly sit inside every workflow, every model, every monitoring system.

But AI is only as strong as the physics it honours, the data it understands and the people who guide it. The future will belong to professionals who can combine domain expertise with digital fluency and systemic thinking.

Our community thrives when every professional feels welcome, when opportunity is shared, and when excellence, scientific, operational and ethical, guides every step forward. That has been the quiet power of EAGE for 75 years: not a single breakthrough or a single event, but a living ecosystem that helps people, ideas and technologies meet at the right moment.

As we enter 2026, let us carry this legacy with confidence and build boldly for the next 75 years. The challenges ahead will demand from us more than technical mastery, they will require imagination, integrity, and a willingness to lead when the path is not yet clear. EAGE has always been strongest when we combine rigorous science with a human spirit that welcomes every professional into the fold. If we remain curious, collaborative, and courageous, the next era of geoscience will not just be something we observe, it will be something we shape together.

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EAGE NEWS

Announcing Dedicated Sessions for Annual in Aberdeen A great series of Dedicated Sessions awaits participants at our 87th EAGE Annual Conference & Exhibition in Aberdeen in June.

Dedicated Sessions add depth and focus to the Technical Programme. They group talks and case studies around a single theme so attendees can compare approaches, stress test assumptions, and leave with ideas they can use. Below is an overview of what is planned for Aberdeen.

age in aquifers, boreholes and mines, cost-effective monitoring for CCS and geothermal, the UK CCS project pipeline, recent research highlights, and the geological and technological levers for large-scale geothermal.

Frontiers in geophysics Three sessions will cover lunar subsurface mission concepts, the renewed impact of gravity, magnetic and EM methods, and marine geohazards on Europe’s glaciated margins. Expect takeaways for hazard awareness, site characterisation and project design.

Data, integration and decision quality Five sessions will focus on extracting value from underused datasets, aligning language and workflows between geoscience and engineering, turning uncertainty into decisions, communicating complex ideas clearly, and field-scale digital and integrated modelling.

Energy transition, storage and monitoring Six sessions will address fluid flow in transition resources, thermal energy stor-

Geoscience for resources and resilience Five sessions will discuss critical minerals exploration, geochemistry for low-car-

bon mining, opportunities in deep brines, integrating renewables with traditional oil strategies, and lessons from exploration under crisis conditions.

Fields, basins and place Four sessions will cover production management and surveillance, new insights from mature basins with a North Sea focus, Aberdeen’s geological and industrial story, and later-life field opportunities with decommissioning considerations.

These sessions sit alongside the broader conference programme, workshops, short courses and field trips. Add the ones most relevant to your work, and plan to compare methods, challenge assumptions and build contacts in the room.

Learn more at eageannual.org/dedicatedsessions.

GET 2026 coming to Hannover in November The 7th EAGE Global Energy Transition Conference and Exhibition (GET 2026) will take place in Hannover, Germany, from 2 to 6 November 2026. This world world-class attracts geoscientists, engineers, operators, service companies, academia and policymakers to turn ideas into deployable solutions for the energy transition.

Hannover is a strong fit for this edition. The city is a European hub for trade fairs, engineering and research, set among generous green spaces such as Herrenhausen Gardens and the Maschsee waterfront. Its central location and direct rail and air links make travel straightforward for both regional and international delegates. The venue is the Hannover Congress Centrum.

GET 2026 will combine rigorous technical exchange with practical discussion on skills, delivery and policy. As in our previous successful events, expect tracks across CCS, geothermal, hydrogen and energy storage, offshore wind site characterisation

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Hannover welcomes GET 2026 participants.

and critical raw materials. Sessions will cover subsurface risk and modelling, MRV, digital and data, and the role of markets and regulation. An exhibition, hands-on workshops, short courses, field trips and a strategic programme will round out the week.

If you work in planning, permitting, building or operating low-carbon energy systems, add GET 2026 to your calendar and stay tuned on eageget.org for updates.

EAGE NEWS

Packed programme ahead for Digital 2026 Our upcoming EAGE Digital 2026 hit a new milestone with more than 100 abstracts submitted. It means we are bring-

Hackathon last year.

ing together a richer and more diverse programme than ever to the conference and exhibition being held on 9-12 March 2026 in Stavanger, Norway. Better still, if you wish to contribute, there is still time to present your research and be part of the technical programme if you submit your abstract by 1 February 2026.

The technical programme is now accessible along with the strategic programme including sessions on how OSDU transforms energy operations by unifying data, applications, and workflows and data readiness that will explore critical questions surrounding the trust, quality and efficiency of subsurface data in the context of emerging AI workflows.

The event offers three side activities designed to enhance digital skills. The powermix hackathon provides participants the chance to learn how to turn open energy data into an actionable national-scale plan

for the future of power generation. There is a short course titled ‘Language models for geoscience applications’. presented by Dr Thomas B. Grant, domain expert, Cegal, exploring the potential of generative AI (Gen-AI) for geoscience by examining the key concepts of large language models, and real-world applications of these models.

In addition, a field trip to the University of Stavanger and Stratum Reservoir is planned. Participants will learn about AI-driven innovation in oil and gas value chain, and gain key insights into advanced methodologies used to convert conventional core material into high-quality digital datasets that support enhanced reservoir evaluation.

Register by 10 February to take advantage of regular registration fee. For all details on the programme please visit eagedigital.org.

Australian Exploration Geophysics journal now available on EarthDoc We are now hosting the Australian Exploration Geophysics journal on the EarthDoc platform, making it easier than ever for the global geoscience community to access its valuable content.

In a world where geoscience data grows exponentially, finding research that is both rigorous and directly applicable can feel like striking gold. Exploration Geophysics, the flagship journal of the Australian Society of Exploration Geophysicists (ASEG), delivers just that, a rich mix of innovative methods, real-world case studies and insightful interpretations that matter to anyone working in mineral exploration, petroleum, mining, groundwater, or environmental geophysics.

What makes this journal stand out isn’t just the quality of its papers, but its perspective. Each article connects complex geophysical methods to practical outcomes. From seismic and electromagnetic surveys to magnetic, gravity, resistivity, and ground-penetrating radar techniques, Exploration Geophysics spans the full toolkit of subsurface investigation, translating data into actionable knowledge for professionals around the world.

The journal embraces a hybrid open-access model, reflecting a commitment to making high-quality research available to as many readers as possible without compromising rigorous peer review. Its international editorial and reviewer network, drawn

from both industry and academia, ensures that every paper is scientifically robust, methodologically sound and directly relevant to real-world applications.

Exploration Geophysics thrives on diversity. Significant case histories, advances in data interpretation and theoretical developments coexist alongside studies with direct field implications in Australia and beyond. Environmental and geotechnical research sit comfortably alongside traditional exploration work, creating a publication that mirrors the broad and interconnected world of applied geophysics.

Published online, each issue often features special sections or collections from ASEG conferences, providing both topical focus and a snapshot of the global geoscience conversation.

For professionals and researchers alike, the journal is more than a publication, it’s a meeting ground where ideas are tested, methods are refined and data is turned into insight.

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Klaus Helbig (1927–2025) Prof Dr Klaus Helbig, geophysicist, professor, editor, and colleague, passed away peacefully on 6 November 2025 at the age of 98. His career, spanning over six decades, left a lasting mark on exploration geophysics, scientific publishing and geophysical education worldwide.

He will be particularly remembered by EAGE for his lasting contribution to the Association’s publications and events.

Helbig began his studies in astronomy at the University of Göttingen (1946–1948) and continued with physics (1948–1952), eventually graduating as Diplomphysiker cum laude. He then conducted research at the Geophysics Institute in Göttingen (1954–1955), where he earned his PhD (Dr rer nat) magna cum laude. He completed his Dr habil in geophysics at the University of Munich in 1964.

His early career included work at Seismos in Germany, and assignments in Egypt, where he helped find a safe foundation for the Aswan Dam, as well as in Sicily and France exploring for oil, salt and iron. From 1958 to 1964, he served as a scientific assistant at the University of Munich and as a Unesco expert at the University of the Punjab, Lahore, Pakistan.

Klaus Helbig.

coast cycling and hiking, and duets for recorder and harpsichord.

In his scientific work, Helbig was relentless in his attention to detail. A quote from a 1988 interview in The Leading Edge (TLE) could serve as an admonition to all of us: ‘I do not give up.

My main research project, for instance, is something I started in 1954 and I’m still at it. As I tell my students, ‘In seismic or any other work, there is no other road to success than meticulous attention to detail. “So don’t give up and don’t be sloppy at it!”.’ During seismic fieldwork

‘Combination of rigour, creativity, humour, and intellectual spirit remain an inspiring example.’

From 1964, Helbig held positions in academia and industry in the United States, Belgium and Germany, including associate professor at St Louis University, senior research geophysicist at Texaco Bellaire, and director of geophysics at Texaco Europe. In 1977 he became ordinary professor of exploration geophysics at Utrecht University, The Netherlands, with concurrent appointments in Amsterdam. He remained active after retirement, publishing, consulting and lecturing internationally. In the early 2000s, he visited Memorial University of Newfoundland’s Geomechanics Project several times, enjoying scientific collaboration, Atlantic

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in Zeeland, when an assistant suggested estimating receiver spacing by pacing the distance by foot, he would gently interrupt (in Dutch): ‘Niet raden, maar meten!’ (‘Don’t guess, but measure!’).

With great humour and intellectual spirit, he set high standards.

As co-editor of the Seismic Exploration section of the Handbook of Geophysical Exploration, Helbig helped to shape one of the most influential multi-volume reference works in applied geophysics.

Together with his close friend Sven Treitel, he oversaw contributions from leading geophysicists and guided the series as it grew from its first volumes

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in 1984 to more than 40 books on topics ranging from seismic instrumentation and inversion to shear waves, anisotropy, tomography and monitoring.

Helbig’s main research topic was seismic anisotropy. He wrote the 1994 textbook Foundations of Anisotropy for Exploration Seismics, published as part of the Handbook series. The book has become a classic for anyone who wants to understand its physical and mathematical foundations and its geological impact. A considerable part of the book is based on thoughts he developed together with his good friend Michael Schoenberg, whom he first met at Tel Aviv University. Helbig deeply cherished his later visits to Schoenberg at Schlumberger-Doll Research (Connecticut, USA) and Schlumberger Cambridge Research (UK). In 1997, they published the revolutionary paper in Geophysics ‘Orthorhombic media: Modelling elastic wave behaviour in a vertically fractured earth’, which opens the way for practical applications of low-symmetry anisotropy models.

Helbig enjoyed revisiting classical references, notably rediscovering the work of Maurycy Pius Rudzki (18621916), who conducted the first studies of wave propagation in anisotropic media. Together with his close friend Johannes Schmoll, he translated from Latin the very first paper on diffraction theory (Grimaldi, 1665). In 2013 he published a speculative review paper ‘What Kelvin might have written about elasticity’. He was classical in the sense that he put high value on geometrical constructions in seismic exploration.

Helbig also had a keen interest in seismic instrumentation and high-resolution shallow seismic surveys. His prophetic vision is illustrated by another remark in the same TLE interview (1988): ‘Exploration seismics, as we know it, may not in the long run play the predominant role it has. We are running out of oil. As long as we continue trying to find it, we have to pay more attention

EAGE NEWS

to detail, to the intricacies of wave propagation in complex media. Exploration for oil, for petrochemicals, not to burn it as we do now, is destined to become a very esoteric business. Therefore, we must move to other targets, like groundwater. As for other applications, shallow seismic will play an important role in engineering.’

To this day, Helbig holds the record as the longest-serving editor-in-chief of Geophysical Prospecting (1969–1988).

He personally handled over 1200 manuscripts, with the editorial office based in his home and much of the work carried out together with his wife, Gerda Helbig-Rickens. His editorship, before the advent of email or centralised manuscript management, was one of his major contributions to applied geophysics, as he succeeded in establishing the journal as a respected and influential publication within the community. If he judged a submission worthwhile, he would completely rewrite it while preserving the author’s content. In 1974 he published ‘How to Write for Geophysical Prospecting’, with recommendations still relevant today; one of them is to comb through a text and eliminate every redundant word. He also oversaw the journal’s modernisation, introducing personal

Still active in his nineties.

computers, supporting the transition to digital typesetting and maintaining an efficient editorial workflow that became a model for scientific publishing in Europe.

The founding of EAGE’s flagship association journal First Break which began publication in 1983, coincidentally months after TLE appeared, will be

At work in the lab.

one of Helbig’s lasting legacies. From the first planning meetings in the stuffy atmosphere of then publisher Blackwell Science in Oxford, he was enthusiastic about a more accessible publication that could also garner more advertising revenue than Geophysical Prospecting.

He nursed First Break into life from afar respecting the new journal’s independence, hence he did not demur when first editor Ian Williamson in his introductory editorial noted a weakness of other geophysical journals being that a large part of the contents remained unread!

Always attentive to his PhD students’ development, Helbig ensured they benefited from his extensive global network and his long editorship of Geophysical Prospecting. This opened unique opportunities for them, including summer studentships at Schlumberger-Doll Research and assistant-editor positions with Geophysical Prospecting. Although Helbig fully supported his students in pursuing careers with major oil companies, he was known for a memorable remark to one of his PhD students: ‘You are entering the monastery.’ It was his way of warning that publication opportunities could become limited, highlighting his deep commitment to academic freedom and the importance he placed on publishing.

He was a member of EAGE, SEG, AGU, DGG, and numerous other national and international societies. Awards

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included the SEG Honorary Membership (1982) and, from the EAGE, the Conrad Schlumberger Award (1984), Honorary Membership (1989) and the Desiderius Erasmus Award (2002). Helbig was a regular participant, and often co-organiser, of the International Workshops on Seismic Anisotropy (IWSA), which bring together experts in anisotropy internationally. In EAGE 1950-2001: Reflections on the first 50 years, he mischievously recalls attending his first EAEG (as it was then) meeting in London in 1955. On his arrival at the official banquet (a dinner dance in those days), the young Helbig, just out of university, was highly amused to being formally announced by a liveried master of ceremonies.

Outside geophysics, Helbig was a lifelong musician. An accomplished recorder player, he maintained a collection of instruments, had a lively interest in Renaissance music and, even in his nineties, participated in two musical ensembles. He was a passionate visitor to the annual Festival Oude Muziek Utrecht (Utrecht Early Music Festival). Attending international conferences never stopped Helbig from practicing his instruments before the official programme began.

‘You don’t mind if I play my recorder this early, do you?’ he once asked one of his PhD students sharing a room with him, already up and ready to fill the morning with music. In 1975 he became known in Germany for a piece of art in macramé, inspired by Nietzsche’s poetry. He enjoyed longevity and in 2017 celebrated his 90th birthday in Hannover, attended by family, friends, and colleagues from around the world.

Helbig’s contributions to geophysics, publishing and education endure, and his combination of rigour, creativity, humour, and intellectual spirit remain an inspiring example for colleagues and students.

Remembered by Jan Douma, Boris Gurevich, Andrew McBarnet, Tijmen Jan Moser, Michael Pelissier, Ivan Pšenčík, Michael Slawinski, Alexey Stovas, Leon Thomsen, Ilya Tsvankin, Bjørn Ursin, Anton Ziolkowski and many others all over the world who came into contact with Helbig and his work.

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Technical Community on Geomechanics is launched

At the International Geomechanics Conference the new EAGE Technical Community was announced.

The official announcement of the creation of the EAGE Technical Community on Geomechanics took place

during the Society President’s Panel at the International Geomechanics Conference (IGS) in Saudi Arabia where Anke Simone Wendt, chair of the committee, represented EAGE and introduced the vision behind this new initiative.

This Technical Community has been founded with its members focused on the role of geomechanics in tunnelling, mining, optimising hydrocarbon recovery, enabling geothermal energy, ensuring the integrity of liquid and solid underground storage, and supporting the safe deployment of new energy technologies in the energy transition field.

It is ready to launch activities with its members and is thrilled to become a place where ideas in geomechanics can grow into solutions as they strengthen their knowledge to impact energy security and sustainability. Make sure you join their community on LinkedIn, update your affiliations and connect with a global network of professionals driving meaningful change in the subsurface world.

Join the Geomechanics Technical Community on LinkedIn

Masterclass on CO2 Storage to return in 2026 Our very successful and well received Masterclass on CO2 Storage is coming back in March 2026.

Our instructors Andreas Busch, Eric Mackay, Philip Ringrose and Florian Doster will continue to explore the different technical aspects of geological CO2 storage through a comprehensive programme of three short courses. In particular, they will focus on risk assessment of CO2 storage, project design and optimisation, and flow mechanics for geological CO2. Participants will have access to a combination of industry projects and academic research that merges geology and energy transition as the core disciplines.

From the previous editions, participants said that the courses were eye-opening in the understanding of carbon capture storage

projects across disciplines and a ‘good state of the art of the academic knowledge on CO2 storage’. Similarly, they noted that the courses were well prepared, in-depth and interactive.

The courses will be taught in three sessions from 24 to 27 March 2026 in Paris, France. Upon registration you may choose between attending an individual course or the complete programme with our All Access Pass.

Scan the QR code for more information

EAGE Education Calendar 4 FEB

EXPLOITATION AND COMMERCIALIZATION POTENTIAL OF NATURAL HYDROGEN –

BY ARNOUT JW EVERTS

DLP WEBINAR

1 LIVE WEBINAR OF 1 HR

17-18 FEB

INTEGRATED METHODS FOR DEEP-WATER RESERVOIR CHARACTERIZATION –

BY JON ROTZIEN

INTERACTIVE ONLINE SHORT COURSE

2 LIVE WEBINARS OF 3 HR EACH

12 MAR

LANGUAGE MODELS FOR GEOSCIENCE APPLICATIONS –

BY THOMAS B. GRANT

STAVANGER, NORWAY DURING EAGE DIGITAL 2026

23-25 MAR STRUCTURAL GEOLOGY MUST-KNOWS – BY PASCAL RICHARD

THE HAGUE, NETHERLANDS

24-27 MAR • FLOW MECHANICS FOR GEOLOGICAL CO2 STORAGE – BY FLORIAN DOSTER • RISK ASSESSMENT OF CO2 STORAGE BY UNDERSTANDING COUPLED THERMOHYDRO-CHEMICAL-MECHANICAL PROCESSES –

BY ANDREAS BUSCH AND ERIC MACKAY • CO2 STORAGE PROJECT DESIGN AND OPTIMIZATION (SALINE AQUIFERS) –

BY PHILIP RINGROSE

PARIS, FRANCE

GEOLOGICAL CO2 STORAGE MASTERCLASS

FOR THE FULL CALENDAR, MORE INFORMATION AND REGISTRATION PLEASE VISIT WWW.EAGE.ORG AND WWW.LEARNINGGEOSCIENCE.ORG.

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EAGE NEWS

Every month we highlight some of the key upcoming conferences, workshops, etc. in the EAGE’s calendar of events. We cover separately our four flagship events – the EAGE Annual, Digitalization, Near Surface Geoscience (NSG), and Global Energy Transition (GET).

APGCE 2026 2nd Curtain Raiser: EAGE Workshop on Exploration and Opportunities in the Paleogene Play 28-29 July 2026 – Jakarta, Indonesia

EAGE/DGG Workshop on Radioactive Waste Storage 6 March 2026 – Münster, Germany Safe disposal of high-level radioactive waste relies on deep geological repositories that satisfy strict geological requirements. Site characterisation is complex and demands high-resolution, combined exploration methods to build reliable geological and water-transport models. The workshop initiated by the newly established EAGE Technical Community on Radioactive Waste Storage will highlights the challenges and present advanced tools such as semi-airborne electromagnetic systems and seismic surveys. Its goals are to unite waste management organisations, authorities, academia and industry; exchange experiences, and discuss multi-scale exploration techniques.

Abstract submission deadline: 30 January 2026 Early bird fee deadline: 8 February 2026

This second curtain raiser for APGCE 2026 focuses on unlocking frontier potential in Asia Pacific’s upstream oil and gas sector.

The Paleogene succession is gaining recognition as one of the region’s most promising yet underexplored petroleum systems.

Once overshadowed by Miocene and Pliocene plays, it is attracting renewed interest through new discoveries, advanced deepwater access, and improved geophysical and geological models.

The workshop offers a platform to share case studies, engage in technical discussions and explore how the Paleogene can unlock new growth opportunities.

Abstract submission deadline: 13 February 2026

Second EAGE/SBGf Conference on Deepwater Brazil Equatorial Margin 26-28 May 2026 – Rio de Janeiro, Brazil

ECMOR 2026 – 20th European Conference on the Mathematics of Geological Reservoirs 8-11 September 2026 – Porto, Portugal

The call for abstracts is now open for the Second EAGE/SBGf Conference on Deepwater Brazil Equatorial Margin, one of the hotspots of frontier exploration. We invite industry experts to share achievements, challenges and bold ideas that can shape future collaborations.

Submit 2–4-page abstracts on topics including: Tectonic and geology of conjugate basins; Basin and petroleum systems; Geoscience technologies; Environment, regulations, safety, and socioeconomics - Lessons learned and case studies; and New opportunities in the energy transition: Offshore wind, CO2 storage potential and Hydrogen.

Mathematical modelling and simulation of the subsurface support UN Sustainable Development Goals 7 and 13 by guiding safe, efficient carbon and hydrogen storage and improving risk management and engineering design. Artificial intelligence enhances these capabilities, enabling more innovative solutions. For over 30 years, ECMOR has united mathematicians, engineers and geoscientists from academia, government and industry to advance numerical modelling of geological systems. The 2026 conference will continue this tradition emphasising CO2 sequestration and large-scale hydrogen storage to address renewable energy intermittency.

Abstract submissions by 29 January 2026

Abstract submission deadline: 8 February 2026

For the latest updates and information, visit eage.org/events FIRST

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More to oil history that you may realise Oil and gas have shaped our modern world more than almost any other resource. They power industries, keep cities running and influence global politics, technology, and daily life in ways we often take for granted. The story behind this global dependence goes back far beyond modern drilling rigs and refineries.

This was the theme of our recent event at La Démocratie, a Parisian venue that once hosted the intellectual circles and political debates of the early 20th century. LC Paris organised this event in collaboration with SPWLA France Chapter and SPE France section.

In this historic setting, Dr Martin G. Luling, a retired SLB expert, was the special guest and gave a talk on ‘The historic origins of oil production’, guiding the audience through the roots of petroleum exploitation and how it evolved into the powerful industry we know today.

Luling began by tracing the earliest known human use of oil to the Absheron Peninsula in Azerbaijan, a region considered the cradle of petroleum exploitation. Natural oil seeps there sometimes ignited on their own, shaping local practices and even influencing Zoroastrian purification rituals centred around fire. Participants from different backgrounds contributed during the conversation, including a guest from the same region who spoke about the early use of oil by Zoroastrian communities.

This added an international dimension to the discussion and showed how varied the historical timeline of petroleum really is.

Luling also demonstrated how oil became strategic for ancient communities as they dug wells to extract light oil

(naphta) for burning and black oil (mazut) for waterproofing, often becoming a cause for conflict, until Peter the Great organised exports to Russia in the early 18th century.

Luling then discussed the emergence of oil exploration in Western Europe in the 18th century, focusing on Eyrini d’Eyrinis in Switzerland and Northern Alsace. Pechelbronn, in the Alsace region, is recognised as the first organised industrial oil exploitation site in Europe, starting around 1770.

Moving into the 19th century, he said that the arrival of steam engines greatly increased demand for oil, driving exploration and production in North America, including the Pennsylvania fields and later Texas, Oklahoma and Louisiana. Luling traced the international expansion of oil trade, noting Marcus Samuel’s creation of Shell to transport Azerbaijani oil to Europe and British colonies, in partnership with Henry Deterding in Indonesia. He concluded that the development of the global oil industry was shaped by technological innovation and exploitation, and strategic trade networks, and that understanding this history is essential for contemporary energy planning and technology development.

The event did more than revisit the origins of the oil industry. It brought people together, highlighted the roots of petroleum history globally and reminded everyone how understanding the past can help shape today’s energy perspectives. A second part of this event is already planned for next year. Paris LC will continue organising events in collaboration with the French chapters, continuing to create opportunities for learning, networking and community building.

Another successful roll-out for borehole geophysics workshop

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The Eighth EAGE Borehole Geophysics Workshop, held from 29 September to 1 October 2025 in Al Khobar, Saudi Arabia, was a resounding success that exceeded expectations in both presentation quality and participant engagement.

Key highlights included the introduction of several new technologies such as TotalEnergies’ Surface Linear Vibrator (SLV), MagiQ Technologies’ GeoLite fibre-optic accelerometers and Petrobras/SLB’s hybrid wireline Distributed

A global community reunited as the Borehole Geophysics workshop returned to its roots in Saudi Arabia.

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Acoustic Sensing (DAS) systems, which demonstrated efficient and environmentally friendly well seismic acquisition in deepwater environments.

Additional innovations showcased included BGP’s large-scale onshore 3D DAS-VSP project that significantly enhanced structural imaging in China’s Junggar Basin, ADNOC/SLB’s application of 4D seismic monitoring to support enhanced oil recovery (EOR), Avalon/ IFP’s 3-C vertical seismic profiling (VSP) work analysing shear-wave polarisation in geothermal reservoirs, Delphi Studio/ INPEX/ADNOC’s use of joint migration

EAGE NEWS

inversion (JMI) technology to improve subsurface imaging, and advancements in microseismic monitoring using DAS that successfully detected events invisible to shallow 3-C sensors.

The workshop also highlighted several best practices and workflows, including TotalEnergies’ use of the surface linear vibrator for reliable and repeatable 4D monitoring, BGP’s implementation of large-scale 3D DASVSP surveys for improved structural imaging, and Opera/TotalEnergies’ studies on the impact of seismic acquisition geometries on 4D velocity anomaly estimation. Delphi Studio/INPEX/ ADNOC further emphasised the value of JMI technology in enhancing subsurface imaging and velocity modelling.

In general, the workshop was highly successful, and discussion revealed emerging trends and focus areas such as angle-dependent imaging for complex geological settings; the use of multiples for enhanced illumination; the increasing role of DAS VSP data and 4D applications in time-lapse monitoring and reservoir characterisation; the integration of 3D VSP data with surface seismic for improved imaging between wells; and the application of convolutional neural networks (CNNs) to distinguish between seismic events and production-related signals.

Key takeaways for GID emphasised the importance of focusing on FWM/JMI to extend lateral illumination through multiples, adopting angle-dependent imaging to enhance frequency and continuity in the VSP domain and combining 3D VSP with surface seismic to improve imaging results between wells. Immediate action plans include continuing to promote DAS VSP for all borehole seismic applications in the oil and gas industry, particularly for 3D VSP in complex geological settings. Overall, the workshop reinforced the significance of advancing subsurface imaging, reservoir characterisation and monitoring, while highlighting the growing potential of DAS, artificial intelligence and hybrid survey designs to enhance the efficiency and effectiveness of seismic monitoring and exploration.

Local Chapter Zhuhai takes off with inaugural lecture on lunar frontiers We are delighted to announce the establishment of the latest EAGE Local Chapter in Zhuhai, China. Established as a platform to bridge local geoscientists, engineers and scholars with the industry’s global frontiers, the Chapter dedicated its very first event to deep space exploration.

The inaugural seminar featured Dr Chunyu Ding, researcher at the Institute of Moon-base Exploration and Observation at Shenzhen University, who discussed ‘The role of lunar-penetrating radar in researching lunar shallow subsurface structures’.

His presentation demonstrated how radar, a powerful geophysical tool, is applied across inter-planetary space to offer new perspectives for deciphering the Moon’s complex geological evolution. The core of Ding’s talk focused on the precise analysis of radar reflection signals, as he detailed how these signals clearly delineate material stratification at various depths beneath the lunar surface. This analysis is crucial for determining lunar regolith thickness and dielectric properties, which are key parameters for all subsequent radar data processing and geological inversion.

As the lecture unfolded, a clear picture of the hidden lunar subsurface emerged. Ding utilised valuable data from the Chang’e-3 and Chang’e-4 missions to demonstrate how multi-layered geological interfaces are pinpointed. The imaging also revealed diverse subsurface structures, including buried ancient impact craters and potential lava tubes. These findings stand as a vivid testament to the Moon’s extended impact history and complex volcanic activity.

The discussion on lunar resources was particularly exciting for attendees. Ding stated that radar signals from specific regions indicate the presence of potential water ice depos-

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Dr Chunyu Ding led an inspiring seminar on Moon exploration for the opening of LC Zhuhai.

its. This discovery is significant not only for understanding lunar resource distribution but also for providing a crucial scientific basis for a long-term human presence and future energy development on the Moon.

The event concluded with a highly interactive Q&A session, where the audience’s enthusiasm was palpable.

Attendees posed numerous questions regarding the application of radar on other planetary bodies, the specifics of lunar geological structures and data interpretation methods for complex radar sets.

This inaugural event of LC Zhuhai was declared a resounding success.

The topic of space exploration should continue to inspire members with the staging of a dedicated session at the EAGE Annual on ‘Geophysics for space resources exploration’. Particular attention will be given to how these initiatives contribute to long-term scientific and strategic objectives.

Building on this foundation, the session will propose a forward-looking perspective envisioning the design, goals and technological requirements of a dedicated mission aimed at probing the lunar subsurface, with implications for both solar system exploration and future human settlement. Read more at eageannual.org – and if you wish to be involved, you have time until 15 January to submit your work!

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EAGE concludes 2025 with strong presence at Associated Society events In October and November 2025, EAGE participated in three major conferences: SPG 2025, SBGf Rio’25 and IGS 2025.

The meetings highlighted how geoscience is evolving at remarkable speed, and how essential global collaboration has become for scientific and professional progress.

Reflecting EAGE’s commitment to deepening engagement across South Asia and supporting regional professional development, our Association participated at the 15th Biennial International Conference & Exposition of the Society of Petroleum Geophysicists (SPG India) in Jaipur, India.

One of the most significant milestones of the event was the renewal of the cooperation agreement between EAGE and SPG India. EAGE president, Dr Sanjeev Rajput, referred to SPG as one of the ‘key bridges’ connecting India’s innovation energy to the global community. ‘Our renewed collaboration helps keep that bridge strong, open and future ready. Together, we can create more room for learning, research and student engagement ensuring that the momentum of India’s subsurface community continues to accelerate’, he said.

Another highlight was the official launch of the BP India Student Challenge, an initiative hosted by bp India and organised by EAGE. The competition offers students invaluable professional exposure offering authentic datasets to work and real exploration challenges.

At the Opening Session of the SBGf Conference Rio’25, EAGE President Dr Sanjeev Rajput highlighted the essential role of professional societies in shaping the future workforce.

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At SPG 2025, EAGE renewed its cooperation agreement with SPG India, placing new emphasis on education, knowledge exchange, and early-career engagement.

SPG 2025 demonstrated how rapidly geoscience is transitioning into the era of AI-native subsurface workflows. ‘Many discussions focused on deep-learning seismic processing, hybrid physics-ML inversion, large-scale cloud computing, and automated interpretation environments that can significantly accelerate project cycles’, Dr Rajput stated.

At the plenary session on ‘Data to discovery: AI for subsurface insights’, Dr Rajput called for a national-scale leap in compute infrastructure. Upstream discovery requires more than data, he said. It demands trusted infrastructure, a realistic view of AI/ ML maturity, and a national compute vision aligned with India’s exploration goals.

The conference also reflected India’s growing commitment to the energy transition, with strong engagement around CCUS screening, geothermal development and near-surface integrated studies for infrastructure and sustainability applications.

Next stop for our president was Rio de Janeiro, Brazil, where EAGE was represented at the SBGf Conference Rio’25 organised by the Brazilian Geophysical Society (SBGf).

At the Opening Ceremony, Dr Rajput delivered a keynote speech noting the essential role that professional societies play in supporting the development of the future workforce, thereby contributing significantly to the advancement of geoscience and engineering.

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At the meeting EAGE renewed its partnership with SBGf with Dr Rajput insisting that this was more than a symbolic gesture. ‘It reflects our shared intent to work together on a sustained programme of workshops, symposia, technical exchanges, and professional development initiatives that will uplift scientific excellence in Brazil and strengthen the global geoscience network’.

Participating later in a strategic panel on ‘How to empower diverse talent in a technology-driven world’, he observed that in a decade of intelligent machines, our greatest challenge isn’t keeping up with technology, but keeping humanity in the loop.

According to Dr Rajput, ‘We need to rethink diversity not as a checklist but as a design principle. If technology is the engine that powers our future, then inclusion must be built into its architecture, not added as a decorative layer. Empowering diverse talent is about creating systems that support professional inclusion, fostering workplace belonging, open access to opportunity, and upholding meritocracy as a guiding principle. When these elements come together, the entire geoscience community benefits from deeper insight, stronger collaboration and more sustainable progress’.

SBGf Rio’25 presented a distinct and regionally grounded set of innovations shaped by the country’s deepwater heritage, geological complexity and strong academic–industry culture. The most prominent

EAGE NEWS

discussions focused on next-generation pre-salt imaging, advanced full-waveform inversion tuned for complex salt geometries, elastic and multi-component imaging, and the integration of multi-sensor OBN datasets, areas where Brazil continues to be recognised as a global leader.

The meeting also expanded into broader applications of geophysics for the energy transition, including offshore wind site characterisation, marine environmental monitoring, subsea infrastructure integrity, and long-term CCUS surveillance.

On duty 12,000 km away from Rio, in Al Khobar, Saudi Arabia, Dr Anke Wendt (SLB), chair of the newly created EAGE Technical Community on Geomechanics, attended the International Geomechanics Conference (IGS 2025), an event hosted by the American Rock Mechanics Association

(ARMA), the Dhahran Geoscience Society (DGS), and SEG. Under the theme Geomechanics: Innovations and Solutions for Energy Sustainability and Resilience, the conference set the spotlight on the growing importance of geomechanics in addressing modern energy demands and challenges. Key conversations revolved around AI and data-driven methods applied in petroleum and drilling geomechanics; hydraulic fracturing (modelling, lab, monitoring, diagnostics, operation), and advances in subsurface energy storage.

As an invited speaker on the society presidents’ panel, Dr Wendt spoke about the creation of the new community on Geomechanics as an initiative that reflects EAGE’s commitment to fostering cooperation, knowledge exchange and skills transfer towards a sustainable future.

She told the meeting: ‘This community supports dialogue across disciplines and generations, focused on responsible energy use. If we can influence how the industry designs, monitors and regulates subsurface activities -from extraction to storage- we’ll strengthen both energy security and sustainability. In short: we’ll help the energy transition stand on solid ground.’

Active participation in Associated Society events is essential to EAGE’s identity and mission. Dr Rajput sees these gatherings as ‘opportunities to listen closely to the priorities of diverse communities, understand emerging needs and ensure our programs remain relevant and future ready.

Our partner societies are like a constellation of lighthouses. Each shines on its region, yet together they guide the global geoscience community toward shared progress.’

February deadline for EAGE Student Chapters to register for 2026

The Chapter of The Year recognition went to the Universidad Nacional sede Bogotá.

The EAGE Student Community is pleased to announce the launch of the 2026 Student Chapter Renewal & Creation Call, inviting university students worldwide to

renew their existing chapter or establish a new one for this year. This initiative offers students a unique opportunity to strengthen their engagement with the global geoscience and engineering community while accessing valuable academic and professional benefits.

All approved student chapters will receive 15 free EAGE student memberships, giving students access to journals, learning materials, webinars and a variety of career development resources. Active chapters will also be eligible to participate in the Online Global EAGE GeoQuiz 2026, where teams will compete in a fun and competitive knowledge challenge.

The best-performing teams will win free

registration to attend the EAGE Annual Conference & Exhibition 2026 in Aberdeen, UK. Renewing or creating an EAGE Student Chapter is an excellent way to promote leadership, encourage teamwork and increase universities visibility within an international network of students, academics and industry professionals. We invite all interested students to take part in this initiative and help strengthen the future of geoscience and engineering education. The deadline to submit the 2026 renewal form is 28 February 2026.

For more information about the Student Renewal Process, please contact the EAGE Student Team at students@eage.org.

EAGE Student Calendar 9 JAN

LAURIE DAKE CHALLENGE + GLOBAL ENERGY TRANSITION CHALLENGE 2026: APPLICATIONS DEADLINE

ONLINE

9 JAN

BP INDIA STUDENT CHALLENGE: APPLICATIONS DEADLINE

ONLINE

21 JAN

EAGE STUDENT WEBINAR: “AN INVESTIGATION OF NATURAL PROCESSES INFLUENCING SURFACE SEAWATER PH DYNAMICS” BY RICHARD ROSAS

ONLINE

8-11 JUN

87TH EAGE ANNUAL CONFERENCE & EXHIBITION (STUDENT ACTIVITIES)

ABERDEEN, UK

FOR MORE INFORMATION AND REGISTRATION PLEASE CHECK THE STUDENT SECTION AT WWW.EAGE.ORG.

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Workshop explored geophysical techniques for monitoring CO2 storage

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Lee Hunt (Carbon Alpha), Don White (Geological Survey of Canada) and Patricia Montoya (ExxonMobil) report on the First EAGE Workshop on Geophysical techniques for monitoring CO2 storage held on 21-22 October in Toronto, Canada.

Some of the participants at the workshop.

The workshop focused on geophysical techniques that will play an important role in monitoring carbon geological storage (CGS) projects. The goal of the workshop attended by 43 international participants was to help connect ideas and methods in monitoring for the new wave of commercial projects underway and those on the way.

The majority of formal presentations focused on seismic applications for monitoring CGS projects. It was generally recognised that the cost of full time-lapse 3D seismic monitoring is a hindrance to its widespread general utilisation within monitoring programmes.

This challenge is being addressed by the development and demonstration of ‘sparse’ and/or hybrid seismic or multi-physics acquisition methods as well as strategic combinations of time-lapse 2D and VSPs. Alternative/complementary methods presented included gravity, electrical resistivity and time-lapse gamma ray logging for fluid flow. AI applications were proposed for identifying CO2 leakage and well log extrapolation/ interpolation.

Technical challenges identified included the need for methods of early leakage detection, reduction in environmental impact of monitoring methods, methods for regional pressure monitoring, the curation of extremely large volumes of data, turnaround times for monitoring results for decision-making, and automated monitoring.

It was suggested that evolving technologies should be validated/ demonstrated at test sites with multi-agency support.

As a central theme of the workshop, strategies for effective and efficient monitoring of CGS projects were discussed at length.

Although diverse opinions were expressed, it was generally agreed that the monitoring programmes should be based on project risks which are identified at the start of a project, are updated during site characterisation and evolve over the lifetime of the project as storage performance is understood. Site characterisation was identified as a crucial stage in the lifetime of the project as it should provide the key assurance of safe and secure long-term CO2 storage. It identifies additional data that may be required to reduce the 16

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risks at the outset of the project, provides a baseline against which subsequent monitoring data are compared to determine storage conformance, and ultimately guides the monitoring plan. Thorough site characterisation can be expensive, though it may ultimately reduce capital costs in subsequent monitoring. The timing puts it into tension with the desire to minimise large expenditures prior to a final investment decision for the project or site.

Another point of discussion concerned the monitoring effort required during the initial storage operation. These approaches might be termed ‘precautionary’ vs ‘triggered’. In the former, the contention is that extensive monitoring is required for the initial period of injection operations to establish that the storage system is operating as predicted and to calibrate both the monitoring methods and the dynamic storage model. As conformance is demonstrated, the monitoring effort can be reduced accordingly. The latter approach presumes that the site is well enough characterised that only monitoring of key indicators is required. An indication of non-conformance would trigger a response that may include additional monitoring to determine appropriate mitigation measures. Some members of the workshop supported the cautionary approach as appropriate for the initial CGS projects as any failure of these first industry projects could be detrimental to public acceptance. However, other members felt that appropriately characterised sites with low-risk profiles might be appropriate for a triggered approach from the onset.

Interactive session The workshop closed with a three-hour interactive session where all attendees participated in solving hypothetical monitoring problems.

Three projects were quickly introduced and attendees broke into small groups picking a task associated with one of the projects. The tasks, or problems, included producing an MMV programme for the project or a mitigation plan for one or more threats or events.

All tasks were given a budgetary limitation and cartoon cost sheet for any action or mitigation to force prioritisation in the solutions.

Attendees were given creative licence to add monitoring solutions even if they were not provided in the cost sheet. After working on the tasks for a short period of time, the work groups individually presented their solutions to the rest of the attendees. A discussion about the work of each group ensued.

The goal of this session was not to produce actionable advice on these problems, nor could the proposals be relevant to project liability or duties in the real world. Real MMV plans require months – usually years – of work by multi-disciplinary teams. The session proved a valuable a tool for debate, and to help reinforce the learnings from the preceding talks and discussion.

A summary of key points from the session follows. We removed commercial names from some of the techniques, but readers will

EAGE NEWS

note that the teams chose a wide variety of monitoring techniques rather than each choosing the same approach. One exception to this is that three of the four working groups did choose to reprocess the baseline 3D or employ specialised seismic processing.

Project 1 followed an onshore carbon storage project in its early stages of development in Saskatchewan Canada. This shallow (~1000 m deep) Cambrian aged storage complex is situated in a relatively unstructured area with low historical seismicity. The storage reservoir is over 150 m thick and is believed to have far greater capacity and injectivity than project needs. The overlying seal section is composite in nature with seven thin, but regionally correlatable shales, separated by sands. The team chose to examine the threat of a potential fault outside of the expected plume and pressure affected region. The fault appears to be of limited lateral extent, and there is significant uncertainty that it is being imaged and/or interpreted correctly. Fault seal analysis suggests that this fault may enable a CO2 escape through the primary and ultimate seals.

The team suggested reprocessing the baseline 3D near the fault, using CO2 tracers and additional borehole gravity survey and CSEM. Targeted VSP around this fault was later changed to a targeted 2D survey when it was pointed out that the fault was far beyond the illumination range of a VSP. Project 2 concerned a deep (~2500 m) carbonate onshore storage complex. The overlying seal section was a 500 m thick shale section. There was also the possibility of simultaneously injecting into a shallower (~1000 m deep) sandstone reservoir, which is overlain by an unconventional tight shale gas play element about 50 m above the sandstone reservoir. The task of this team was to choose the best storage reservoir and formulate an MMV plan.

The team suggested the reprocessing the baseline 3D, pre-stack inversion, seismic cube and perform attribute analysis to identify potential faults, hybrid monitoring for detection of natural and induced seismicity, injectivity testing for the unpredictable carbonate reservoir, InSAR monitoring, and legacy wellbore monitoring.

Project 3 followed a series of hypothetical threats and events at Sola, offshore Norway. This fault bound storage complex is ~1100

m deep. 2.5 Mta of injection is planned at two injection wells (Alpha and Beta). Risks in the area include active seismicity, evidence of gas/fluid escape in the seafloor nearby and the potential for CO2 migration into adjacent structures. Two groups worked on different threats associated with Project 3.

The first threat was the potential for an unexpected CO2 migration from the Alpha injector into a nearby structure via a fault complex as well as through a structural syncline within the reservoir. The team performed a bowtie analysis to help prioritise their

Project teams at work.

monitoring plan. This yielded a plan to model the pressure front and CO2 saturation plume; enhance the 3D seismic fault mapping with select imaging techniques plus iterate reservoir modelling with this new data, use a continuous network of focused or surgical seismic sources and receivers to detect the CO2 saturation front, and reduce injection rates into the Alpha injector and increase injection rates into the Beta injector.

The second threat for Project 3 involved the present day observed seafloor CO2 and/or methane emissions near injectors of this project. These pockmarks and gas/fluid escape features suggest there might be potential vertical natural pathways (faults, chimneys, etc.) that could present a vertical containment risk to CO2 injection.

The working team assessed if the escaped fluid is CO2 from injection using tracer monitoring, seabed monitoring, reducing injection pressures if the escaping fluids are from the injection project, and using controlled source electromagnetic surveys to finely monitor the CO2 migration.

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Simpler signing up for student teams entering 2026 Challenges Teams planning to take part in EAGE’s two big student Challenges in 2026 should find it easier to sign up.

We are introducing a unified registration process for the Laurie Dake Challenge and the Global Energy Transition Challenge (GETC), formerly the Minus CO2 Challenge. Beginning this cycle, teams can apply through a single application form and a single deadline, making participation easier, more efficient and more accessible for students around the world.

Applications for both competitions opened in November 2025, and teams will be able to select whether they wish to participate in one or both challenges.

Each competition follows its own timeline and delivers its final presentations at different EAGE flagship events – the Laurie Dake Challenge at the EAGE Annual in Aberdeen in June 2026, and the GETC at the EAGE GET Conference in November 2026. The registration deadline will be uniform for both: 9 January 2026.

This new approach aims to expand the global reach of EAGE’s student competitions, enhance their educational impact, and increase visibility and accessibility across the community. By streamlining the process, EAGE encourages more diverse teams to engage with two of its most influential learning and innovation platforms.

To participate, students must form a team of 3-5 members, consisting of Bachelor’s and/or Master’s students, with a maximum of one PhD student

Award-winning ceremony for the Laurie Dake Challenge 2025 at the EAGE Annual Conference.

per team. During the application, teams will indicate their preferred challenge(s) and submit a declaration of academic integrity along with the required motivational letter(s). Teams applying to both competitions should provide one motivation letter per challenge, outlining their interest, project idea and team introduction. Before submitting, participants are also encouraged to carefully review the rules and procedures for each competition.

As of 2026 the former Minus CO2 Challenge has been rebranded into the Global Energy Transition Challenge to better reflect its expanded scope. In addition to carbon sequestration, the competition now invites proposals across broader energy transition themes, including geothermal energy, hydrogen, energy storage, wind energy, and more, thereby aligning its mission more closely with the GET Conference, where finalist teams will present their work.

The Laurie Dake Challenge remains one of EAGE’s flagship academic competitions, inviting students to integrate geoscience and engineering expertise to address complex, real-world subsurface challenges. The top three teams will earn a place in the final round at the EAGE Annual 2026 in Aberdeen, while the three leading GETC teams will present their solutions at the 2026 GET Conference.

EAGE invites students worldwide to embrace this opportunity to innovate, collaborate and push the boundaries of geoscience and energy transition knowledge.

Applications close on 9 January 2026, and we encourage all interested teams to prepare early, gather their strongest ideas and be part of this exciting journey.

Students ready to take on the challenge can apply through the official portal and contact the EAGE Student Team at students@eage.org for any questions or guidance.

The EAGE Student Fund supports student activities that help students bridge the gap between university and professional environments. This is only possible with the support from the EAGE community. If you want to support the next generation of geoscientists and engineers, go to donate.eagestudentfund.org or simply scan the QR code.

Many thanks for your donation in advance!

D O N AT E T O DAY !

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PERSONAL RECORD INTERVIEW

Henk Kombrink

Personal Record Interview

Geoscience editing was news to him Since 2022 Henk Kombrink has been editor of the popular Norwegian publication GeoExpro, already garnering two professional society communication awards to his name. It was not the job he expected when embarking on a career as a geologist over 20 years ago.

He does keep a direct connection with rocks through a small business accepting, storing and distributing unwanted North Sea oil company cores.

Netherlands upbringing I spent my childhood in a little hamlet in the north of the country, where we had a big garden including a bit of woodland.

We used to play there a lot, and built stuff all the time. When digging a hole at some point, I looked at the yellow wind-blown glacial sand on the walls and wondered where all these grains were from, and when they were deposited. My first fascination with geology!

Geography to geology Utrecht became my hometown in 1998, when I started my physical geography studies. It was the field work that attracted me. As I progressed through the years, geology appeared on my radar more and more, and I started to attend some courses. This culminated in applying for a PhD position at the Geological Survey about the Carboniferous of the Netherlands, and I was accepted. Ever since, I have felt more like a geologist than a geographer, but I don’t regret my initial choice.

Early work history Following completion of my PhD, I stayed with the Geological Survey for a few years. It was great to work in the Deep Subsurface Mapping Team, and I particularly enjoyed being part of big projects such as the Southern Permian Basin Atlas.

It opened many doors, including a visit to the legendary petroleum geologist Ken Glennie in Scotland. this was memorable as he was in at the beginning when the Groningen field was found in 1959.

First years in Aberdeen In 2011, I decided it was time to move somewhere else, and that somewhere became Aberdeen. The job was not entirely what I had expected: the research department at Total E&P UK was a little distant from operations, where I really wanted to be. Then, just when the oil price started to drop in 2014, I secured a role in the subsurface consultancy group LR Senergy, at that time part of Lloyds Register.

The years that followed were tumultuous, many redundancy rounds followed, but I survived somehow, until the last one hit us in 2020.

Going independent Our entire group was let go in 2020 when the pandemic unfolded. But, as my mentor David Mudge used to say; ‘Henk, you have to go independent at the age of 40, it’s the right time’. I never expected that to happen, but it did. Fortunately, I could start as a freelance writer for the website expronews.com straight away, working with Ingvild Carstens and her father Halfdan. We built up a relationship on Teams, as they were in Norway, but it worked.

Evolution as a communicator The first two years as a freelancer were great, then Halfdan unexpectedly asked me to take over the editor role for the GeoExpro magazine and website. I agreed, but on condition that I could take a level of ownership. And so it happened. In 2022 I became co-owner of the magazine with Ingvild and we’ve been running it together since. We had to FIRST

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learn to work together as a small team, but these days I’m really happy with how it has turned out.

North Sea core story In 2017, when attending a meeting in preparation for the Annual Devex Conference in Aberdeen, I overheard someone saying that they were keen to rehome some core from the Dunlin field. From that moment, I’ve been on the case. It led to the founding of North Sea Core, a small business taking delivery of unwanted core from the UK oil and gas industry. We upcycle the cores and send them all over the world for education, analysis and licensing rounds.

Geoscience future?

I am not very optimistic. From what I observe around me in Aberdeen and through my exposure as an editor worldwide, I see that there is less demand for geoscientists as we further engineer our energy system, including unconventional drilling for which fewer geologists are needed. This goes against the narrative that more geoscientists will be required going forward. But I don’t see it.

Aberdeen as a base I have been in Aberdeen for 14 years now, which is much longer than I expected.

Despite what many people say, it is still a good place to live and work. The air is clean, the beach is around the corner, and the mountains are not far away. Scotland is a beautiful country and the people are nice too.

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Two defining events point to how energy fortunes will continue to track At the beginning of a new year, it is difficult to resist the tempand advanced technology, set the tone with quotable lines any tation to get into predicting what we can expect in the 12 months speechwriter would be proud of. to come. It is a mug’s game of course. The upside is that very He said: ‘With all the static around, it can be challenging to few people remember what you forecast, so you can usually brag concentrate on what is genuinely material to our business. At times about what you got right without fear of being reminded of those like these, my approach is straightforward: tune out the noise, track things you got wrong. the signal. And the signal indicates that while near-term uncertainty Looking ahead at likely developments in the energy sector is real, long-term demand remains robust. It advises us to balance in 2026, there is a good chance of being on the ball (not crystal). cost discipline with capital investment, maintain a laser focus on At the end of last year, there were two defining events that surely efficiency, and invest in people, technology and AI.’ point to how energy fortunes will continue to track around the Unafraid to predict the future, Al Jaber estimated that $4 trilworld this coming year: one was the annual ADIPEC (Abu Dhabi lion in annual capital investment is required for grids, data centres Petroleum Exhibition and Conference) held on 3-6 November and all energy sources up to 2040. ‘You can’t run tomorrow’s in Abu Dhabi, the other was the COP30 (the economy on yesterday’s grid,’ he said. ‘Here 30th UN Climate Change Conference) held are the facts: electricity demand will continue ‘COP30 made the on 10-21 November in Belém, Brazil. The to surge through 2040, with power for data contrast between the two in ambition and headlines, but in all centres increasing four-fold, 1.5 billion people outcome speaks volumes. migrating to cities, and more than two billion the wrong ways.’

ADIPEC is the spectactularly impressive air conditioners being activated. Aviation will annual forum for the world’s energy business also expand, with the global airline fleet with an obvious bias towards the oil business. The 2025 statistics doubling from 25,000 to 50,000 aircraft. As a result, renewables alone are astounding. According to the organising company, dmg will more than double by 2040; LNG will increase by 50%; jet (owned by a Daily Mail company and responsible for many other fuel will grow by more than 30%, and oil will remain above 100 massive events in various industries), a record 239,709 attendees million barrels per day beyond 2040, increasingly utilised not just from 172 countries were gathered. for mobility, but also for materials.’

Just about every major oil/energy company participated Doug Burgum, US Secretary of the Interior and chairman including ADNOC, Aramco, BP, Chevron, CNPC, ExxonMobil, of the the country’s National Energy Dominance Council, was NNPC, Oxy, Petronas, Petrobras, Shell and TotalEnergies. From also on the platform with a clear message. ‘We stand at a critical all accounts the mood was buoyant, in other words, the industry moment in time, where innovation, national security and proshas got its mojo back, able to talk unapologetically about its perity intersect like never before,’ he said. ‘Energy has always contribution to a world that needs resilience and security through underpinned national security and prosperity, but today those energy addition to achieve sustainable growth. forces are converging in a way history has never seen.’

At the Opening Sultan Ahmed Al Jaber, managing director Burgum also provided a clue as to why the Trump Adminand group CEO of the Abu Dhabi National Oil Corporation istration is so focused on maximising its energy resources. ‘For (ADNOC) and the United Arab Emirates’ minister of industry all of history, knowledge has been power. But today, for the

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first time, a kilowatt of electricity can be converted directly into intelligence. We now live in a world where we can manufacture intelligence. That is a first in human history … I’ve stopped calling them data centres. These are factories manufacturing intelligence. This manufactured intelligence is a general-purpose technology, capable of transforming medicine, education and every industry, including ours.’

The electricity theme was later picked up by Patrick Pouyanné, chairman and CEO, TotalEnergies. He told a session ‘This transition is not about less energy; it is about more energy with fewer emissions. The planet needs more energy, full stop. And when we move from thinking in terms of oil and gas to thinking in terms of energy, that still means more oil and more gas, because they remain at the core of the system. But increasingly, the energy everybody is looking at now is electricity.’

ADIPEC will return to Abu Dhabi on 2-5 November 2026 when, according to dmg, it will ‘continue its mission to unite the global energy sector and drive system-wide transformation for a secure, inclusive and sustainable future.’ But the event, however momentous, is unlikely to attract anything like the coverage accorded to the COP meetings, indicative of the energy transition dilemma.

COP (Conference of the Parties) summits, initiated by the 1992 United Nations Framework Convention on Climate Change began in 1995 in Berlin as the most significant inter-governmental initiative to combat climate change. Over three decades it has set out some important internationally agreed statements of intent. Compliance has been another matter.

The Kyoto Protocol (1997) was the first landmark event. It called for reducing the emission of six greenhouse gases in 41 countries plus the European Union to 5.2% below 1990 levels during the ‘commitment period’ 2008–12. The Paris Agreement (2015) at COP21 has proved the most enduring reference: it is a legally binding accord to hold global temperature increase to well below 2°C above pre-industrial levels and pursue efforts to limit it to 1.5°C above pre-industrial levels. Around 195 countries have signed up but the US has pulled out with President Trump referring to the whole exercise as a ‘con job’ or ‘hoax’. The Glasgow Pact (2021) addressed accelerated phasing down of coal power; Sharm El-Sheikh, (2022) established a Loss and Damage Fund to help vulnerable nations deal with the impact of climate-related destruction; and COP28 in Dubai (2023) finally agreed after 28 years of negotiations a somewhat unconvincing commitment to a Transition from Fossil Fuels (2023).

COP30 made the headlines, but in all the wrong ways and even before it got underway. The choice of the Amazonian venue of Belém by the host country Brazil was obviously political, apparently reflecting President Lula’s wish to focus on the important role of the Amazon in climate stability. But the move exposed the city’s inadequate infrastructure and accommodation facilities to cater for the more than 56,000 delegates attending. The siting of the

event also attracted protests throughout the proceedings from local indigenous people, angry that not enough was being done to protect the region from the impact of mining and agribusiness. Optics were not improved when, on the last day but one, a fire broke out at the venue disrupting already fractious negotiations.

Attendance at COP30 was impressive: 194 out of the 198 UN-registered countries participated. But the notable absentee was the US, consistent with the Trump Administration’s sceptical view of climate change mitigation measures, effectively undermining any meaningful global agreements on decarbonisation measures.

Environment groups expressed dismay at the 1600 ‘fossil fuel’ lobbyists attending, a significant number of whom were advocating for carbon capture and storage. According to the Centre for International Environmental Law, the CCS proponents are exploiting the boom in AI and the associated surge in energy demand to cement further fossil fuel expansion, using carbon capture promises to mask the devastating climate impact of fossil fuels.

Like so many COP conferences, this latest edition met with obstruction and obfuscation when it came to drafting any action plans, leaving media channels non-plussed in their reporting.

More that 80 countries had gone along with President Lula’s call for a road map to transition away from fossil fuels. This was blocked by Saudia Arabia, Russia and other oil-dependent nations. Colombia backed by some 90 other countries will try to progress the road map idea in a meeting outside the UN process next April. A proposed road map to end deforestation is also back to the drawing board with new proposals being prepared for COP31 in Turkey; however, the meeting did witness the launch of the Tropical Forest Forever Facility to protect tropical forests with significant funding promised.

There were other positives from COP30. These included tripling of the per annum finance to be paid by rich nations for adaptation to climate change in poorer countries, but the deadline to reach the target was extended from 2030 to 2035 and will be way short of the annual $300 billion once talked about. There was recognition for the first time of carbon trade measures such as the EU’s Carbon Border Adjustment Mechanism. A just transition mechanism was agreed to protect the rights of all peoples including workers, women and indigenous communities.

The conference’s grudging acknowledgement of the UN Intergovernmental Panel on Climate Change report as the ‘best available science’ to be reviewed along with those ‘produced in developing countries and relevant reports from regional groups and institutions’ hinted at a scepticism previously absent.

No wonder Simon Stiell, UN climate change executive secretary, qualified his statement at the closing plenary session that ‘COP30 showed that climate cooperation is alive and kicking, keeping humanity in the fight for a livable planet.’ He felt compelled to add: ‘I’m not saying we’re winning the climate fight. But we are undeniably still in it, and we are fighting back.’

We can only guess how that will transpire in 2026.

Views expressed in Crosstalk are solely those of the author, who can be contacted at andrew@andrewmcbarnet.com.

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HIGHLIGHTS

INDUSTRY NEWS

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ExxonMobil posts bold earnings plan

Westwood research shows that rise in exploration wells will not happen any time soon The number of companies drilling high impact exploration wells has fallen by 50% between 2020 and 2024, according to research by Westwood.

Some 136 companies have exited exploration completely and another 102 remain in exploration but didn’t drill any HI wells in 2020-2024.

Only 17 new exploration companies created since 2014 have drilled HI exploration wells in the last five years and still exist.

‘Companies need to return to drilling, and a new wave of companies needs to be created if exploration is to increase significantly, but it’s unclear if the investor appetite will be there,’ said Westwood.

A delayed energy transition and expectations of higher future oil and gas demand have led to calls for more exploration to plug future supply shortfalls after a decade of cutbacks and declining exploration discoveries, said Westwood.

Global replacement of production by HI exploration discoveries declined to only 11% in the 2020-2024 period compared to 33% in 2010-2014, according to its research.

According to Westwood research, the number of E&P companies drilling HI exploration wells fell by half from 326 in 2010-2014 to only 162 in 2020-2024. This fall mirrored the decline in the number of HI exploration wells completed per year,

which fell from an average of 150 per year in 2010-2014 to 77 in 2020-2024.

Of the original 326 companies, only 88 (27%) drilled HI exploration wells in 2020-24, while 136 companies (41%) had exited exploration completely and 102 (32%) remained in exploration, holding exploration acreage but not drilling.

More than half of the companies who exited exploration have merged with or been acquired by another company, said Westwood. In almost all cases the M&A transaction resulted in fewer exploration wells being drilled than the individual companies did before the combination, it added. Another 24 companies made strategic exits from the upstream sector. Thirteen remained in upstream but not exploration, 20 companies entered administration and/ or were dissolved, and 10 became inactive.

‘Several of the 102 companies who didn’t drill HI wells in 2020-2024 but still hold exploration licences could return to HI exploration drilling if strategy changes and funding allows,’ said Westwood. The 88 explorers who were still drilling HI wells in 2020-2024, drilled 28% fewer net HI wells, on average, compared to 2010-2014.

The 88 continuing explorers were joined by additional 55 companies, who held acreage but did not drill a HI well in 2010-2014, Westwood added.

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HI exploration wells in 2020-2024 did little to replace the 136 companies that exited exploration,’ said Westwood. ‘Only two were brand new listed small exploration companies compared to 47 listed small companies that exited exploration.’

Westwood said that many of the larger companies have now committed to increase exploration spending, some by up to 50%, but the dramatic fall in the number of companies active in exploration drilling makes stepping up drilling activity much harder. If the industry were to return to 2010-2014 levels of drilling, it would require the remaining E&Ps to drill roughly twice the number of wells they did in the $100/barrel+ 2010-2014 period. ‘This is an unlikely proposition, so more HI drilling is going to need more companies returning to exploration and a new wave of E&P company start-ups,’ said Westwood.

‘The ability of the industry to materially increase discovered resources is not just limited by the attractiveness of the geology available to explore – the rarity of golden plays like the pre-salt in Brazil or the Upper Cretaceous in Guyana is well documented,’ said Westwood. ‘It is also limited by the smaller pool of HI explorers, their capacity to fund HI drilling and their ability to build prospect inventories big enough to support more drilling. Those calling for the industry to explore more may be disappointed.’

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TGS characterises 13 US basins TGS has completed a multi-year reservoir characterisation project across 13 US basins, providing formation-level petrophysical interpretations to model reservoir performance and assess CO2 storage feasibility.

The project delivers a comprehensive dataset resource and integrated geological frameworks that incorporate petrophysical properties, stratigraphy, and test data to enable advanced, multivariate analysis for robust decision-making for energy strategies.

‘When combined with other TGS solutions such as well performance and well economics datasets, this resource delivers a comprehensive view of asset potential, supporting decisions from permitting and development through performance optimisation and eventual abandonment,’ said TGS. The completed basins include: Gulf Coast, Central Gulf Coat-Haynesville, East Gulf Coast, Appalachia, Illinois, Michigan, Uinta, Piceance, Paradox, Greater Green River, Wind River, Powder River, and Greater Williston. Together, these regions represent critical areas for both conventional and emerging energy strategies.

Project highlights including 48,000+ wells analysed with full petrophysical interpretation calibrated to core data for maximum accuracy. Integrated stratigraphic frameworks across 340 formations were evaluated, delivering basin-wide geological consistency and detailed reservoir characterisation for cross-basin comparisons.

There are more than 3700 regional property maps covering petrophysical attributes like porosity, permeability, pressure, and CO2 storage capacity trends for major reservoirs. Advanced data integration includes inferred curves, bottom-hole temperatures, core, and wireline formation tests for robust modelling and calibration.

David Hajovsky, executive vice president of multi-client at TGS, said: ‘With more than 48,000 wells, 340 formations, and thousands of property maps calibrated to core, temperature, and pressure data, we’ve created a resource that integrates seamlessly into existing workflows and accelerates evaluations across multiple energy strategies.’

Shearwater and Searcher launch latest 3D survey offshore Brazil Shearwater Geoservices and Searcher Seismic have launched the third season of their multi-client 3D seismic data acquisition in the Pelotas Basin, offshore Brazil.

The survey, which is expected to be completed early Q2 2026, is being shot by the vessel SW Empress and will add a further 7500 km2 of 3D data, building on the 9500 km2 already acquired.

The Pelotas Basin shares conjugate margins with the prolific Orange Basin, recognised as an emerging super basin.

‘This geological relationship strengthens Pelotas’ exploration potential, drawing

significant industry attention following recent discoveries on the African margin’, said Searcher. By leveraging insights from across this conjugate trend, explorers have an opportunity to unlock new plays and prospectivity on the South American side, it added.

Irene Waage Basili, CEO of Shearwater, said: ‘We continue to expand our multi-client market position through disciplined investments in co-operation with partners and the E&P industry. The Pelotas Basin success demonstrates the complementary strengths of Shearwater and Searcher Seismic, where we together

SW Empress.

will acquire more high-quality data in one of the world’s most promising exploration regions.’

PXGEO wins two big OBN contracts offshore Brazil PXGEO has won two big contracts from a Petrobras-led consortium to deliver seismic data acquisition and monitoring services in the Santos Basin, offshore Brazil.

The projects will run consecutively in 2026 with PXGEO deploying its proprietary MNode 4C ocean bottom node (OBN) technology. MNode technology delivers a 300-day battery life, enabling 24

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the extended deployment time needed for larger, more complex surveys, said PXGEO. The enhanced operating time means surveys can run uninterrupted for extended periods, reducing the need for frequent retrieval and redeployment and projects with timelines challenged by high levels of environmental standby, said Shearwater.

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Charles ‘Chuck’ Davison Jr, PXGEO CEO said: ‘As reservoirs grow more complex and exploration pushes into deeper waters, so does the need for high-resolution seismic surveys. Over the past four years, we have completed six surveys in the region, where our reputation is continuing to grow as operators see the value our technology unlocks.’

INDUSTRY NEWS

Viridien appoint Henning Berg as CEO Henning Berg will take over as group chief executive officer of Viridien in June 2026.

Berg worked for SLB for 27 years, where he was recently in charge of the Subsea Integration Alliance and the One Subsea joint venture and has held several senior global leadership roles. ‘His career combines deep operational expertise with strong exposure to technology, business development, and international management,’ said Viridien.

In line with the board’s earlier commitment to limit the combination of the chair and chief executive officer (CEO) functions to a temporary period, Sophie Zurquiyah will step down as CEO but remain as non-executive chair to ‘maintain strategic continuity and to guide Viridien’s long-term vision’.

‘Since 2018, her leadership has repositioned Viridien as an asset-light, technology-driven company with a stronger financial foundation and a more diverse portfolio,’ said Viridien in a statement.

Berg has been appointed after a thorough selection process, coordinated by Colette Lewiner, chair of appointment, remuneration and governance committee, and Philippe Salle, lead director. Berg will join Viridien on 3 March 2026, as chief operating officer, ensuring ‘a structured and gradual transition to the CEO role’.

His appointment as director will also be submitted to the shareholders for approval at the 2026 general meeting.

Philipe Salle will continue to serve as lead director.

Colette Lewiner, chair of the appointment, remuneration and governance com-

mittee, said: ‘On behalf of the board of directors, we extend our sincere appreciation to Sophie for her tremendous leadership, under which Viridien has achieved a profound and resilient transformation and is now well positioned for the future. We are confident that Henning’s experience and operational strengths will allow him to leverage the group’s solid foundations and effectively support Viridien’s growth.’

Zuruiyah said: ‘I am proud of the group’s accomplishments over the past eight years. I am delighted to hand over the group CEO role to Henning, whose knowledge and experience will support Viridien’s continued success.’

Berg said: ‘I thank the board of directors and Sophie for their trust, and I look forward to working closely with the teams to drive sustainable growth for the group.’

BGP and TGS shoot 3D survey offshore Suriname

BGP Prospector will tow eight streamers, each 6-km long, at a depth of 9 m.

BGP and TGS have begun a 3D seismic survey for Staatsolie in a shallow offshore area off the Suriname coast of Saramacca and Coronie.

The multi-client survey in the shallow offshore area is being conducted in an area of approx. 2000 km2 with water depths ranging from 20 m to 50 m to map potential oil and gas deposits.

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This survey is an important step in further exploiting Suriname’s offshore oil and gas potential, aligning with the Open-Door Offering that started on 24 November 2025. The Open-Door Offering invites international investors to participate in new exploration and development opportunities in our offshore areas.

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The vessel BGP Prospector will tow eight streamers, each 6-km long, at a depth of 9 m.

Under the multi-client agreement Staatsolie does not bear the full costs of the survey, owns the data, can use it for its own exploration activities, and receives a share of the proceeds from its sale.

The Open-Door Offering in the prolific Guiana Basin, represents some 60% of Suriname’s offshore acreage, from shallow waters to deep offshore.

Companies can select their acreage of interest, propose a work program, and choose between a production sharing contract (PSC) and a joint study agreement (JSA)/technical evaluation agreement (TEA).

Staatsolie has also launched its GeoPortal, providing a graphical interactive view of all geological and geophysical data available for interested companies and available to lease at ‘an attractive discount’. Finally, Staatsolie has posted on its website the GeoAtlas of Suriname, which that describes the geology and petroleum potential of the Guiana Basin based on decades of data gathering and analyses.

INDUSTRY NEWS

UK launches carbon storage licensing round The UK North Sea Transition Authority (NSTA) has opened a carbon storage licensing round offering 14 locations in Scottish and English waters for exploration.

The areas to be offered fall into two broad categories: depleted hydrocarbon fields selected by the NSTA and saline aquifer sites identified following a ‘Call for Nominations’ earlier this year.

After industry partners indicated sites of interest which offered a greater chance of successful project delivery, the NSTA has offered five areas in Scottish waters and nine off the coast of England.

Successful applicants will require a seabed agreement from either Crown Estate Scotland or the Crown Estate in English waters. Application deadline is 24 March 2026 and licences are expected to be awarded in early 2027.

Gus Jaspert, managing director, marine at the Crown Estate, said: ‘We have worked with the NSTA to ensure the interests of other vital sectors including offshore wind, aggregates, cables and nature were considered. We look forward to continuing to work together through our Marine Delivery Routemap programme as we evolve our approach to seabed leasing for carbon capture and storage.’

On 8 December 2025, the NSTA published updated Guidance on the Application for a Carbon Dioxide Appraisal and

BRIEFS The US’ Lease Sale Big Beautiful Gulf 1 lease sale in the Gulf of America has generated $280 million in high bids for 181 blocks across 80 million acres.

Thirty companies submitted bids totalling $372 million. The US Bureau of Ocean Energy Management offered approximately 15,000 unleased blocks across the Western, Central and portions of the Eastern Gulf Planning Areas. To encourage strong participation and spur investment, a 12.5% royalty rate was applied for shallow and deepwater leases, the lowest deepwater rate since 2007.

Gus Jaspert, managing director, Crown Estate.

Storage Licence. The NSTA said it will continue to work with the Crown Estate on streamlining application processes for developers.

In the UK’s first carbon storage licensing round in September 2023, 21 carbon storage licences were offered. The NSTA subsequently awarded the first storage permits to two projects – Endurance and HyNet. The Endurance site, off the coast of Teesside, which could store up to 100 million tonnes of CO2, received a permit in December 2024, and Liverpool Baybased HyNet, which could also store up to 100 mt CO2 over 25 years, received three permits in April 2025.

The projects, funded from the UK’s government’s commitment of up $28 billion, could contribute around $6.7 billion per year of gross value to the UK economy by 2050.

The Nigerian Upstream Petroleum Regulatory Commission (NUPRC) has launched the Nigeria 2025 Licensing Round. The round includes 15 onshore blocks, 19 in shallow waters, 15 frontier assets and one deepwater block. https:// br2025.nuprc.gov.ng/ Greenpeace has welcomed the British government’s North Sea Future Plan, in which it has confirmed that no more licences for new oil and gas will be issued, Greenpeace UK’s co-executive director, Areeba Hamid, said: ‘The government has shown genuine global climate leadership, making the UK the world’s largest economy to call time on new fossil fuel exploration. This is a major milestone.’

TGS has launched a multi-client 2D-cubed project covering the offshore India Andaman region. 2D-cubed is a structurally conformable interpolation technology that transforms 2D seismic data into a regional-scale 3D volume.The project covers 640,000 km2, providing insights into the siliciclastic shallow and deepwater sediment basins of this region.The project area covers four of the OALP-X Bid Round blocks in the Andaman-Nicobar basin.

Shearwater wins 4D OBN survey offshore Malaysia Shearwater Geoservices has won a contract from Sabah Shell Petroleum Company Limited for an ocean bottom node (OBN) 4D seismic survey at its operated field off the west coast of Sabah, Malaysia.

The 4D acquisition will provide high-resolution time-lapse seismic data, used to support reservoir understanding and management at the field.

The two-month project will be carried out in early 2026 using the vessel SW Tasman, designed to perform both node

deployment and seismic source operations. After completion the SW Tasman will have had more than two years of back-to-back projects, said Shearwater.

Irene Waage Basili, CEO of Shearwater, said: ‘The integration of seismic source and dual ROV OBN deployment of the vessel SW Tasman since its launch in early 2024 sets it apart in the industry, consistently delivering efficiency and quality gains for our customers across multiple projects.’

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Harbour Energy has agreed to sell its operated interests in the producing Natuna Sea Block A field and the Tuna development project in Indonesia to Prime Group for $215 million.

Chevron has announced capital expenditure of $18 to $19 billion for 2026.

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TotalEnergies invests to become a bigger player in UK oil and gas production

Credit: TotalEnergies.

TotalEnergies has signed an agreement to become the largest shareholder in NEO NEXT, merging assets to become what they claim is the largest independent oil and gas producer in the UK. After the transaction, the renanmed NEO NEXT+ will be jointly owned

by TotalEnergies (47.5%), HitecVision (28.875%) and Repsol UK (23.625%).

The company will encompass a ‘large and diverse asset portfolio’ including notably NEO Energy’s and Repsol UK’s interests in the Elgin/Franklin complex and the Penguins, Mariner, Shearwater and Cul-

zean fields, enriched by TotalEnergies’ UK Upstream assets, notably including its interests in the Elgin/Franklin complex and the Alwyn North, Dunbar and Culzean fields.

With TotalEnergies as its leading shareholder, NEO NEXT+ will have a production over 250,000 barrels of oil equivalent per day in 2026.

‘This transaction demonstrates the long-lasting commitment of TotalEnergies towards the UK oil and gas sector and its energy security. As the new largest shareholder of NEO NEXT+, we are excited to bring along our recognised track record as a leading operator in the UK North Sea, where we have been present for more than 60 years,’ said Patrick Pouyanné, chairman and CEO of TotalEnergies.

Completion of the transaction is expected during the first half of 2026.

Shearwater reports third quarter operating loss of $24 million Shearwater Geoservices has reported a third quarter operating loss of $24 million on revenues of $146.5 million compared to a Q3 operating profit of $14 million on revenues of $179 million in the third quarter of 2024.

The company reported a net loss of $40 million compared to a net loss of $1 million in Q3 2024.

Shearwater said that results were impacted by lower activity, changed project mix and recognition of expected multi-client revenue delayed to the fourth quarter.

The company operated an average of 7.8 active vessels, including two OBN crews with a fleet utilisation of 68%. It had a backlog of $413 million at the end of Q3 including multi-client commitments.

Irene Basili, CEO of Shearwater, said: ‘As expected, marine seismic acquisition activity remained muted in the third quarter as a continued soft contract market impacted utilisation and profitability. We are adjusting our business to the current market environment, to ensure resilience and flexibility to ramp-up activity when demand picks up again.

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‘The current project pipeline secures a streak of more than two years of consecutive contracts for the SW Tasman, despite a slow quarter. We are mobilising for a third season of data acquisition over Brazil’s Pelotas Basin, one of the world’s most promising exploration regions.

‘We remain disciplined even if there are no immediate signs of a near-term demand recovery with current market conditions expected to continue into next year. We are therefore right-sizing the organisation and expanding our cost reduction and efficiency improvement programme.

‘Longer term, the oil and gas industry must rebuild reserves to sustain output and energy security. This will require increased investment in marine seismic acquisition and imaging. We are committed to balancing short-term market volatility while maintaining scalability and flexibility to capture emerging opportunities and deliver long-term value when demand for seismic strengthens again.’

Total operating expenses were $171 million compared to $165.1 million in the same period of 2024.

INDUSTRY NEWS

Viridien and TGS release Gulf of America OBN data Viridien and partner TGS have announced the availability of data from the Laconia Phase III ultra-long offset ocean bottom node (OBN) survey in the Gulf of America.

Top: Legacy StagSeis 15Hz RTM. Bottom: Laconia III early out 5Hz acoustic TLFWI.

ENERGY TRANSITION BRIEFS The Italian energy agency GSE has awarded European Energy contract for difference (CfD) tariffs for five solar projects with a combined capacity of 513 MW. The projects are in Sicily, Apulia and Molise. The awarded projects include large-scale photovoltaic installations with capacities ranging from 20 MW to 225 MW. The CfD awards provide each project with a predictable price structure.

The initial 5Hz Acoustic TLFWI (AFWI) OBN products from the Laconia Phase III survey cover the full 151 Outer Continental Shelf (OCS) block area. Early results demonstrate significant imaging uplift and provide valuable insight to help reduce exploration risk across key Paleogene targets ahead of US lease sale BBG1 (lease sale 262) on 10 December 2025, said the partners.

The project will deliver fast track 5Hz Elastic TLFWI (EFWI) products in Q1 2026 followed by final 12Hz EFWI volumes in January 2027. The enhanced resolution and imaging improvements from the EFWI will further support exploration of the Paleogene, said the partners.

Norway’s Ministry of Energy has allocated two areas for floating offshore wind in Utsira Nord to Equinor and Harald Hårfagre AS. Licence applications must be submitted within two years of the approval of the impact assessment programme.

Petrobras and Shell have launched the Carbon Countdown, the largest project ever undertaken to measure, in a standardised way and on a national scale, the carbon stocks above and below ground in all terrestrial biomes of the country.

The initiative is supported by Esalq/USP as well as universities and research centres Brazil.

TGS wins OBN contract in Europe TGS has won its first OBN contract in Europe for the 2026 season. The company’s node-on-a-rope crew is scheduled to mobilise early May 2026 for the 60-day contract.

Kristian Johansen, CEO of TGS, said: ‘The European market currently has several tenders for OBN projects planned for 2026, and our goal is to build a robust acquisition campaign in the region.

This award comes from a valued repeat customer.’

Meanwhile, TGS has signed an agreement with the Comoros Islands to market and license geophysical data covering its offshore basins in the Indian Ocean.

The 10,000 line km 2D ComorosSPAN survey lies outboard of the deepwa-

ter Rovuma Basin, a ‘major world-class emerging petroleum province’ said TGS. The data will enable the mapping of tectonic elements reflecting the deformation that has occurred along the East African margin as a result of offset along the Davie Fracture Zone throughout the Lower Cretaceous. It allows for the mapping of reservoir sands and modelling work to reduce the risk around source potential.

Finally, TGS has extended its contracts with an international energy company for permanent reservoir monitoring (PRM) and 4D ocean bottom node (OBN) surveys on the Norwegian Continental Shelf. Both contracts have been extended until 2030, with options to extend for a further fiveyear period.

TotalEnergies and Google have signed a 21-year power purchase agreement to supply Google with a total volume of 1 TWh (equivalent to 20 MW) of renewable power from the Citra Energies solar plant in the northern Kedah province.

The solar farm, will support Google’s data centre operations in Malaysia.

The Danish Energy Authority has announced tenders for three areas for the establishment of at least 2.8 GW of offshore wind power. The tenders include state subsidies and ‘greater flexibility for developers to increase the likelihood of qualified bids’.

Technip Energies has won an engineering contract for PTTEP’s Arthit carbon capture and storage (CCS) project in the Gulf of Thailand. It will leverage existing infrastructure at Arthit field while installing additional facilities as required and store up to 1 million tonnes of CO2 a year.

Source: TGS via LinkedIn.

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ExxonMobil launches bold earnings plan to 2030 ExxonMobil has upgraded its earnings estimate by $5 billion in its corporate plan to 2030.

Earnings growth is projected to average 13% per year through 2030, with double-digit cash flow growth. Over the next five years, the company expects to generate roughly $145 billion in surplus cash flow at $65 real Brent, with return on capital employed now reaching over 17% in 2030. Total upstream production will increase to 5.5 million oil equivalent barrels per day by 2030 under the plan.

The company anticipates more than $14 billion in upstream earnings growth at constant prices vs 2024, an increase of $5 billion versus prior guidance.

The increase reflects stronger Permian growth – underpinned by technology advancements and improved capital efficiency – as well as further structural cost reductions, said Exxon Mobil. Unit earnings are projected to reach more than $15 per barrel by 2030, three times 2019 levels.

Darren Woods, ExxonMobil chairman and CEO, said. ‘By 2030, we now expect $25 billion in earnings growth and $35 billion in cash flow growth vs.

2024. We expect to do it with no increase in capital. We’re also beating our 2030 emission-reduction plans across the portfolio. We’ve already achieved our plans for reducing GHG and flaring intensity and expect to reach our planned 2030 methane intensity reductions next year.’

The company’s advantaged assets – Permian, Guyana, and LNG – remain central to revenue growth, said the company. By 2030, production from these assets is expected to reach nearly 3.7 million oil equivalent barrels per day, representing approximately 65% of total volumes.

ExxonMobil is also advancing integrated CCS-enabled low-carbon data centre projects, targeting a final investment decision by late 2026.

New businesses have the potential to reach $13 billion in earnings by 2040 as lower-emissions markets mature, including Proxxima systems and carbon materials. To this end, the company is pursuing approximately $20 billion of lower-emission investments between 2025 and 2030, with approximately 60% focused on reducing emissions for third-party customers.

Viridien reimages 3D data offshore Angola Viridien has announced a new multi-client seismic reimaging programme over Angola’s highly prospective offshore block 22 to support the country’s upcoming licensing round.

The 4300 km2 data set will bring insights into underexplored structures along the Atlantic Hinge zone, following the same trend as the proven Cameia and Golfinho fields.

Viridien will reimage the block 22 dataset with technologies including time-lag FWI, Q-FWI, Q-Kirchhoff and advanced deghosting and demultiple. The data will complement its 2900 km2 of data over nearby block 20/11, giving operators access to a combined regional coverage of more than 7200 km2 of ultramodern broadband PSDM data 30

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to conduct regional pre-salt and postsalt play evaluation in the Kwanza Basin.

Map showing location of Viridien’s new Angola reimaging program (image courtesy of Viridien Earth Data).

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Dechun Lin, head of earth data, Viridien, said: ‘Viridien is delighted to continue its strong relationship with Angola’s national energy agency, ANPG (Agência Nacional de Petróleo, Gás e Biocombustíveis), and longstanding presence in Angola by committing to this new reimaging project which will support their important upcoming licensing round. We have the most modern 3D broadband seismic data available offshore Angola and will continue to generate value from it to provide critical support for industry decision-making and help to increase exploration success.’

Fast-track results are scheduled for delivery in Q1 2026 and final products in Q3/Q4 2026.

27-31 JULY 2026 NEWFOUNDLAND AND LABRADOR I CANADA

CALL FOR ABSTRACTS IS NOW OPEN! SUBMIT BY 22 MARCH 2026

INDUSTRY NEWS

TGS launches 3D survey offshore Brazil TGS has launched the Pelotas Norte Phase I multi-client 3D survey in the Pelotas Basin, offshore southern Brazil.

Phase I will encompass 14,800 km2 across 21 exploration blocks, the majority of which lie in unheld acreage expected to be included in upcoming bid rounds.

A Ramform Titan-class vessel utilising TGS’ GeoStreamer technology was scheduled to mobilise for the survey later in Q4, with project duration running into Q3 2026.

The Pelotas Basin features early basin carbonates and passive margin clastic sequences, including three organic-rich intervals of Albian, Turonian and Paleocene ages.

The basin has attracted ‘significant industry interest’ driven by its geological similarities to the conjugate margin and the proven hydrocarbon systems of West Africa, said TGS. Kristian Johansen, CEO of TGS, said: ‘Exploration activity in the Pelotas Norte Basin is accelerating, with several major oil companies increasing their presence and commitment to the area. The Pelotas Norte Phase I multi-client survey significantly expands our seismic coverage. After the announcement of two large multi-client surveys in the Equatorial Margin earlier in Q3, the addition of Pelotas Norte Phase I brings the number of Ramform Titan-class vessels working offshore Brazil to three for the remainder of this year and well into next.’

Meanwhile, TGS has won a streamer 4D contract from an independent energy company in the Campos basin, offshore

Brazil. A Ramform vessel is scheduled to mobilise for the survey in the second half of 2026, with the contract expected to last approximately 75 days.

Finally, TGS has extended its agreement with the Somali Petroleum Authority granting the company continued rights

to market and license geophysical data covering Somalia’s offshore basins. TGS will continue to offer, exclusively, 46,000-line km of modern 2D seismic data and 50,000 km of aeromagnetic data.

Oil and gas round-up Staatsolie has given Petronas approval to develop a commercial field for the Sloanea-1 gas discovery, located in Block 52 offshore Suriname. Three discoveries have been made since Staatsolie and Petronas signed the production sharing contract for Block 52 in 2013. Petronas Suriname (80%) is the operator of Block 52 and is partnered

by Staatsolie (20%). In late 2020, the Sloanea-1 exploration well was drilled, which encountered a gas-bearing reservoir. In 2024, Petronas advanced the appraisal of the Sloanea reservoir by drilling the Sloanea-2 appraisal well, which confirmed the field’s gas-inplace and recoverable volumes. Final investment decision is planned in the second half of 2026 and first gas is expected to flow in 2030.

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Eni has made a significant gas discovery in the Konta-1 exploration well, drilled in the Muara Bakau PSC, in the Kutei Basin, about 50 km off the coast of East Kalimantan in Indonesia.

Estimates indicate 600 billion cubic feet (Bcf) of gas initially in place with a potential upside beyond 1 trillion cubic feet (TCF). Konta-1 was drilled to a depth of 4575 m in 570 m water depth, encountering gas in four separate sandstone reservoirs of Miocene age with good petrophysical properties that have been subject to an extensive data acquisition campaign.

Vår Energi has confirmed an oil discovery in the Goliat North exploration well, located close to the Vår Energi-operated Goliat field in the Barents Sea. The exploration well

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located 5 km north of the Goliat field encountered hydrocarbons in the Realgrunnen and Kobbe formations.

Estimated gross recoverable resources encountered are up to 5 million barrels of oil equivalent (mmboe). Vår Energi and partner Equinor will drill a total of four wells in the Goliat Ridge and utilise extensive data acquisition combined with the newly acquired 3D seismic data.

Petrobras has discovered ‘excellent quality oil’ in the post-salt layer of the Campos Basin, offshore Brazil, in an exploratory well in the Southwest Tartaruga Verde block. The well, 4-BRSA-1403D-RJS, is located 108 km off the coast in the city of Campos dos Goytacazes-RJ, at a water depth of 734 m.

TECHNICAL ARTICLE

Transforming cities with real-time passive geophysical monitoring Jie Zhang1*

Abstract Geophysics has served as a fundamental science for over 140 years and has driven oil and gas exploration for the past seven decades. Its adaptation to urban monitoring applications, however, was long constrained by high costs, labourintensive field operations, and complex data processing. Recent technological advances, including low-cost nodal sensors, ambient noise as passive sources, real-time data transmission via Wi-Fi and 5G, and artificial intelligence, are now enabling autonomous, real-time geophysical monitoring in several cities of China. Rather than aiming for fully resolved velocity models, urban geophysics can deliver greater practical value by tracking temporal variations in key geophysical attributes. This shift in detection strategy lowers costs, reduces reliance on human intervention, and supports scalable, continuous monitoring of critical infrastructure such as roads, bridges, dams, construction zones, slopes, and buildings. By embedding geophysics intelligence into cities, geophysics evolves from a project-based, resource-driven discipline into a living, responsive nervous system for the urban environment.

Introduction Geophysics, particularly seismology, originated with the study of earthquakes, seismic wave propagation, and tectonic processes, significantly advancing our understanding of Earth’s internal structure. Over the past century, it has also become essential for natural resource exploration. Controlled-source seismic surveying has remained the primary tool for oil and gas exploration since the 1950s (Yilmaz, 2001), contributing greatly to the global economy.

In recent decades, seismic techniques have been adapted for urban applications, including shallow subsurface imaging to support engineering, hazard assessment, and infrastructure planning (Nakamura, 1989; Yilmaz, 2015). However, large-scale adoption of urban geophysics has been hindered by the high cost and labour demands of field deployment and manual data processing.

Recent developments in passive seismic sensing have opened new opportunities for urban monitoring without the need for controlled sources. City-based seismic arrays have been deployed to detect a wide range of natural and anthropogenic signals.

For example, the Covid-19 lockdowns led to a marked global decrease in anthropogenic seismic noise (Lecocq et al., 2020).

Seismometers have recorded ground vibrations from concerts, sporting events, fireworks, and even crowd movements (Díaz et al., 2017). Seismic monitoring has also captured the landfall and weakening of hurricanes, such as Hurricane Isaac in 2012 (Tanimoto and Lamontagne, 2014). These studies show that changes in seismic signal characteristics can provide real-time insights into urban activity with minimal data acquisition and processing effort.

1

University of Science and Technology of China

*

Corresponding author, E-mail: jzhang25@ustc.edu.cn

A major breakthrough enabling scalable, high-resolution monitoring in complex environments is the rise of ambient noise seismology (Nakata et al., 2019; Wang and Yao, 2020). Ambient seismic noise, generated by natural sources (e.g., ocean waves, storms) and human activity (e.g., traffic, construction), can be harnessed to detect subtle subsurface changes. Cross-correlating continuous noise recordings between sensor pairs allows approximation of the Green’s function of the medium. Foundational work in the early 2000s (Campillo and Paul, 2003; Shapiro and Campillo, 2004) demonstrated that both surface and coda waves can be reliably retrieved from ambient noise, laying the groundwork for passive seismic imaging. Since then, dense urban arrays have successfully mapped shallow subsurface structures using these techniques (e.g., Lin et al., 2013; Liu et al., 2014), underscoring their value for infrastructure and engineering applications.

The field of seismic exploration has developed a wealth of algorithms and methods for reconstructing true earth models. However, most of these approaches demand substantial computational resources and runtime. As a practical first step, real-time geophysics should prioritise monitoring temporal changes rather than resolving full earth models. This strategy simplifies AI implementation while delivering significant value for infrastructure monitoring.

The convergence of low-cost seismic nodes, real-time wireless data transmission (via Wi-Fi or 5G), and AI-driven data processing and imaging is now ushering in a new era of autonomous, real-time urban geophysical monitoring. Dense sensor networks can be deployed across cities, continuously capturing seismic signals. Machine learning algorithms enable automated extraction

DOI: 10.3997/1365-2397.fb2026001

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and interpretation of meaningful features, reducing the need for manual analysis and enabling timely decision-making.

Several cities in China have begun implementing such realtime permanent seismic monitoring systems using nodal sensors or distributed acoustic sensing (DAS). For example, Hefei is installing 50,770 seismic nodal sensors as part of the CitySeis project, which is designed to support a wide range of urban safety and infrastructure monitoring tasks. However, complimentary DAS systems have so far been deployed mostly for small-scale applications. Their large-scale implementation remains limited, primarily due to challenges associated with installation in urban complex environments and the reluctance of many cable owners to allow the use of existing underground fibres. In this study, we present examples using nodal sensors and automated processing workflows to achieve continuous, man-free seismic monitoring in Shenzhen and Hefei, China. By extracting surface waves, coda waves, or reflections from ambient noise recordings, we demonstrate applications in infrastructure health monitoring — covering roads, dams, bridges, slopes, and buildings. These examples illustrate how modern seismological techniques can deliver actionable insights for urban safety and planning, offering a scalable and transformative new role for geophysics in the 21st century.

data are reliable. In engineering-scale applications, however, ambient noise sources may include both repeatable signals (e.g., moving traffic, ongoing construction) and non-repeatable ones (e.g., human activity, sporadic operations). These diverse source characteristics require carefully designed monitoring geometry, along with robust data processing and interpretation workflows to distinguish persistent structural anomalies from transient or incidental events. Several studies present theories and methodology to select data from reliable noise sources for urban structural monitoring (Wapenaar et al., 2010; Mi et al., 2025).

Urban subsurface environments are inherently complex, often containing sewers, buried cable tunnels, reinforced concrete structures, and weathered geological layers, which make absolute structural characterisation difficult. However, by deploying dense arrays of seismic receivers, it is possible to detect temporal variations in seismic responses with high precision. Even in the absence of a fully resolved velocity model, changes in the recorded wavefield over time can reveal meaningful structural evolution beneath the surface. We will present case studies demonstrating that ambient noise data can be used to continuously monitor seismic velocity variations, power spectral density, and cepstral features in real time, providing valuable insights into infrastructure health and stability.

Methods

Power spectral density

Seismic ambient noise

In urban settings, we should apply multiple seismic properties to characterise any observed change, because of the far more complicated noise sources than earthquake problems. Power spectral density (PSD) is another efficient approach that can be applied to process ambient noise data and quantify how the energy of a seismic signal is distributed across different frequencies. By computing PSD, we can differentiate between natural and anthropogenic noise, and between repeated and non-repeated noise. PSD offers a way to track changes in noise level, detect events, monitor resonance or natural frequencies of infrastructures (McNamara and Buland, 2004). It is also utilised in H/V spectral ratio calculation (Nakamura, 1989), extracting subsurface velocity structures (Lin et al., 2008), and estimating attenuation factor (Toksöz et al., 1979). With a seismic array, we can use PSD to enhance signals from a particular direction (beamforming) (Rost and Thomas, 2002). This helps us to detect weaker events and locate their source.

Across these applications, the power spectral density fundamentally helps to separate signal from noise and elucidate the frequency-dependent properties of seismic waves — whether for monitoring background levels, understanding site response, detecting earthquakes, or informing infrastructure design. In this study, we show examples of utilising PSD to monitor landslides and bridges.

The rise of seismic ambient noise studies has marked a significant turning point for urban seismology, creating new opportunities through continuous recordings without the need for active sources. Ambient noise data can be leveraged for a wide range of urban applications, including: monitoring S-wave velocity variations (dv/v) by correlating the current Green’s functions of surface or coda waves with a fixed reference Green’s function for the same receiver pair, identifying reflection multiples through Cepstrum analysis, tracking frequency-dependent changes via power spectral density (PSD), estimating site resonance using the horizontal-to-vertical spectral ratio (HVSR) method, and imaging subsurface structures with ambient noise tomography (ANT).

Over the past two decades, earthquake seismologists have extensively utilised ambient noise data to monitor temporal changes in the crust. This effort has led to the development of four primary methods for extracting Green’s functions from coda waves: moving-window cross-spectral analysis (Brenguier et al., 2008), the stretching method (Lobkis and Weaver, 2001), dynamic time warping (Mikesell et al., 2015), and wavelet cross-spectrum analysis (Mao et al., 2020).

However, these methods primarily focus on coda waves — later arrivals in the Green’s function that result from scattering and do not follow fixed raypaths. While coda waves are well suited for monitoring structural changes, they are less effective for resolving the depth of variations. More recent developments have extended ambient noise approaches to include ballistic phases such as body and surface waves (Brenguier et al., 2020; Takano et al., 2020). These advances leverage dense receiver arrays with small spacing to capture shorter wavelengths, enabling S-wave velocity structural imaging suitable for urban environments.

Seismic ambient noise methods generally require repeatable noise sources over time so that structural changes resolved from 34

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Seismic cepstrum

Cepstrum analysis is a signal processing technique that detects and characterises repeating or echo-like features by examining periodicity in the logarithmic frequency domain. Mathematically, the cepstrum of a signal x(t) is obtained by taking the Fourier transform X(f), computing the logarithm of |X(f)|, and then applying the inverse Fourier transform to log|X(f)|. In exploration seismology, this method is often applied to separate the source signature (wavelet) from multiple reflections, reverberations,

TECHNICAL ARTICLE

or layer-thickness effects. It is also used to identify and remove multiple reflections caused by subsurface layers (Bao et al., 2022).

In engineering applications, we intentionally retain multiples to observe how they change over time, which can help us to reveal shallow collapses, landslides, or infrastructure alterations (Butler, 1988). By continuously calculating the cepstrum from ambient noise, shifts in these multiples can serve as indicators of variations in layer shape or thickness — making it a valuable tool for real-time subsurface monitoring.

For engineering problems, the multiples identified in the cepstrum serve as direct proxies for shallow subsurface conditions. Changes in their frequency or amplitude correspond to modifications in layer geometry or material properties. When integrated with deep learning techniques, cepstrum analysis can be fully automated, enabling efficient, continuous monitoring in urban and infrastructure settings.

Real-time urban applications Using seismic ambient noise as a passive source enables continuous, real-time monitoring in urban settings — a practice already adopted in several Chinese cities. The primary objective is to detect hazardous structural changes in the subsurface and infrastructures — problems that cameras and other methods may not easily catch — and provide timely warnings. Figure 1 illustrates the system’s architecture, which includes wireless seismic nodes (4.5 Hz natural frequency), data transmission over 4G/5G, remote server analysis, and end-user interfaces. The seismic sensors not only cover the subsurface but also the surface activities. When seismic analysis flags an anomaly at the surface, nearby cameras or drones are automatically prompted to collect further information.

In the following, we present several cases demonstrating how this system can address various issues, including subway construction monitoring, road collapse, dam seepage, landslides, bridge integrity, and building health.

Subway construction During urban subway construction, tunnel boring machines (TBMs) advance underground while using pressurised water to stabilise the surrounding soil and support overlying structures — often operating at depths exceeding 25 m. This process carries risks such as soil collapse, water leakage, and even structural

tilting in nearby buildings. Therefore, real-time monitoring of TBM operations is critical to ensure construction safety and minimise potential damage.

Figure 2 illustrates a monitoring scenario in which seismic sensors are deployed at 10-m intervals along the surface above a subway construction route. As the tunnel boring machine (TBM) advances, Green’s functions — referenced to a fixed baseline — are updated every 10 minutes to track subsurface changes ahead of the TBM. For each narrow frequency band of the full Green’s functions, we calculate cross-correlation between the current Green’s functions and the baseline. The resulting maximum coefficient is defined as the Similarity between now and then for this frequency. This approach follows the same principle as measuring dv/v variations but focuses on tracking similarity changes. By plotting the similarity coefficients across all frequencies and receiver pairs, and converting frequency to depth, the results shown in Figure 2 are obtained. In the calculation of Green’s function, each data window spans one hour and is refreshed every 10 minutes, resulting in a 50-minute overlap with the previous window.

Figure 2 shows the relative similarity changes in the subsurface referenced to an early construction day. A progressive reduction in similarity is observed ahead of the TBM, indicating the influence of pressurised water from the TBM. Notably, a potential water breakout to the surface is detected before it occurs. In response, cement was injected into the affected zone to seal the area and prevent further complications, allowing construction to continue safely.

Road collapse Roads can collapse due to subsurface soil migration triggered by rainfall or the presence of pre-existing karst caves, posing a significant risk to public safety and traffic. Early detection and monitoring for signs of collapse are thus critical. Once a collapse occurs, real-time monitoring of subsurface movements is also vital to guide repair efforts.

On 12 October 2024, a road collapse in Shenzhen received extensive coverage in the Chinese media. Fortunately, no casualties were reported. Immediately following the incident, workers began refilling the collapse zone with cement but noticed a significant amount of cement was disappearing without any clear explanation. In response, a seismic array of node sensors, spaced at 10-m intervals, was swiftly deployed along the road.

Figure 1 A permanent system for real-time urban seismology. GPS-synchronised seismometers transmit data to centralised servers within milliseconds, where automated processing is performed. Results are displayed on monitoring screens, and warnings are issued when necessary.

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Figure 3 shows the temporal variations of shear-wave velocity over a three-day period. On the first day, continuous soil collapses were observed at three locations (indicated by red arrows), accompanied by repeated cement injections between two receivers.

Ambient noise was generated by randomly passing vehicles and was used for monitoring the subsurface changes from surface down to several hundred metres. On the second day, injection activities continued, but the seismic response began to stabilise. By the third day, velocity changes had significantly reduced, indicating that the cement had effectively sealed the affected zone.

Dam seepage During the rainy season, elevated precipitation increases the reservoir’s water level, which in turn places additional pressure on the dam structure. This heightened pressure can intensify seepage or leakage risks, posing a significant hazard to dam integrity and surrounding communities. Consequently, continuous monitoring and preventative measures are especially critical during this period to detect potential leaks early and mitigate any resulting damage.

The 2024 Dongting Lake levee breach occurred on the afternoon of 5 July 2024, in Tuanzhou Dike, Yueyang, China. The breach was caused by prolonged heavy rainfall along the Dongting Lake shoreline. The breach raised widespread alarm across southern China. In response, more than 10,000 personnel were mobilised to conduct round-the-clock patrols and monitoring of the Gongjiaxu Levee in Lujiang County, Hefei. Simultaneously,

real-time D.C. resistivity and seismic monitoring systems were deployed along the dam.

At 5:26 am on 11 July 2024, the system issued a resistivity warning: measurements at five adjacent locations approached zero, accompanied by a significant reduction in shear-wave velocity after 6:00 am Ambient noise data are processed within the frequency range of 5 — 100 Hz, and the frequency-dependent dv/v response is converted to depth following the method of Yates et al (2024).

Seismic reflections, as revealed by cepstrum analysis from ambient noise, indicated structural changes at the same site (see Figure 4).

The city authorities were immediately alerted, and by 8:00 am, emergency repair work was initiated to ensure the dam‘s safety.

Following the rainy season, inspections confirmed structural defects in the previously flagged area, which were subsequently repaired and reinforced to restore long-term dam stability.

Landslide The use of seismometers for landslide monitoring has been extensively investigated, with a comprehensive review provided by Whiteley et al. (2019). In general, natural frequency is a key indicator of rock slope stability (Bottelin and Baillet, 2024), while reduction in S-wave velocity (dv/v) relative to a normal day is widely recognised as critical indicators of clay slope stability (Mainsant et al., 2012). A reduction in S-wave velocity below zero is an indicator of increased water saturation in the soil or weathered layers. The greater the water

Figure 2 Monitoring the TBM operation in Shenzhen, China with a surface-deployed seismic array using the ambient noise method. (a) Schematic illustration of TBM activity; (b) Real-time image of subsurface changes ahead of TBM by calculating the similarity between the current Green’s functions and reference Green’s functions. Blue areas (lower similarity) indicate zones of fluid penetration and major structural changes relative to an early day.

Figure 3 Monitoring cementing efforts after a road collapse in Shenzhen, China. A seismic survey line (red triangles) was deployed along the road with 10-m receiver spacing. Blue areas show shear-wave velocity changes over three days of operation. Red arrows indicate ongoing collapse, while the blue arrow marks the cement injection site as shown in the photo.

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Figure 4 Monitoring a dam in Hefei, China during a major storm. (a) Seismic array and a D.C. resistivity system installed at co-located sites (stars), an electrical outage occurred between the water and embankment areas (red stars). (b) It was followed by the appearance of reflection multiples extracted from ambient noise using the cepstrum method. (c) Concurrently, a significant reduction in shear-wave velocity (dv/v) was observed in the same area, suggesting possible leakage within the dam structure.

Figure 5 Monitoring a rock slope and an overpass bridge during and after 15 days of heavy rainfall in Anhui Province, China. Two seismic sensors were deployed at each site (red triangles in the photos). (a) Local temperature over a continuous 29-day period; (b) Relative humidity (%) over the same period; (c) Rock slope: continuous S-wave velocity variation (dv/v); (d) Rock slope: continuous natural frequency variation; (e) Bridge: continuous S-wave velocity variation (dv/v); (f) Bridge: continuous natural frequency variation. Note the strong sensitivity of the rock slope to daily temperature fluctuations, in contrast to the bridge, which remains stable during low-temperature periods and exhibits only small variations under normal temperature conditions.

accumulation, the higher the likelihood of a potential landslide. Conversely, an increase in S-wave velocity often signifies the reverse process, reflecting the loss or drainage of water from the subsurface materials. Natural frequency reflects how a system tends to vibrate based on its intrinsic properties. Complex systems such as slopes, buildings, or bridges typically exhibit multiple natural frequencies.

Figure 5 presents 29 days of monitoring data from a rock slope site in Anhui Province, during which heavy rainfall

persisted for the first 15 days. Two seismometers were installed — one at the top of the slope and the other at the bottom. This configuration is ideal for leveraging passing vehicles as ambient noise sources at the bottom receiver location. The top panel shows temperature, the second panel depicts humidity, the third illustrates shear-wave velocity variations (dv/v) between the two receivers, and the fourth displays the slope’s natural frequency response from PSD calculation.

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Figure 6 Monitoring a building with structural defects in Shenzhen, China. One seismic sensor was installed at the top of the building and another at the base. (a) The top sensor exhibits irregular variations in dv/v; (b) Cross-correlation between the two sensors shows only minor changes (<2%); (c) The top sensor records irregular fluctuations in a specific frequency component, likely associated with fractures within the building structure.

On 29 June and 3 July 2024, rainfall briefly ceased, resulting in a rise in temperature and a drop in humidity. Throughout the first 15 days, the shear-wave velocity variation (dv/v) of the rock slope remained largely stable but showed a modest decrease (6-7%) on those two days when weather conditions shifted. A similar slight decline was observed in the slope’s natural frequency during the same period. These changes triggered an initial alert, though subsequent analysis ruled out any immediate risk. After the rainy season ended, both dv/v and natural frequency began to fluctuate daily in a recurring, stable pattern. These observations underscore the high sensitivity of seismic measurements and their ability to capture multiple environmental factors influencing the rock slope.

Bridge During the same period, two seismometers installed on an overpass bridge in the same province recorded variations in dv/v and natural frequency using passive noise from traffic signals as shown in Figure 5. While many conventional devices are already used to monitor bridge conditions, the seismic method offers a unique advantage: it captures elastic waves propagating through the bridge and measures the vibrations of the entire structure.

This approach enables the detection of both long-wavelength structural variations and small-scale defects that alter the physical parameters extracted from ambient noise data. The seismic sensors record not only the direct arrivals generated by passing vehicles but also the Lamb waves — specifically, the flexural modes that propagate along the entire bridge structure. These flexural waves can reverberate between the bridge ends after excitation, generating scattered coda waves within the structure.

The scattered coda waves are then analysed to monitor subtle temporal changes in the bridge’s integrity and material properties.

The typical frequency range of vibrations generated by passing vehicles on bridges extends from approximately 5 to 250 Hz, with dominant energy concentrated between 5 and 100 Hz, producing strong ambient noise. During the heavy rain, dv/v and natural frequency remained relatively stable, as the combination of rainfall and low temperatures appeared to keep the bridge rigid. Once the weather normalised, these parameters began to vary within 2% and displayed a recurring daily pattern. If the variations dip below -10% or cease to return to their regular cycle, it may indicate emerging structural defects (Salvermoser et al., 2015).

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Building When seismic waves from ambient noise repeatedly pass through buildings, they carry valuable information about the structural health and integrity of the buildings (Mordret et al., 2017).

Changes in building conditions can be inferred from variations in natural frequency and S-wave velocity.

Building risks may arise from multiple factors, including structural defects, extreme weather, and nearby construction activities.

In one urgent case, subway construction caused visible ground anomalies, prompting us to deploy seismometers to monitor more than 20 buildings in the affected area. For each building, one sensor was installed at the top and another at the base on the ground.

The system continuously tracked natural frequency and S-wave velocity variations between the two sensors and the subsurface.

Most buildings exhibited stable responses. However, one building displayed irregular natural frequency shifts over time, while all other frequencies remained stable (see Figure 6c). In addition, its S-wave velocity variations were inconsistent and non-repeatable over time. Notably, this was the only building with visible cracks observable from the outside. These findings suggest that the observed anomalies in ambient noise data were caused by underlying structural defects.

Conclusions This study demonstrates how recent advancements in passive seismic monitoring, low-cost nodal sensors, wireless data transmission, and AI-driven processing are transforming geophysics into a real-time, autonomous system for urban infrastructure monitoring in China. The system has been deployed and operated across Anhui, Guangdong, Zhejiang, and Hebei provinces. By leveraging ambient noise from both natural and anthropogenic sources — such as traffic, rainfall, and construction — our approach extracts key seismic attributes, including shear-wave velocity variations, natural frequencies, power spectral density, and cepstral features. These parameters provide continuous, non-invasive insights into the health and stability of critical infrastructure.

We present several case studies from these large-scale engineering efforts, covering subway construction monitoring, road collapse assessment, dam seepage detection, landslide surveillance, bridge integrity evaluation, and building diagnostics.

The results show that passive seismic methods can deliver early

TECHNICAL ARTICLE

warnings of hazards and support timely interventions. Embedding seismic intelligence within cities not only strengthens resilience against natural and anthropogenic threats but also lowers monitoring costs and expands the role of geophysics in the emerging landscape of smart and sustainable urban development.

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Acknowledgements I sincerely appreciate the dedication of the entire CitySeis project team, particularly, Drs. Yi Luo, Tong Fei, and Pengxiang Zhou, whose work has helped shape a new landscape in geophysics.

I am also deeply grateful for the constant support and encouragement from Prof. Mark Zoback and Dr. Öz Yilmaz. We thank Editor Clement Kostov and the reviewers for their helpful suggestions.

America, 94(4), 1517-1527.

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Mordret, A., Sun, H., Prieto, G.A., Toksöz, M.N. and Büyüköztürk, O. [2017]. Continuous monitoring of high-rise buildings using seismic

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TECHNICAL ARTICLE

Automated realistic labelled DAS data synthesis using CycleGANs and their application to phase arrival picking William Tegtow1*, Nepomuk Boitz1, Serge A. Shapiro1 and Andres Chavarria2.

Abstract Distributed Acoustic Sensing (DAS) provides dense spatial, robust and cost-effective seismic monitoring. However, automated analysis of DAS recordings remains challenging due to their variable and inherently two-dimensional structure, densely sampled in space and time. While explicit methods often struggle with this complexity, machine learning schemes are well-suited to handle such data but are limited by the need for large, labelled datasets, which are rarely available for DAS. Furthermore, unique properties of different DAS datasets make it necessary to have a representative labelled dataset for each new application, which limits the utility of pre-trained models. To overcome these limitations, we propose a fully automated, generalisable framework that synthesizes realistic, labelled DAS datasets using cycle-consistent adversarial networks. We demonstrate the benefits of such datasets by training a seismic phase arrival picker for microseismic DAS images by comparing two models: one trained on purely synthetic data and one trained on domain-translated data, using our proposed method. The latter model provides more accurate predictions by effectively reducing model generalisation issues. The end-to-end pipeline is fully automatable and provides a scalable machine learning tool for DAS-based seismic analysis.

Introduction Distributed Acoustic Sensing (DAS) is increasingly used for seismic monitoring on both reservoir and regional scales (Zhan, 2019; Rashid et al., 2025). During DAS acquisitions, an interrogator periodically sends laser pulses through a fibre-optic cable and detects backscattered light that originates from heterogeneities in the cable. Tracking the phase shift from the backscattered light over time allows us to convert and locate these signals into dynamic strain measurements along the cable (Hartog, 2017).

Depending on the application, DAS can be used to measure strains over a wide frequency range with distances ranging from a few metres to several tens of kilometres. (Karrenbach et al., 2019; Vásquez et al., 2022; Ning et al., 2022). Furthermore, it can be used in environments where installing conventional sensors is challenging, such as in boreholes, offshore or in infrastructures (Zulic et al., 2022; Quinn et al., 2022; Baba et al., 2023). However, automated analysis of the recorded seismic data, such as event detection, phase arrival picking, localisation, etc., remains a challenging task for several reasons. Unlike conventional 3-component point sensor data, wavefields recorded by DAS have a two-dimensional structure. Traditional signal processing methods developed for single trace geophone data (e.g., Withers et al., 1998) do not exploit the dense channel spacing, leading to unsatisfactory results due to the lower signal-to-noise ratio (SNR)

1

Freie Universität Berlin | 2 VIAVI Solutions Inc.

*

Corresponding author, E-mail: w.tegtow@geophysik.fu-berlin.de

of DAS data. Furthermore, variable source-fibre geometries, optical settings, spatial and temporal sampling frequencies, and any other acquisition system-related distortions result in diverse noise characteristics and moveouts of seismic events. As a result, proposed explicit methods are often case-study specific, but their application to other datasets is rarely possible (e.g., Glubokovskikh et al., 2023; Tegtow et al., 2023; Porras et al., 2024). Therefore, robust and generalisable schemes are required that can fully handle the complex nature of DAS data.

Supervised machine learning offers an alternative approach for such schemes. With this method, the rules that describe the target features do not need to be explicitly formulated. Instead, a deep learning model learns to identify them independently through training with paired inputs (data) and outputs (labels).

Once trained, the model can be used on new data to identify the label-specific targets. Therefore, the most important prerequisite for this approach is the availability of suitable paired datasets.

Although large amounts of seismic data are typically available, generating the corresponding labels is challenging. This problem is particularly pronounced with DAS data because their variability limit the use of pre-trained models to cases similar to the conditions of the used training data. Therefore, models must be separately trained or at least fine-tuned for each application, which requires a representative set of labelled data for each new

DOI: 10.3997/1365-2397.fb2026002

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use case. To obtain labels for geophone data, Zhu and Beroza (2019) hand-picked several thousand P- and S-wave arrivals.

However, for DAS data such detailed manual annotation across hundreds or thousands of channels per event is practically unfeasible. Several attempts have been made to work around this problem. Huot et al. (2022) labelled coarse event windows in DAS data to train an event detection model. While suitable for identifying the presence of events, this approach does not allow more detailed analyses, which require sample-wise label annotations. Boitz and Shapiro (2024) used co-located geophones and fibres to label phase arrivals. However, since geophones were sparsely distributed in the borehole, labelling was limited to adjacent DAS channels. Zhu et al. (2023) developed an automated labelling method that performs single-trace phase picking followed by phase association. While this reduces the need for manual input, it does not take advantage of the 2D structure of DAS data and relies on associators to correctly remove picking errors. Furthermore, models intended for real-time applications must be fully trained and deployed before data acquisition, as post-acquisition processing is not possible in such scenarios.

This problem can be addressed using synthetic DAS recordings, which can be created in advance and used to train the models. To increase realism, the synthetic wavefield recordings can be embedded into real recorded ambient noise (e.g., Binder and Chakraborty, 2019; Stork et al., 2020). Tegtow et al. (2024) trained a model purely on synthetics to perform a sample-wise binary classification for event detection. While synthetic data can be used for relatively simple tasks like binary classifications, its usefulness gradually vanishes with increasing complexity of the task the model must perform (e.g., phase arrival picking). The underlying problem is that synthetics can only be considered as an approximation of the real field data. If the statistical distribution of the training data differs significantly from that of the target data, the model’s ability to generalise and recognise relevant patterns in the field data will be negatively affected. Recently, Choi et al. (2025) used a generative model to create more diverse data to train a fault detection model.

In this study, we present a fully automated and generic machine learning framework for the synthesis of realistic, labelled DAS datasets using cycle-consistent adversarial networks (CycleGANs). The CycleGAN generator is designed to preserve the semantic content of the input images while applying to them the style of the target domain. In this way, domain-translated synthetic events retain their structure and positions, while field-data-specific features are automatically applied to them.

Once trained, the generator can be used to create any amounts of realistic data from a pool of synthetic events which allows us to directly transfer corresponding pre-computed labels.

The content of this work is organised as follows: Section 2 introduces the CycleGAN methodology. Section 3 presents the application of CycleGANs to DAS data, including an introduction to the case study, data preparation, and CycleGAN training details. Section 4 presents a showcase application in which CycleGAN domain translated data are used to train a seismic phase arrival picking model. This includes a novel picking model architecture designed to meet the specific requirements of this task. We compare two picking models: one trained exclusively on 42

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synthetic data and the other on CycleGAN-translated data. Qualitative and quantitative comparison of both models for unseen field data demonstrates the benefits of the proposed method.

Overview of CycleGANs Considering DAS space-time recordings as single-channel images, computer vision techniques can be adapted for a pixel-wise analysis.

Many computer vision tasks can be seen as image-to-image translation problems, such as super-resolution (Dong et al., 2016; Yuan et al., 2018), semantic segmentation (Minaee et al., 2021), denoising (Zhang et al., 2017; Lehtinen et al., 2018), inpainting (Pathak et al., 2016; He et al., 2022) or any other pixel-wise translating model.

Training such models typically requires paired datasets, where each input image has a corresponding labelled output from the target domain. The pixel-wise constraints enforce models to build a proper mapping between the two domains. However, acquiring pixel-by-pixel paired data is often difficult or impossible to obtain.

In contrast, unpaired image-to-image translation attempts to establish such a mapping between two domains without pair information.

Given two image collections with pixel value distributions X and Y, the goal is to find a mapping that transfers the style between the domains while preserving the semantic content. In this context, ‘semantic content’ refers to the underlying structures or meaning of an image, such as the objects it contains, their shapes, and spatial arrangements. The term ‘style’ refers to the visual appearance of the semantic features, including their colours, textures, or patterns.

Because there are infinitely many possible mappings, the problem is inherently ill-posed and requires additional constraints to ensure meaningful translations. Various methods have been developed to guide the translation process, including diffusion-based models (Ho et al., 2020; Rombach et al., 2022), path regularisation (Xie et al., 2023), and cycle-consistency (Zhu et al., 2017).

A CycleGAN model uses a pair of generative adversarial networks (GANs) along with the cycle consistency to establish such a transformation. A GAN consists of two networks, a generator and a discriminator (Goodfellow et al., 2014). The generator tries to convert an image from the input to the target domain, while the discriminator checks whether a given image is real or a fake created by the generator. The idea is that these two networks compete in an adversarial process. The generator continuously improves its ability to fool the discriminator, and the discriminator becomes better at distinguishing real from generated images. This way, the generator becomes increasingly better at synthesizing realistic images.

A CycleGAN extends this concept by using a coupled pair of GANs to learn translations between two domains in both directions (Zhu et al., 2017). It uses a generator to domain , and a that translates an image from domain from to . A discriminator is used generator and generated fakes to distinguish between images from , and discriminator from and , where the subscript denotes fake. Adversarial losses (gan-loss) are applied to both discriminators:

(1)

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2023). Unlike the original CycleGAN, we omit the identity loss component. Figure 1 illustrates the CycleGAN scheme.

Application of CycleGANs to DAS data Case study

Figure 1 CycleGAN scheme. Two generators G and F translate images between domains X and Y, while discriminators Dx Dy distinguish real from generated images.

Cycle-consistency losses ensure that translating an image to the other domain and back reconstructs the original.

and both generators:

(2)

where denotes the expected value of over the distribution , denotes the adversarial loss, which can be any classification loss, and labels 0 and 1 stand for fake and real images, respectively. Furthermore, cycle-consistency losses are applied to the generators:

(3) where can be any regression loss. The total loss for the generators is then given by:

(4)

where can be used as a hyperparameter to weight the cycle-consistency constraint. The cycle consistency ensures that an image is reconstructed after a translation cycle to another domain and back. This form of consistency has proven to be effective in preserving the semantic content of the image, while adapting the style of the target domain (Zhu et al., 2017; Choi et al., 2018; Kim et al., 2019; Park et al., 2020; Torbunov et al.,

In this study, we focus on microseismic DAS data that were acquired during three hydraulic fracturing stages at the Hydraulic Fracturing Test Site II (HFTS2) in a horizontally oriented borehole (Ciezobka, 2021; Chavarria et al., 2022). Figures 2a and 2b show the borehole trajectories of the injection well (B4H) and the observation well (B3H), as well as the microseismic clouds of events triggered during stage 20, 21 and 23, respectively. The microseismic event locations are taken from a geophone-based event catalogue (Grechka et al., 2021). The DAS data were acquired while dual streaming low-frequency strain signals (1 Hz) and high-frequency microseismic signals (2 kHz) simultaneously with the same interrogator. The optical settings were optimised for strain monitoring (Chavarria et al., 2022). However, to increase the signal-to-noise ratio in microseismic-focused studies, the optical resolution can be better adapted to the wavelengths of seismic events, which are longer than those of strain signals from fractures.

From Tegtow et al. (2024) we have access to a DAS-based event catalogue. From this catalogue, we randomly selected 750 events and compiled them into an image collection representing the domain of real events (Figure 3). Each image corresponds to a space-time segment extracted from the continuous recordings, with a resolution of 320 x 320 pixels, corresponding to fibre-optic channels spanning 1280 m along the horizontal borehole and time samples covering a 160-millisecond window. The chosen spatial and temporal resolution ensures that seismic events are fully captured within the images to provide the model with complete semantic information. Furthermore, the use of uniformly sized images increases possible geometric augmentations for subsequent training to improve data variability and model performance. Each image was normalised to the range [−1, 1] to standardise input values for the networks.

The second dataset consists of forward modelled synthetic DAS recordings. The main advantage of using synthetic recordings is that they allow us to automatically calculate corresponding labels, such as arrival times or any other target attribute of interest. To create synthetic DAS recordings, we used the open-source software ElasticFDSG (Tegtow, 2025) to solve the elastic wave equation.

During each simulation, we extracted the strain response along predefined profiles that served as virtual fibres. Note that we worked with the raw strain values directly and no attempt was made to

Figure 2 Source-receiver geometry. a) Map-view. b) Side-view. Microseismic event locations originate from a geophone catalogue (stages grouped by colour).

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make the data more ‘DAS-like’ by accounting for the gauge-length averaging, strain-rate conversions, etc. We performed a total of 50 simulations, each with 10 virtual fibres, different source locations and mechanisms to increase the variability in the strain responses.

The resulting 500 synthetic events served as templates for a processing pipeline, which randomly selected one or two template events, applied random perturbations (shifts, damping), and then embedded them into randomly selected ambient noise samples at the same resolution (320 × 320) as the field data. This way, every output image is unique to some degree. Accordingly, processed synthetic samples represent the domain of synthetic events. Figure 3 shows examples of the resulting unpaired image dataset. Both components of the datasets share common semantic features such as P-waves, S-waves, codas and reflections with similar moveouts and with the same background noise. However, differences exist in terms of signal-to-noise ratios, wavelet types, and overall sharpness of the signals (Figure 3). All simulations were performed exclusively with Ricker wavelets, while the field data exhibit more complex wavelet types. Furthermore, some field data waveforms appear blurred, likely due to the gauge-length averaging or due to artifacts of the pre-processing. Since the underlying physics are more complex than typically assumed in the modelling process, synthetic data is unlikely to accurately replicate the properties of field data. Attempts to account for effects that give field data its real-world properties would drastically increase the complexity of the modelling task.

Therefore, a CycleGAN generator capable of transforming synthetic events into more realistic ones would automatically incorporate real-world details and eliminates the need for more sophisticated modelling. This way, the generator can synthesize any number of realistic samples on demand and labels can be transferred directly if the semantics of seismic events are preserved. However, the generator is optimised for a specific dataset. When used for data with different properties (e.g., gauge length, strain-rate effects, or source–fibre geometries), translation may not provide any benefit for models trained on this data. Therefore, a separate generator must be trained for each application.

Training details

For the generator model, we use the Unet-VisionTransformer-CycleGAN-v2 (UVCGANv2) generator described in detail

in Torbunov et al., 2023. This architecture integrates a fully convolutional Unet (Ronneberger et al., 2015) with a pixel-wise Vision Transformer (ViT) (Dosovitskiy et al., 2020) as the bottleneck with a style-token modulated convolutional decoder branch.

We chose this architecture because it performs well for modern, high-resolution CycleGAN applications, combining the benefits of convolutional local feature extraction and transformer-based global understanding. For the discriminator networks, we use the PatchGAN architecture (Isola et al., 2017), which classifies not entire images, but rather image patches of size NxN (e.g., 30 x 30) as real or fake. This approach helps the discriminator to learn both high- and low-frequency features more effectively.

For the adversarial loss we use the L2 norm for the generators and discriminators (LSGAN) (Mao et al., 2017). However, unregulated training can be unstable and can cause problems like vanishing or exploding gradients, or mode collapse (Mescheder et al., 2018) – a phenomenon in which the generator produces only a limited variety of outputs to fool the discriminator while failing to capture the full diversity of the target distribution. To counteract these issues, several regularisation strategies have been proposed, such as Wasserstein GANs (WGAN) (Arjovsky et al., 2017) and gradient penalties (GP) (Gulrajani et al., 2017). These methods aim to enforce 1-Lipschitz continuity of the discriminator, which requires that the gradient norm of the discriminator remains close to 1 with respect to its input. Here, we adopt a LSGAN + GP to: approach, which modifies the total loss of the discriminator

(5)

where is a hyperparameter that controls the weight of the gradient penalty, and is an interpolated sample given by:

(6)

where is randomly drawn from a uniform distribution [0,1], x is denotes a real sample and a generated fake. The loss for similarly modified. During training, a new collection of synthetic events was generated from the template pool at each epoch, while the field data image collection remained unchanged. Table 1 summarises our CycleGAN training configurations.

Figure 3 Unpaired image dataset. Top: Recorded field data samples. Bottom: Forward modelled and processed synthetic samples. Images have a resolution of 320x320 and are normalised to [-1,1]. Both components of the dataset share semantic content, but differences are particularly visible in the SNR and wavelet shapes.

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Optimization Steps

Batch Size

Learning Rates

cycle

GP

ℓgan

ℓreg

300k

1

1,00E-04

5

0.1

L2

L1

Table 1 CycleGAN training configurations. We use the same learning rates for both generators and discriminators.

Figure 4 Top: Synthetic samples. Bottom: Corresponding translated images synthesized by the generator. The position and structure of the events are preserved while the style of the field data domain is applied.

Figure 5 a) and c): Synthetic sample with some selected traces. b) and d): Translations corresponding to a and c. The generator changes the shape of the wavelets while retaining their positions. Traces in b and d are normalised.

Results

Figure 4 shows various translations performed by the trained generator, which maps images from the synthetic to the field data domain. Visually, the synthesized images are indistinguishable from real events. Furthermore, the positions and shapes of the events remain unchanged. The generator modifies only the signal-to-noise ratio and the shape of the wavelets to approximate the data distribution of the field data. Figure 5 provides a detailed view of a synthetic sample and its translated counterpart, with some selected traces for comparison. The generator reshapes the Ricker wavelets and mimics the acquisition system’s typical smearing and stretching of the wavelets that were observed in the field data. Hence, explicit forward modelling aiming at replicat-

ing one-to-one field data specific characteristics is not necessary when using image-to-image generative models. Instead, the generators learn and apply these details automatically, making it sufficient to provide the generator with just a rough skeleton of the fibre strain responses.

Showcase application: Phase arrival segmentation With a trained CycleGAN generator, one can create an unlimited number of realistic data samples and directly transfer pre-calculated labels. In the following, we demonstrate this workflow and its benefits for a model that is trained to identify phase arrivals of microseismic events in DAS images. To evaluate the impact of the FIRST

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Figure 6 Overview of the proposed training scheme. Synthetic samples are translated into the field data domain. Labels are then adjusted to the resulting SNR of the translated samples before being used as data pairs to train the phase arrival segmentation model.

Data

# P-Labels

# S-Labels

# Background

P/S

SYN

505,191

585,665

101,309,144

0,863

CGAN

325,052

544,688

101,530,260

0,595

data translation, we train two models under identical conditions: one trained with synthetic and one with CycleGAN domain-translated data only. From here on, we will refer to these models and their corresponding datasets as SYN-model/data and CGAN-model/data, respectively. To obtain labels for phase arrivals, we use ray-tracing software from Roeser et al. (2018) to get P- and S-wave arrivals for each fibre channel in the SYN-data. P- and S-wave labels are assigned using boxcar functions that envelop the Ricker wavelet responses. Hence, the label matrices are in binary format (one-hot) with a separate channel for each class: P-wave arrivals, S-wave arrivals, and background. Then, synthetic samples are translated by the generator to obtain the CGAN-data, and labels for both datasets are adjusted to the resulting signal-to-noise ratio of the respective sample to prevent false labelling in noise sections (Figure 6). Table 2 compares the number of P- and S-wave arrival labels obtained from 1000 generated SYN-data and corresponding CGAN-data samples. Notably, the CGAN-data exhibit a significantly lower P/S-ratio compared to the SYN-data. This indicates that the generator tends to attenuate the P-waves of synthetics to approximate the amplitude distribution of the field data.

Table 2 Comparison of P-wave, S-wave, and background label distributions obtained from 1000 SYN-data samples and their corresponding CycleGAN domain-translated CGAN-data samples. The lower P/S ratio in the CGAN-data indicates that the generator tends to attenuate P-waves.

Training details

To meet the specific requirements of a phase arrival segmentation model, we use a modified Unet-Transformer (UNETR) architecture introduced by Hatamizadeh et al., 2022. The UNETR architecture combines a Vision Transformer (ViT) encoder with a fully convolutional decoder, which enables it to capture both global context and local features effectively. Here, the ability of the ViT component to capture the global context is particularly valuable for the picking model, since accurate P- and S-wave labelling requires the interpretation of pixels in the entire image context. In addition, our model uses two techniques proposed by Qin et al. (2021) to further enhance its segmentation performance.

First, it extracts three intermediate coarse predictions from different stages of the decoder which are incorporated into the training objective. Second, a residual network (Refinement-Module) processes the latest decoder output to determine the residuals between predicted segmentations and ground truths, which have been shown to improve the model’s ability to accurately segment objects with complex boundaries (Qin et al., 2021). Figure 7 gives an overview of the model architecture.

Figure 7 Overview of the proposed picking model architecture. The input image is divided into non overlapping patches of size 16x16. Intermediate outputs from the transformer encoder are merged with a fully convolutional decoder via skip connections.

Furthermore, we extract three additional coarse predictions from the decoder path and apply a residual network (Refinement-Module) to the last decoder output.

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The training objective is defined as the sum of loss contributions from all outputs using a multi-class segmentation loss of choice. In this study, we apply the Generalized-Dice-Focal-Loss (Ahamed and Rahmim, 2023) because it is particularly well suited for multiclass segmentation tasks with deterministic labels and imbalanced class distributions (Table 2): (7) where denotes the generalised dice loss (Sudre et al., the focal loss (Lin et al., 2017), and are bal2017), ancing weights for the P-arrival, S-arrival, background classes.

The model outputs are normalised using the Softmax function before being used in the loss computation. Both models were trained for a total of 30,000 optimisation steps with a batch size of 10 and a learning rate of 0.001. During training, samples were randomly rotated by 0°, 90°, 180° or 270°. These geometric augmentations were used for two reasons: first, to improve the model’s ability to generalise features from the training images;

and second, to improve final inference on continuous DAS recordings. For inference, continuous DAS data are processed with a sliding-overlapping-window approach (Tegtow et al., 2024). Predictions are made for all four rotated versions of each window, then rotated back, stacked, and smoothly blended with overlapping regions weighted using a Hann window taper.

Qualitative comparison

Figure 8 shows a collection of both model predictions on unseen field data. Despite being trained exclusively on synthetics, the SYN-model performs reasonably well. It successfully identifies phase arrivals and avoids incorrect labelling of codas or reflections in most cases. However, it does not always consistently label the full extent of the visible phase arrivals. On the other hand, the CGAN-model shows more consistent predictions and utilises visible signals more effectively. Furthermore, the CGAN-model more precisely separates temporally close and similar events into individual arrivals. However, since the CycleGAN generator has encountered some events before during its training,

Figure 8 Predicted phase arrivals on unseen field data. Blue: P-wave; Red: S-wave arrivals. a) Events that were seen by the CycleGAN generator during training. b) Events that were not seen by the generator. While the SYN-model performs reasonably well, the CGAN-model yields more consistent predictions.

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Figure 9 Example picks with corresponding hyperbolic curve fits. a) All picks are sufficiently close to the fits and are therefore considered as inliers. b) False picks occurring between true phase arrivals are correctly classified as outliers, while some correct picks are incorrectly classified as outliers for being too far from the fitting curves. c) When multiple events occur within the selected time window, only the event with the most P- and S-inliers is retained, while all other correct picks are automatically classified as outliers.

Model

Events

P-Inlier

P-Outlier

P-Ratio

S-Inlier

S-Outlier

S-Ratio

0,73

18252

2277

0,889

0,74

22997

1959

0,922

Stage 20 SYN

514

13042

4831

CGAN

545

10032

3527 Stage 21

SYN

616

13477

6289

0,68

26099

2656

0,908

CGAN

676

9862

6318

0,61

33541

2203

0,938

SYN

466

9203

3399

0,73

17553

1800

0,907

CGAN

536

7489

4086

0,65

23657

1118

0,955

SYN

1596

35722

14519

61904

6733

CGAN

1757

27383

13941

80195

5280

Stage 23

Sum

Average SYN

0,711

0,902

CGAN

0,663

0,938

Table 3 Results of the RANSAC evaluation. The CGAN-model provides approximately 11% more inliers and around 10.1% more detected events. Note that not all outliers correspond to false picks, as correct picks can also be classified as outliers if they lie too far from the fitted curves.

predictions may be influenced by prior exposure. To demonstrate that the model has successfully learnt and generalised field data characteristics, Figure 8b shows only field data events that were not part of the CycleGAN generator’s training. Even in these cases, the CGAN-model provides more consistent results.

requires solving a quartic optimisation problem for each pick– curve combination. Because the latter is computationally intensive, naive random sampling and testing can be inefficient. To accelerate convergence, we first filter the proposed curves using physically motivated geometric constraints. For example, considering our fibre geometry, we impose the following rules:

Quantitative comparison

In the absence of ground truth labels for the field data, a quantitative assessment of the performance of one of the picking models is not straightforward. To distinguish between true and false picks provided by a model, we propose using a Random Sample Consensus (RANSAC) algorithm (Fischler and Bolles, 1981) to determine optimal parameters of hyperbolic curves that best fit a subset of selected picks. This allows picks to be classified as inliers or outliers. Finding a hyperbolic moveout curve using RANSAC essentially involves two steps per iteration: first, proposing a curve based on a randomly selected minimal set of picks required to construct the curve; second, evaluating the proposed fit by computing the distance from each pick to the nearest point on the curve, which 48

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For each phase:

• The conic section must be a hyperbola or parabola (circles and ellipses are excluded).

• The transverse axis should be approximately aligned with the time axis.

For combined P- and S-wave curves:

• Vertex channel coordinates should be approximately equal.

• The P-wave vertex must precede the corresponding S-wave vertex in time.

• The eccentricity of the P-wave fit should exceed that of the S-wave.

TECHNICAL ARTICLE

This allows several tens of thousands of random trials to be performed in a negligible amount of time to pre-select a specified number of curves for evaluation. For a set of picks with time and fibre channel coordinates (t, c), n=1,...,N, hyperbolic fits can be determined by finding a set of of the general conic six parameters a = section equation: (8) Assuming error-free picked arrival times, a subset of five randomly selected picks is sufficient to determine a conic section intersecting these points: (9)

which can be straightforwardly solved for the parameter vector a. If the resulting curve violates the predefined geometric constraints, a new random subset of five picks is selected, and the process is repeated. Otherwise, the distance from each pick to the nearest point on the curve is calculated. Picks with distances below a predefined threshold are classified as inliers, otherwise as outliers. The best fit is defined as the curve with the highest number of inliers. If both P- and S-wave arrivals are present, the computations in Equation (9) are carried out separately for each phase. If two valid single-curve fits are obtained, both are subsequently tested against the combined constraints.

To apply the proposed RANSAC metric to our DAS data, both picking models were first applied to the continuous recordings of stages 20, 21, and 23, using the sliding-overlapping-window inference strategy described above. Within each predicted arrival window, the first time-sample was selected as the phase arrival.

Remaining picks were then grouped into individual microseismic events if they occurred less than 200 time-samples (100 milliseconds) apart from each other. Figure 9a shows an event with both Pand S-wave picks with their corresponding hyperbolic fits. Because all picks are close enough to the fitted curves, all were classified as inliers. However, we are aware that this metric is far from being perfect. Figure 9b shows a case where RANSAC successfully identified incorrect P- and S-wave picks between the true wavefront arrivals as outliers, while some correct picks were incorrectly classified as outliers for being too far from the fitted curves. Furthermore, if multiple events occur within the same time window, only the event with the largest number of combined P- and S-picks is retained as an inlier, while all other valid picks are automatically classified as outliers (Figure 9c). Table 3 summarises the results of the RANSAC evaluation. Across all stages, the CGAN-model detected a total of 1757 events, 161 more than the SYN-model.

Notably, the SYN-model provides more P-wave detections than the CGAN-model. This can be attributed to the initially higher P/S-ratio of the SYN-data. Consequently, the SYN-model is biased towards detecting a similar P/S-ratio in the field data. Hence, using CGAN-domain translated data also has the positive effect of balancing class labels towards the distribution of the field data.

Overall, the CGAN-model shows better performance, with roughly 11% more inliers and about 10% more detected events.

Conclusions In this study, we trained a cycle-consistent adversarial network to translate forward-modelled synthetic DAS images into more realistic versions. The CycleGAN generator preserves the structure and positions of the synthetic events and automatically applies field data-specific characteristics. This simplifies the forward modelling process, as only a rough skeleton of the fibre strain responses is required as input for the generator. Furthermore, by modifying the shape and amplitude of the wavelets, the generator adjusts the label distribution to better align with the field data. After training, the generator can synthesize any number of realistic samples from a pool of synthetic events and pre-computed labels are transferable. We demonstrated the benefits of this approach by training two models to identify seismic phase arrivals in DAS images: one trained only on synthetic data and the other on CycleGAN-translated data.

Our analysis showed that the model trained with CycleGAN domain-translated data achieved better qualitative and quantitative results. The combination of labelled synthetic data with a conditioned image-to-image generative model can be utilised for automated synthesis of labelled datasets that can be used to train models for a variety of downstream tasks. The data distributions of these datasets more closely resemble those of the target datasets, which effectively counteracts model generalisation issues. Furthermore, it might serve as a first step towards generating labelled datasets for different case studies, which could be integrated into larger models to obtain more diverse and universally applicable tools. However, a potential limitation is that training a CycleGAN generator requires a representative baseline catalogue of real events. In real-time monitoring applications, newly detected events can be used concurrently to fine-tune the generator, to dynamically adapt it to changing data characteristics, especially when the base catalogue is not comprehensive.

Acknowledgements We thank the sponsors of the PHASE consortium for supporting the research presented in this paper.

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https://doi.org/10.3390/s22239510.

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Special Topic

LAND SEISMIC

Land seismic solutions are improving to facilitate ever more channels, more hardwearing and smaller nodes along with more effective cableless systems to ensure robust acquisition in the most challenging terrains, in challenging weather and with little downtime.

Demand for land seismic solutions is proving to be sustained, motivating solution providers to innovate to achieve higher density, larger channel count, higher productivity vibroseis, greater efficiency and more automation.

As a result, the sector is continuing to evolve as competing companies devise improved systems are becoming smarter and can offer more sophisticated insights into the subsurface.

Tim Dean et al give an overview on the development of nodal acquisition systems and offer their opinions and suggestions on future systems.

Dennis Pavel explains why the process of seismic data downloading and transcription is a critical aspect of a nodal system.

Piotr Potepa et al describe how challenges specific to transition zone (TZ) in 3D seismic surveys can be overcome in a cost-effective manner, by adapting land seismic equipment to marine conditions.

Andrea Moscariello et al present a regional exploration strategy needed to develop a viable geothermal industry and ensure successful pathways to unlock the full deep subsurface geothermal potential of Switzerland.

Nabil Khadiri Yazami et al present an efficient and low-impact methodology that delivers data-driven diagnostics to inform both ongoing and future acquisition and imaging strategies.

James Sheng et al introduce a multiparameter full-waveform inversion (FWI) approach for land seismic imaging that jointly estimates subsurface velocity and reflectivity.

Special Topic overview

Submit an article First Break Special Topics are covered by a mix of original articles dealing with case studies and the latest technology. Contributions to a Special Topic in First Break can be sent directly to the editorial office (firstbreak@eage.org). Submissions will be considered for publication by the editor.

It is also possible to submit a Technical Article to First Break. Technical Articles are subject to a peer review process and should be submitted via EAGE’s ScholarOne website: http://mc.manuscriptcentral.com/fb You can find on www.firstbreak.org/guidelines the First Break author guidelines.

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January

Land Seismic

February

Digitalization / Machine Learning

March

Reservoir Monitoring

April

Underground Storage and Passive Seismic

May

Global Exploration

Further Special Topics may be added over the course of the year.

SPECIAL TOPIC: LAND SEISMIC

Land seismic node technology: Current capabilities and future directions Tim Dean1* and Matt Grant 2 give an overview on the development of nodal acquisition systems and offer their opinions and suggestions on future systems.

Introduction In 1996 Ian Jack published a summary of the specifications for a future land seismic recording system (Jack 1996). Ian Jack’s system was based on what he called an SGR (seismic group recorder) but what we would now call a node. Back in 1996 the range of nodes available was limited and they were both heavy (> 5 kg) and expensive, restricting their use (Dean et al. 2018).

The introduction of GPS timing and modern lightweight electronics has resulted in a boom in nodal acquisition and there are a wide variety of units currently available (Figure 1).

We have been tracking the development of nodal acquisition systems with much interest over the years and, similar to Ian Jack’s paper, we decided that it was time we gave our suggestions on future systems. Many of the features we recommend are not new, and we have attempted to give credit to the originators accordingly, for those we have missed, we apologise. Obviously, we could have dreamt up some unlikely component, e.g. a tiny geophone with a low natural frequency and high spurious frequency, but we attempted to be realistic in the choices made.

The aim of the system design is to reduce time (i.e. cost) and HSE exposure whilst maximising the quality of the data acquired.

A commonly accepted model of quality vs. cost is shown in Figure 2. Initially, we can make significant improvements in quality for little additional cost, but as the system improves additional improvements in quality become increasingly costly. Ideally, our system would appear near the inflection point of the graph (the green point on Figure 2), which represents the best value in terms of the trade-off between quality and cost.

The quality of the seismic data is not only related to the node itself (i.e. the sensor and its electronics) but also the coupling

Figure 1 A photo of just some of the modern nodes available on the marker (from left): Sercel Accel, Stryde, EarthPulse ANT-1C, Geospace Pioneer, INOVA Quantum Accuseis, AllSeis.

1

Curtin University | 2 Grant Geoscience Consulting

*

Corresponding author, E-mail: tim.dean.geo@gmail.com

of the sensor. Similarly, the cost of the node is not only related to its purchase price but also its cost of use. In this paper we begin by describing the acquisition process. By examining this process in depth, we can then make decisions about how the node will be configured, which will be the subject of the second section.

Acquisition process When describing the acquisition process, we assume that the survey has already been planned, and the lines have been cleared (if required).

Scripting

The first stage in deploying the nodes (assuming they are fully charged of course) is to script them. Scripting the nodes involves setting their recording parameters such as the gain level, sample-rate, and any acquisition filters. Of particular importance is programming the recording periods – if we are limited in the times during which we can shoot, then there is no point wasting battery and memory by recording data outside these periods. For some systems this ‘calendar’ option is limited to simply setting the times at which the node will be operational. Although better than recording continuously, a superior option is to be able to individually set recording times by date as well. Although not applicable to every survey, often longer breaks during acquisition may be required, for example to allow the crew to have rest days.

Figure 2 Theoretical quality vs. cost graph. Quality improves rapidly at the lower end of the cost axis but small improvements in quality become increasingly costly.

DOI: 10.3997/1365-2397.fb2026003

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Figure 3 Photo of a typical node system harvester. The nodes are placed into racks to script/download data/charge. Often there will be different download and charge racks as the former is considerably quicker (minutes vs. hours).

Figure 4 Stryde initialisation tool used to program the nodes with their acquisition parameters and positions during deployment. Courtesy of Stryde.

If we can set the nodes not to record during these days, then we can conserve additional memory and battery.

Scripting the nodes is typically done by running the nodes through the harvester (Figure 3). Although the scripting itself is quick (of the order of a few seconds) it still takes time to physically load the nodes into and out of the harvester. An alternative approach is to script the node during its planting, using an initialisation device, such as that employed by the Stryde system.

(Figure 4), or by connecting to it wirelessly. This may appear to be desirable functionality but if this is the only operation required during deployment (note that the Stryde system also programs the node with its position at this stage) then it may be more efficient to do so before deployment. It also requires careful management – if one of the node programmers is incorrectly set up then all the nodes it initiates will be incorrect as well.

Survey

Once the nodes have been scripted (or will be scripted during deployment) we need to navigate to their position. This is conventionally done in one of two ways: 1. A dedicated survey team moving ahead of the layout team marking the receiver positions. There are multiple methods to do so. For closely spaced nodes the survey team can operate on foot with positions marked with spray-paint.

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Figure 5 Photo of the Stryde positioning-with-layout system.

The GPS antenna is mounted on the backpack with the nodes caried in a tray on the side. The operator is initiating a node by placing it upside down into the small initiation device. Courtesy of Stryde.

Figure 6 The ‘Tiny Surveyor’ autonomous survey robot. The can of spray paint can be seen mounted on the rear of the robot.

Alternatively, a vehicle can tow a chain with multiple stations marked on it. For sparser positions surveying can be done from a vehicle. For example, markers (e.g. biodegradable plastic bags of sand) can be dropped out of the vehicle window at each station.

2. Positioning-with-layout: the layout team have their own integrated survey system that is used to navigate to each receiver position where the receiver is then planted. Such a set-up is shown in Figure 5, the GPS system including the antenna is mounted to the back of the backpack and the navigation tablet on the front. Once in position the user initialises the node (carried in the tray on their hip) with its acquisition parameters and position.

The positioning with layout approach may seem at first glance to be the most efficient as it removes the duplication of multiple passes down the line. With such approaches, however, the team progresses at the speed of the slowest activity. For example, it may take twice as long to plant the node as it does to navigate to the next position, thus the surveyor is left standing around waiting. Another alternative is to use a small robotic surveyor as part of the layout team. Such a unit is shown in Figure 6.

This unit is capable of navigating between points autonomously, each one being marked with spray-paint, if the planned point

SPECIAL TOPIC: LAND SEISMIC

cannot be achieved then the operator can adjust the position by manually steering the robot (Dean and Grant 2021).

Transportation

Once the position of each node has been identified, either in advance or during the layout process, the next stage involves placing the nodes in position. Again, there are multiple methods to do so, including: 1. The nodes can be dropped individually out of a vehicle at their required position. If done accurately then the nodes themselves become the survey markers.

2. Trays of nodes can be placed at regular intervals along the line and then hand-carried to their appropriate positions and planted.

3. The nodes can be carried within a vehicle that stops at each position or set of positions for the node/s to be planted.

For efficiency of transportation (not just during deployment but also during mobilisation) the nodes should be as light as possible but also be packed efficiently.

Planting

Now the node is at its correct position it needs to be planted into the ground. Typically, this has involved digging/scrapping a small hole using a pick or mattock, placing the node in the hole, and then stamping on it to get firm coupling. Obviously in soft terrain such as sand the stamping may be unnecessary. Rather than digging the hole by hand the hole can be created using a machine-mounted auger (Figure 7) which can also include a navigation system, removing the need for separate surveying.

Although coupling has been shown to be important, in some terrains, particularly in sand, coupling using a spike may not be effective, instead simply placing/burying the node on the ground may be sufficient. For soft/muddy terrains we have found that cylindrical-shaped nodes not only result in excellent coupling but can also be extremely easy to emplace if a tool is used to create the hole into which they are then inserted. The Stryde node can bridge both these scenarios as it has a removable spike that can be used when required (although the long cylindrical body may leave it susceptible to swaying if the body of the node is not partially buried as well).

Again, there is likely to be a trade-off between the time spent achieving perfect coupling and the resulting quality of the data (i.e.

Figure 2). It may actually be advantageous to spend an equivalent period of time planting a large number of slightly poorly coupled nodes rather than a smaller number of perfectly coupled nodes.

Activation

Once the node is in place it needs to start recording. Nodes can be activated in a number of ways, using a magnet, a specialised tool (e.g. Figure 9), or the node can activate automatically when it is placed vertically.

Line and point assignment

Land seismic surveys typically employ a local grid coordinate system where positions are defined in terms of line and point numbers rather than their actual coordinates. This vastly simplifies acquisition (and processing) as the true (geographic) coordinates are often complex, particularly if the grid is not oriented northsouth. Therefore, each node needs to be assigned a line and point number. This can be done directly during emplacement, either by programming the node before it is planted (Figure 5) or after it has been planted by connecting to it wirelessly. Alternately the position and serial number of the node can be recorded and the values assigned after harvesting. The final approach, and the most efficient as no field effort is required, is self-assignment where the line and point values are assigned post-acquisition based on matching the surveyed positions to the GPS positions recorded by the node. Obviously, this requires accurate internal GPS positions to be recorded by the node, but through the employment of an appropriate matching algorithm even relatively closely spaced nodes (~4 m) can be assigned correctly (Dean 2025).

Quality control

The options for quality control during acquisition currently vary from real-time data, intermittent/compressed data (neither of which are applicable for large channel-count systems), real-time QC, medium-range (hundreds of metres) opportunistic QC, short-range

Figure 8 Stryde node showing its removable spike (which is inserted into the base of the node).

Figure 9 Photo of the NuSeis ‘bump’ tool which is used to turn the nodes on. Courtesy of GT).

Figure 7 Track-mounted auger used to create holes for planting nodes in.

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Figure 11 SmartSolo node split into its electronics/sensor (left) and battery (components). The charging/power connectors are shown by the white boxes and the download connector by the black box.

Figure 10 Examples of determining the most visible colour for a node. (a) and (b) show two different terrains whilst (c) and (d) show their RGB difference to six different colours. The largest and smallest differences are shown in the top left and top right of the photos respectively.

(tens of metres) opportunistic QC, and blind (Dean et al. 2025).

Modern nodes are extremely reliable (Dean et al. 2021) so QC is not really required to confirm the nodes are operating, more so to make sure that they are still correctly planted (or in the location at all).

Retrieval

Once recording has been completed the nodes then need to be collected. One of the obvious issues with doing so is finding them.

Unlike cabled systems where you simply follow the cable, nodes can become completely buried or disturbed by wildlife etc. One obvious way to help find the nodes is to make them a distinctive colour. The visibility of different colours can be tested by taking the Euclidean distance between the average RGB values in a terrain photo and the candidate colours (Miller et al. 2014). An example of the process is shown in Figure 10 which shows two different ground terrains, dirt (a) and grass (b) compared to six possible node colours. For both conditions blue has the largest contrast whilst orange has the lowest contrast (shown in the corners of the photos). Reflective coatings can also make nodes more visible (Dean et al. 2020).

If nodes do become lost, if they have some form of communication then the strength of the signal can be used to help locate their approximate position, with metal detectors being used to find them (Dean, Grant and Sweeney 2025). A nice alternative, not currently offered, would be to have a small buzzer in the node that could be activated remotely to help locate the node. Such buzzers can, however, by quite bulky (e.g. 10 x 30 mm) but still light (e.g. 6 g).

components has additional advantages, as the download time (typically minutes) is much shorter than the recharge time (typically several hours). By employing additional batteries, you can utilise the recording section of the nodes for longer periods. You can also ‘mix-and-match’ different node components (Figure 12).

The obvious disadvantage of such an approach is that it requires the nodes to be split apart for downloading/charging. This process can be improved using automatic machines (the spike at the base of the node acts as the head of a bolt which screws the two components together). Opening the node also risks introducing dirt/moisture into the internal components when it is reassembled.

Although wireless charging is less efficient, the charge times do not appear to be longer for these systems, for example, the Stryde and Pioneer node charge times are ~4 hours for 50 days recording, consistent with, if not better than, the charging time of other systems (Figure 13). Induction charging also creates heat, which may cause issues if a large number of nodes are being charged in an enclosed space.

Deactivation

The nodes have now been downloaded and charged ready for their next survey. One stage that is not always necessary/available is deactivation of the nodes. Some nodes, particularly those that are designed to activate automatically, continue to operate in a low-power mode. Although the battery usage is minimal, if the nodes are not redeployed in a short period they will need to be recharged before being reused. A better option is to be able to

Charging and downloading

The two main choices for charging and downloading are wireless or direct contact. Wireless systems have the advantage in that there are no exposed contacts that can be damaged. An exception to this is the SmartSolo system that protects the physical contacts by placing them inside the two halves of the node meaning they are only exposed when the node is split in half for charging and/ or downloading (Figure 11). Being able to split the node into two 56

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Figure 12 A SmartSolo 3C IGU (top section of the node) attached to a base with external battery connection option.

SPECIAL TOPIC: LAND SEISMIC

Figure 13 Battery duration/charge time for modern nodes, the higher the values the proportionally faster the node charges. The nodes with inductive charging are shown in green.

turn the nodes off completely. Although obviously this then requires an additional stage of turning the nodes back on (ideally during the scripting or deployment process), this is much quicker than having to charge them again.

System requirements and design Now that we have the acquisition process described we will define the ideal system as we see it. We begin by addressing the sensor and the form factor and configuration, in our view the two most important features.

Sensor

A key component of any seismic node is the type of sensor that it contains. The choice of sensor is currently limited to the traditional geophone, MEMS (Sercel WiNG & Accel and INOVA Quantum Accuseis), or a piezo-electric accelerometer (Stryde).

If a geophone is selected as the sensor, then there is a further choice between the element type, in particular its sensitivity and natural frequency. Most geophone-based nodes offer a choice between 5 or 10 Hz natural frequency geophones. The lower the natural frequency the better the low-frequency recording performance, but also the lower the spurious frequency. This can be seen from the geophone response curves for four typical geophones shown in Figure 14. The bandwidth in octaves (calculated between the natural frequency and the spurious frequency) for each geophone is shown in the plot legend; note that the 5 Hz geophones have a lower bandwidth than the 10 Hz geophones, something that is not immediately evident due to the logarithmic scales used on the plots. The tilt-tolerance of geophones decreases with their natural frequency (Dean and Grant 2024) so additional time and effort is required to ensure near vertical placement is achieved.

As well as the natural frequency of the geophones, there is also a choice to be made about sensitivity. For modern nodes, high-sensitivity geophones have become the norm (~80 V/m/s vs. standard sensitivity of ~28 V/m/s). The responses of high-sensitivity and standard sensitivity geophones are also shown in Figure 14. High-sensitivity geophones are preferred as they enable lower amplitude signals to be recorded if the dominant source of noise is system (electronic) noise.

Theoretically this would, in-turn, allow the source energy to be reduced. For example, the 2.8 times larger sensitivity of a high-sensitivity geophone should allow the sweep-length to be reduced by a factor of ~7.8 (the SNR of vibroseis is proportional

Figure 14 Geophone response curves for four typical geophones (in this case made

by DTCC).

to the square-root of the sweep length (Landrum 1967)) but the dominant source of noise is typically ambient noise. Increasing the sensitivity of the geophone will increase the signal level but also the ambient noise level, and thus the SNR will not change.

When compared directly, high-sensitivity geophones tend to be larger and heavier mainly due to their larger internal coil. The Geospace GCL and Pioneer nodes (Figure 15) are unique in that they utilise a much smaller (‘SMG’) element that weighs just 43 g vs. 130 g for a standard element, at the expense of a small decrease in sensitivity (63 V/m/s, note that this is still higher than a ‘standard’ geophone). These small geophones enable the lightweight Pioneer and GCL nodes (Figure 16).

MEMS sensors have a reputation for greater power consumption. For example, INOVA offer a geophone and MEMs version of their Quantum node (Figure 17) – the MEMS version promises 23 days of usage and weighs 0.48 kg (48 days/kg, Figure 18) whereas the geophone version offers 50 days recording and weighs 0.65 kg (77 days/kg). The Sercel WiNG in both its analogue and digital forms claim the same battery life (40/50 days with pathfinder QC on/off, 53/66 days/kg) with only a nominal (<3%) difference in weight. The new Sercel Accel offers 30 days recording (97 days/kg). Even if the power consumption of MEMS nodes is higher, the battery lives of MEMS-nodes still compares favourably with geophone systems such as AllSeis (33 days/kg) and the SmartSolo IGU-16 (22 days/kg).

The only node with a piezo-based accelerometer (the Stryde node, Figure 20a) is also that with the best battery life (333 days/ kg, Figure 18).

Although it is difficult to compare the relative sensitives of accelerometers and geophones (Goujon et al. 2021) our experience where side-by-side measurements have been made (Dean and Grant 2024, Dean, Grant and Sweeney 2025) suggests that they are broadly equivalent. Comparisons of different geophone-based systems have also shown little difference (Dean 2024, Dean and Hooi 2025). Concerns also been raised about differences in dynamic range, particularly with respect to clipping on near-offsets (Miller, Ivanov, Peterie, Bailey and Sloan 2014) but our work (Dean et al. 2021) shows that this is unlikely to be an issue. Modern systems also have dynamic ranges (typically at least 124 dB) that far exceed that previously suggested by Shirley et al. (1985) of just 80 dB. Care must be taken when directly comparing the dynamic range of accelerometer and geophone-based systems (Dean, Grant and Sweeney 2025).

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Figure 17 INOVA quantum nodes containing (a) MEMS, and (b) geophone sensors.

Figure 15 Photo of a GS-One 10hz Geophone (left) and SMG 10Hz Geophone (right). Courtesy of Mike Dahl, Geospace.

Figure 16 Geopace nodes (from left) Pioneer, GCL and GCL3 (a 3-component node).

We remain therefore relatively agnostic on which sensor to choose, although if a MEMS system is employed then it needs to have low power consumption and a low 1/f noise corner frequency. If a geophone is employed then it needs to be a modern, miniaturised element (e.g. Figure 15) to keep node weight down.

Form-factor and configuration

Although popular in early nodal systems, the use of systems with external sensors and batteries (Figure 19) has become increasingly unpopular. This is a result of both an acceptance that denser point-receivers are generally superior to sparser arrays of geophones (Ourabah 2024), and the significant improvements in nodal technology over the past 15 years.

The first successful integrated node, the Fairfield Z-Land (Figure 20d) introduced in 2008, weighed 2.2 kg, had a volume of 1900 cc (excluding spike), but a battery life of only 12 days.

In contrast, modern nodes are typically less than 1 kg, with the smallest, the cylindrical Stryde node (Figure 20a) being just 150 g with a volume of 170 cc (15 times lighter and 11 times smaller than Z-Land). Similarly, the more conventionally shaped Geospace Pioneer (Figure 20c) weighs just 450 g and the INOVA Quantum Accuseis (Figure 20b) 480 g. Despite these lighter weights, modern nodes typically have battery lives of between 20 and 50 days (Figure 18).

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Figure 18 Weights and battery durations of different nodes.

Solo IAU-19 (Figure 21). Rather than force the user to choose between an internal and external sensor option, manufacturers tend to offer the option to ‘override’ the internal sensor of the node by attaching an external sensor (Figure 22), rather than removing the internal sensor completely and thus sacrificing the utility of the self-contained node.

Again, although some systems offer the option to connect of an external battery (Figure 12), no modern large-scale systems are designed with such a configuration in mind. The SmartSolo node offers several different configurations as the node splits into two sections, one containing the recording electronics/sensor and the other the battery (Figure 11). Components with different sensor configurations (1-component/3-component/external sensor) can then be combined with different capacity batteries or external battery connectors to create different nodes.

The NuSeis system (Figure 23) is designed so that the electronic components can be easily moved between different form factors. Even nodes that are not explicitly designed in this way may be reconfigured if required (Figure 24).

Bucking the trend of the conventional body and spike node and the cylindrical designs of NuSeis and Stryde is the new Accel node from Sercel (Figure 25). Accel is a drop-node, i.e. it is designed to be simply placed on the surface without being buried

SPECIAL TOPIC: LAND SEISMIC

or coupled with a spike. This concept is instantly attractive as it is far easier to emplace and far more suitable for automation.

The first key consideration when designing our own node was keeping the weight as low as possible. Figure 26 shows a breakdown of the weight of the components in two popular commercial nodes, both of which have a conventional shape.

Note how the battery, which we originally thought would be the heaviest component, is only ~30% of the weight of the node, less than the total weight of the case (~40%).

• Direct contacts for charging/downloading – We have extensive experience of using nodes with external connectors and have found few issues and thus ideally the node should use direct physical contacts – but only if this can be done without sacrificing the ability to bulk handle the nodes.

• The node should have a colour that makes it visible in the terrains that it is most likely to be used in. Although dark colours may be tempting (Figure 10), these may result in the node becoming too hot, so lighter, particularly fluorescent, colours are recommended.

Design criteria

In terms of the functionality of the node we recommend: • There should be an option to script the node during its deployment, but this should not replace the ability to script nodes prior.

• The system should be compatible with a range of different survey options.

Our design criteria are summarised below. In terms of the physical characteristics of the nodes we recommend: • Light and compact – the node should be a shape that minimises the size and weight of the case and other ‘superfluous’ elements (i.e. those that are not integral to recording seismic data). The weight should be consistent with other lightweight nodes currently offered (Figure 18a), ideally less than 0.3 kg (the target back in 1996 was 0.2 kg (Jack 1996), but this didn’t include the battery).

• Adaptability – the node should be as adaptable as possible, in its simplest form, the node should be capable of being used with different sized spikes or no spikes at all. Ideally it should be able to be easily reconfigured if a different form-factor (e.g. a cylindrical body in muddy terrains) is more appropriate. If geophones are used then it should be easy to replace the elements if they become damaged, or if a different element or even an external sensor is desired (note that the ability to connect an external sensor (Figure 21) should not be a standard feature of the node design).

• Suitable for bulk handling – a key element in the efficiency of the system is to be able to handle the nodes in trays. The aim is that the only time the nodes are not in a tray is when they are planted in the ground.

• Battery life – There is a direct trade-off here with weight, increasing the battery life will increase the weight of the node although perhaps not as much as we originally thought (Figure 26). Given the ability to efficiently recharge the nodes due to their bulk handling, we believe a battery life of 25 days is sufficient (Figure 18b).

Figure 19 Photo of early external sensor/external battery nodes, from left: Autoseis HDR, Geospace GCL, and INOVA Hawk.

Figure 20 The first fully integrated node, the (d) Fairfield Z-Land with some more modern successors (a) Stryde, (b) INOVA Quantum Accuseis and (c) Geospace Pioneer.

Figure 21 Photo of the (a) WiNG AFU and (b) SmartSolo IAU-19. The sensor is connected via the connector on the left of the nodes.

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Figure 22 Modern systems with external sensor options, (a) INOVA Quantum, (b) AllSeis, and (c) SmartSolo IGU-16HR-IES.

Figure 25 Photo of the Accel node from Sercel.

Figure 23 Three different configurations of NuSeis nodes.

Note that the electronic housing (under the transparent dome) is identical for all nodes.

Figure 26 Break-down of the weights of the different components contained in two different nodes.

harvesting unit such as the Geospace line health recorder (LHR) which is compatible with a drone.

Figure 24 A standard AllSeis node (left) that has been converted to a drop-node (right) using a 3D printed case that replaces the lower half of the original node case. The geophone is under the circular cover.

• The survey/layout systems need to be adaptable – no matter how good the plan is there are always issues encountered. Where encountered, these need to be overcome efficiently, for example by integrating offset rules (Dean 2024) into the navigation tablet.

• The node should automatically activate when turned vertically if this does not impact the ability to efficiently transport the nodes, but…

• The node should be capable of being turned completely off/on a the end/beginning of the survey.

• The internal GPS of the node should be accurate enough to enable self-assignment.

• The node should employ opportunistic QC, if short-range then it should be supported by mobile phone apps and/or a specific 60

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Discussion When asked a question about geophysics we often make the ‘joke’ that the answer to every question is ‘it depends’. The node design we have outlined here should also contain the same caveat, our design has been heavily influenced by our own recent acquisition experiences involving high-density, large channel count (>20,000 channels), high-productivity vibroseis (~4000 node moves per day with an average deployment time of ~5 days) in the Australian bush (Dean and Grant 2024, Dean, Grant and Pavlova 2021).

The ways in which nodes are used, and the terrain within which they are employed, varies greatly around the world, and we have attempted to incorporate this into our design by making the node as adaptable as possible.

Although we have been primarily concerned with describing the node itself, the way in which it is employed is a key consideration (note that we have ignored many of the technical specifications given in Jack (1996) as they have either been met or are of no consequence anymore). Given the continued increase in channel-count efficiency of use is a key consideration and we feel that the future of efficiency is automation. Although not mentioned in the previous section, our ideal node design is therefore one that is suited to an automated deployment system, in both its form-factor and ability to be handled in bulk.

SPECIAL TOPIC: LAND SEISMIC

A clear analogy is farming or forestry, where labour-intensive tasks have been replaced by mechanised and/or automated operations. GTI introduced an automated deployment system for their NuSeis system several years ago that involved using a spike to create a cylindrical hole that the node is then inserted into. This is ideal but a simpler system could be to use a post-hole driver with a node-shaped tip that could be easily mounted on a variety of vehicles. The driver would create a node-shaped hole that the node could then be (manually) placed into (rather than an auger (Figure 7) that simply loosens the dirt thus still requiring excavation and effort to ensure tilt is within specification).

We also cannot discount the cost of the node itself and its associated systems. The target cost back in 1996 (Jack 1996) was <$1000 (equivalent to $2000 in 2025)). Even though this target has been far exceeded, given the large, and increasing, number of channels being used, the node should be as low cost as possible (<$200). But when considering cost, the cost of use must be considered along with the cost of purchase. Again, this brings us back to adaptability, what works for one survey will not necessarily work in others, or be the most efficient, e.g. if the receiver spacing changes. For automation, we may need to accept that not every position may be suited to automated node deployment, but its use for a significant proportion of the survey is a huge advantage.

Dean, T. and Grant, M. [2024]. A begineer’s guide to seismic sensors.

ASEG Preview, 230, 38-44.

Dean, T. and Grant, M. [2024]. An in-depth look at ultra-high-density 3D seismic acquisition for mining. Fourth International Meeting for Applied Geoscience & Energy, Expanded Abstracts, 2503-2507.

Dean, T., Grant, M., Barnwell, R. and Barry, D. [2021]. A large-scale study of the reliability of land nodal seismic recording systems. First Break, 39(1), 69-74.

Dean, T., Grant, M. and Nguyen, H. [2020]. Quality control of land nodal seismic recording systems. First Break, 38(1), 53-58.

Dean, T., Grant, M. and Pavlova, M. [2021]. The Efficient Acquisition of High-Resolution 3D Seismic Surveys for Shallow Open-Cut Mining.

First Break, 39(8), 43-49.

Dean, T., Grant, M. and Sweeney, D. [2025]. The essential guide to land seismic nodal recording systems. ASEG Preview, 238, 58-68.

Dean, T. and Hooi, J. [2025]. A comparison of data acquired using two different land nodal recording systems as part of a 3D seismic survey.

Exploration Geophysics, 56(5), 35-43.

Dean, T., Tulett, J. and Barnwell, R. [2018]. Nodal land seismic acquisition: The next generation. First Break, 36(1), 47-52.

Goujon, N., Ourabah, A., Song, Z. and Gierz, C. [2021]. Which sensor for nodal seismic: Recording acceleration or velocity? First International Meeting for Applied Geoscience & Energy, Expanded Abstracts, 91-95.

Jack, I. [1996]. Seismic System 2000. The Leading Edge, 15(10), 11261127.

Landrum, R. A. [1967]. Extraction of signals from random noise by

References

crosscorrelation. 37th SEG Annual Meeting, Expanded Abstracts.

Dean, T. [2024]. A comparison of two land nodal seismic recording systems. Exploration Geophysics, 55(3), 277-287.

Miller, R.D., Ivanov, J., Peterie, S., Bailey, B. and Sloan, S.D. [2014].

Near surface seismic imaging: One size does not fit all. SEG Inter-

Dean, T. [2024]. Minimising the effects of obstacles on 2D seismic lines.

Exploration Geophysics, 55(6), 786-796.

national Exposition and 84th Annual Meeting, Expanded Abstracts, 183-187.

Dean, T. [2025]. The accuracy of self-assigned land seismic node posi-

Ourabah, A. [2024]. Revisiting the Single Sensor vs Array Debate in the Light of New Nodal System Technology. First Break, 42(1), 71-77.

tions. Exploration Geophysics, 56(6).

Dean, T. and Grant, M. [2021]. The evaluation of alternatives to

Shirley, T.E., Linville, A.F., Hadidi, M.T., Davis, A.J., May, C.J. and

pre-acquisition surveying for land seismic surveys. Australasian

Jurkevics, A. [1985]. A systems analysis of dynamic range in seismic

Exploration Geoscience Conference, Expanded Abstracts.

exploration. SEG Technical Program, Expanded Abstracts, 528-530.

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Data download and transcription in nodal seismic acquisition systems Dennis Pavel1* explains why the process of seismic data downloading and transcription is a critical aspect of a nodal system.

Introduction Nodes have become a popular system architecture for seismic data acquisition due to the benefits of higher operational efficiency, lower downtime, lower HSE risk and lower environmental impact. However, there are obvious operational differences associated with nodal acquisition compared to traditional cable-based acquisition. Most notably, cable systems offer real-time access to seismic data during source production since all acquisition units are interconnected, ultimately delivering data directly to a central computer system on a shot-by-shot basis. Nodes are autonomous acquisition units with no interconnectivity, a key system architecture difference that contributes to achieving the benefits described above. Nodes record continuously and store data in local memory, requiring data to be downloaded from each node after source production has completed. For example, either during receiver roll over the course of the project, at the completion of the project or typically both.

This distinction makes the process of seismic data downloading and transcription a critical aspect of a nodal system.

The process must be highly efficient to prevent eroding the in-field benefits gained from nodal architecture. It is important to note that while the process is often referred to simply as ‘data downloading’ or ‘data harvesting’, this describes only the first step. There is much more the system must do to provide final data output in accordance with project requirements.

Data download path Moving data efficiently from nodes to final output in a desired structure and format requires attention to each step along the way. The path can be fraught with potential data throughput bottlenecks both in hardware and in software. Figure 1 highlights key areas of the download and transcription path. The path starts at node memory and then proceeds through the node physical interface, passing across network interconnections until reaching the download and transcription computer (D/T computer). Once at the computer internal disks and memory are utilised for temporary data storage by software orchestrating transcription. Finally, data is archived onto hard disks and written to delivery media, completing the path of potential bottlenecks. For simplicity, Figure 1 shows only a single node connection but in practice this will be hundreds or even thousands of nodes simultaneously connected and being processed which further burdens the downstream network, D/T computer and storage devices.

Node data Seismic data is typically stored in the node in a proprietary native format and is recorded continuously during the time period. The node is programmed each day up to the full 24 hours per day. Shots are dispersed throughout the continuous recording based on the type of source production employed and rate of production. The volume of data contained in each node can be large depending on the acquisition parameters

Figure 1 Diagram of node data download and transcription path.

1

INOVA Geophysical, Inc.

*

Corresponding author, E-mail: Dennis.Pavel@inovageo.com

DOI: 10.3997/1365-2397.fb2026004

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and number of days recording prior to download. In high productivity vibroseis operations, sweep records can overlap, which means the volume of sweep data extracted is actually greater than the volume of continuous data. When multiplied by tens of thousands of nodes on a project the total amount of data that needs to be managed during download increases even more.

Network The configuration of a node download network is analogous to a client-server computer network. Each node connected to the network acts as a client and the D/T computer acts as a server. They communicate through a unique secure protocol whereby the D/T computer sends instructions to the nodes to execute certain tasks such as, download data, perform tests and program operational parameters, to name a few.

Like a computer network there are two primary considerations for node download networks: throughput and bandwidth. Throughput is the rate at which data can be transferred across the network while bandwidth is the maximum data capacity the network can support. Both are important in achieving overall efficiency.

Downland and Transcriptions (D/T) computer The D/T computer plays a pivotal role in the overall node download system and requires server class computing power. In addition, working disks and memory for data handling require fast read and write speeds to move data quickly during processing, formatting, sorting and other data transcription workflows.

Likewise, the software performing these tasks needs to be streamlined. Database schemes should be structured efficiently for rapid indexing required to generate data output in required arrangements and formats.

Output data storage and archive Separate from the D/T computer’s internal storage, the data management system includes additional storage for archiving project data and writing final data to media for delivery to the client. Project data can be archived on RAID arrays which are scalable to hundreds of terabytes storage capacity and can be daisy-chained to increase total archive capacity beyond a petabyte. These devices provide redundancy to protect against loss of valuable seismic data in the event of a hardware failure. Final data output is written to portable or removable high speed disk drives often in duplicate for further data redundancy.

Node download and charge capacity The quantity of node racks, or more specifically the quantity of node slots, used for data download and battery charging are an inherent part of the system efficiency discussion.

Adding additional slot capacity to the system increases the volume of nodes that can be processed at one time but also increases requirements on network bandwidth for data transfer.

Adding slot capacity has a greater impact on reducing overall battery charge time, since more nodes are charged concurrently.

The amount of time required to recharge batteries depends on 64

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how long the nodes have been in the field recording; that is, how much battery has been used.

Some nodes can record continuously for 50 days or more operating 24 hours per day on a single charge. While this is more runtime autonomy than is needed in typical field operations, it provides a benefit in the recharge process.

For example, since the typical deployment duration is much shorter than 50 days only a fraction of the available battery charge is consumed, allowing quicker recharge back to full capacity.

Determining the appropriate quantity of node slots for a download system on a given project requires an understanding of data volume, processing speeds and battery charge requirements as dictated by operational parameters and project time constraints.

Transcription process flows Once data has been downloaded from nodes and resides on the D/T computer or accessible disk storage data transcription can begin. A core function of transcription involves populating data trace headers with information unknown to the node when deployed in the field, such as source geometry and related detail as required for data format compliance. A comprehensive transcription system will go further by providing the user with several options for data output sorting and data format standards to meet contract requirements of clients and provide data sets suitable for on-project geophysical QC. The first step in the transcription process converts data from the node’s native format to a working format the transcription computer will use to generate data output required by the user.

The type of output determines what additional pre-processing steps need to be taken. For example, any output option that requires data sorted by source point requires extracting shot records from the node continuous data. Therefore, these processes require information related to the source point, such as the shot number, shot time, record length and other pertinent information. Once shot records are extracted further pre-processing may still be required. For example, in the case of vibroseis source, individual sweep records may require stacking and/or correlation with a pilot sweep. Depending on desired output, traces can be sorted by receiver point or by source point.

For microseismic or high productivity vibroseis applications data can be output in common time gathers or continuous receiver gathers. An advanced transcription system will have the capability to provide all these options.

Data output The end objective of the transcription process is to produce final data output delivered to the client as fast as possible in a prescribed format with records structured as defined by the seismic acquisition contract. Various types of data output sorting may be required.

Continuous receiver gathers Continuous receiver gathers are the simplest form of transcription data output requiring no pre-processing, no source information and minimal sorting. This option provides raw continuous data and is the default output for nodal systems. Precise recording time

SPECIAL TOPIC: LAND SEISMIC

Figure 2 Example continuous receiver gather (a) and common time gather (b).

Figure 3 Example receiver gather (a) and shot gather (b).

is provided in trace headers allowing later processing relative to source events. Figure 2a shows an example file output for a hypothetical receiver R1. The individual traces within each receiver output file, represented by R1T1, R1T2, R1T3 and so on, are contiguous. Events are spaced throughout the records based on the time they were acquired.

Common time gathers Common time gathers are like continuous receiver gathers in that this output also does not require source information or pre-processing. However, in this instance the emphasis is on a user-specified time segment of recording. Files are generated containing traces from all receivers during a specified period of time. Referring to Figure 2b, time segment T1 contains traces from all receivers, R1-R9, for this time period. Also, like continuous time receiver gathers, precise recording time is provided in trace headers for later processing relative to source events.

Receiver gathers Unlike the previous time-based output options, receiver gathers require source information to extract shot or sweep records from the continuous node data. In this instance, the output file contains shot traces for all source points associated with a common receiver. Figure 3a shows an example receiver gather output file with shot traces sorted by offset distance from a receiver that is nearest to source point S1.

Shot gathers Like receiver gathers, shot gathers also require source information to extract shot traces from each receiver. The output file contains

shot traces from all receivers associated with a common source point. The primary difference between a receiver gather and shot gather lies in the way the traces are sorted in the output file.

Figure 3b shows an example shot gather output file with receiver traces sorted by offset distance from a source point that is near receiver R1. A shot gather file will be incomplete until all nodes required in the gather file have been retrieved from the field.

Modelling the operation Estimating data download, battery recharge and transcription times can be performed based on project parameters, resource requirements and output data preferences. The flow chart in Figure 4 provides an overview of a method for estimating time to complete the operation.

Operational parameters define hours per day of recording, number of days in the field prior to download, type of source production and daily source productivity. Acquisition parameters include sample interval, vibroseis sweep record length and/or impulsive shot record length. Using these inputs, the total amount of shot data and continuous data contained in each node at the time of download can be calculated. Once the size of data in each node is determined and battery recharge time is calculated, assumptions are made for the number of node slots to be used in the analysis. Then benchmarked download speeds are applied to calculate download time for each batch of nodes. If the number of slot positions is less than the number of nodes being processed, the operation is repeated until all nodes are complete. Additionally, modelling of slot requirements is iterative to achieve completion within operational time constraints.

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correlation. Benchmark computational throughput speeds are applied to each selected step in the transcription process allowing estimation of the total data volume and time required. Now the data is ready for output to delivery disks in the specified format standard, SEGY or SEGD. Conclusion Download and transcription is a crucial element of a nodal acquisition system that demands attention to each step of the process to maximise efficiency. The platform needs to be flexible and encompass the ability to scale up to support different aspects of the seismic operation and data requirements. For example, the burden on the process changes depending on the stage of the seismic survey. Data volumes are likely smaller during receiver roll than at the end of a project when many more nodes require data management once the final source point is acquired and the full receiver patch is taken out of the field. Accordingly, the amount of time required to complete the process may be much shorter during receiver roll than at project roll off since nodes during receiver roll are required to be returned to the field quickly to keep pace with source production.

In both phases, time is of the essence for different reasons therefore the download and transcription operation must be designed from a holistic viewpoint to meet changing operational requirements and process time expectations.

With nodal systems, the node acquisition unit itself usually garners the most attention. That attention is justified for evaluating field operation relative to node characteristics. However, it is the system, particularly the download and transcription part of the system that also differentiates one nodal offering from another. It is just not as apparent until put into practice.

Figure 4 Data download and transcription modeling flowchart.

At this point all node data resides on the transcriber computer or accessible disk drive (actual download is complete) and transcription process steps are applied as required. This includes the type of data output sorting required, as described earlier. In the case of vibroseis source this could also include stacking and

Acknowledgements The author would like to acknowledge INOVA Geophysical for support in publishing this paper and the beneficial conversations with INOVA colleagues.

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Redefining transition-zone 3D seismic acquisition: Flexible land-nodal methods applied to the Kalundborg-Gassum CCS site, Denmark Piotr Potepa1*, Karim Souissi2, Manuel Beitz 2, Ewa Zubrzycka1 and Jerzy Trela1 describe how the challenges specific to the transition zone (TZ) in 3D seismic surveys can be overcome in a cost-effective manner by adapting land seismic equipment for use in marine conditions.

Abstract Equinor and its partners Ørsted and Nordsøfonden recently conducted the Kalundborg carbon capture and storage (CCS) 3D seismic survey, acquired by Geofizyka Toruń S.A. (GT), to evaluate the suitability of subsurface sites for CO2 storage in Denmark’s coastal transition zone.

This paper describes how challenges specific to transition zone (TZ) in 3D seismic surveys can be overcome in a cost-effective manner, by adapting land seismic equipment to marine conditions.

With a strong focus on compliance with environmental regulations, the project successfully delivered high-quality 3D seismic data by integrating land-nodal technology across both onshore and offshore settings. The innovative application of buoy-mounted nodes, combined with an adaptive acquisition design, enabled seamless data acquisition and processing while minimising operational complexity. This approach sets a new benchmark for transition-zone seismic surveys.

Introduction Seismic operations in transition zones and shallow water present unique challenges (Clark et al. 2025). The dual nature

of transition zones, which straddle both marine and terrestrial conditions, requires equipment and methodologies from both domains. In many cases, this is neither economically nor operationally efficient. Traditional marine methods, such as streamer vessels and ocean-bottom nodes (OBNs), are designed for use in deeper waters, whereas conventional land seismic systems cannot be used directly in shallow water. The lack of suitable technology has led to transition zones being overlooked in many projects, resulting in data gaps and compromised subsurface models.

For the Kalundborg CCS 3D seismic survey here presented, having both features of transition zone and shallow water (Figure 1), we developed an innovative solution by adapting wireless land seismic node technology for use in shallow water. These self-contained recording units are mounted on buoyancy systems with integrated hydrophones. The nodes operate independently, storing data locally and being powered by internal batteries.

By bridging the gap between land- and marine-based methods, this solution transforms one of the most challenging survey environments into a manageable and predictable part of seismic exploration.

Figure 1 Acquisition of seismic data by source vessel Hydrocat Tapper in typical transition zone conditions off Vesterlyng beach, west of Havnsø. Note the white floats approx. 20 m behind the vessel (red arrow) supporting the source arrays.

Photo credit: Wolfgang Kessler.

Figure 2 Location of the seismic survey area. The blue polygon delineates the receiver layout, the red polygon delineates the source layout, and the green polygon denotes licence block C2024/03.

1

Geofizyka Torun’ SA | 2 Equinor

*

Corresponding author, E-mail: piotr.potepa@GTservices.pl

DOI: 10.3997/1365-2397.fb2026005

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Figure 3 Simplified geologic cross section from Stenlille (Stenlille domal structure) across Havnsø (Havnsø domal structure) to Nekselø Island (Zappalá et al. 2024).

Survey objectives

The Kalundborg CCS 3D seismic survey is the initial phase of the CO2 Storage Kalundborg initiative supported by Equinor and its partners Ørsted and Nordsøfonden. The aim is characterisation of the key geological formations targeted for CO2 storage. This work contributes to Denmark’s broader strategy for carbon management and reduction through the development of a CO2 injection and storage facility.

The survey took place in northwestern Zealand (Sjælland in Danish), Denmark, within licence C2024/03, primarily covering the Kalundborg municipality. The receiver area covered approximately 225 km², including 171 km² onshore and 54 km² in the transition and shallow water zones of Nekselø Bay (Figure 2).

The main objective was the mapping and characterisation of the Havnsø structure, a four-way anticline formed by the halokinetic movement of Zechstein salt and subsequently uplifted during the Cenozoic period. The main reservoir extends from Upper Triassic to Lower Jurassic Gassum-Fjerritslev formations, and the Lower Triassic Bunter sandstone formation could be considered as a secondary reservoir (Figure 3). Since only sparse 2D seismic data was covering the area, this new 3D survey was essential for modelling the structure’s storage capacity, planning and positioning of future exploration and injection wells, as well as derisking the injection and storage process.

Survey framework The licence award in June 2024 included a commitment to Danish authorities to have processed data available by March 2026, thus requiring acquisition to be conducted in the first half of 2025.

However, as the survey area extended over marine protected and sensitive ecosystems, and with Equinor and partners strong focus on safety and environmental compliance, offshore data acquisition could only proceed during the period between early February and late April, outside nesting and feeding periods of marine fauna.

Beside the offshore part, the survey area covered a variety of terrains, including agricultural lands, urban settlements, lakes and shallow coastal waters with variable bathymetry. It presented the typical logistical and operational challenges associated with complex transition zone projects. Additionally, strict environmental regulations, distributed unevenly across the survey region and driven by the ecological characteristics of specific zones were thoroughly followed. For example, the coastal zone, being 68

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Figure 4 Environmental regulations in the work area. The blue polygon indicates the receiver area and the red polygon indicates the source area. Coloured areas: regions where seismic acquisition was either permanently restricted (red) or time/ technology-limited (other colours).

designated as a protected landscape, was entirely excluded from the survey (Figure 4).

Successfully navigating through these dynamic operational challenges and strictly complying with the environmental regulations meant that a highly adaptive and carefully sequenced acquisition plan was necessary. It demanded precise planning, operational flexibility, and close co-ordination with the permitting and land access consenting teams to ensure that all activities were completed on time, in full compliance with environmental requirements, and without compromising on safety or data quality.

Innovative and sustainable acquisition approach Equinor entrusted Geofizyka Toruń with the safe execution of the Kalundborg 3D survey to deliver a seismic solution that combined high data quality, operational flexibility and cost efficiency.

SPECIAL TOPIC: LAND SEISMIC

Survey design

The initial onshore design specified intervals of 300 m and 200 m between the source and receiver lines, respectively, and 20 m spacing for both the source points and receivers. This resulted in approximately 26,000 vibrator points (VPs) and 45,000 receiver positions on land.

As for the offshore configuration, the initial plan was to have 200-m receiver lines and 300-m receiver intervals, together with a very dense source grid of 20-m intervals between both points and lines. This would have resulted in more than 110,000 source points and around 860 receiver positions at sea (Table 1). Recording so many marine source points in approximately 10 weeks of acquisition – to comply with the environmental regulations – was deemed challenging given the operational limitations.

Therefore, for the sake of keeping up with the timeframe allowed for offshore acquisition, and to further adapt to the complex transition zone setting of the project, GT offered here a forward-thinking concept and a technically robust approach.

The configuration at sea was revised by adopting a carpet design, with the receivers arranged in a grid pattern at 160-m intervals. Source lines were spaced at 60-m intervals, with 20-m source point spacing. These modifications decreased the number of source points down to 38,000 approx. and thus saved time, but the number of receivers increased from 860 to about 2000. This was still operationally acceptable and allowed for effective quality control over all receivers while ensuring adequate space for passing vessels and reducing the risk of equipment damage. Despite these changes, the match between the offshore grid and the land geometry was maintained to

ensure consistency as land nodes were also recording marine source points and similarly marine nodes were recording VPs. The resulting preplots, presented on Figure 5 (left) were adapted throughout the acquisition to meet operational challenges and environmental regulations and led to postplots presented in Figure 5 (right).

Table 1 summarises the onshore and offshore survey design from the initial proposal to the actual postplots that were acquired.

Data acquisition

Offshore The seismic survey began with the offshore phase to ensure completion ahead of 1 May as required by the environmental regulations.

Before acquiring data, navigational warning buoys were used to mark the survey area, and a dedicated navigation corridor was established between the port of Havnsø and the islands of Nekselø and Sejerø to ensure the safe passage of vessels. Three smaller vessels were used to deploy the buoy-based receiver nodes. Where the water was too shallow for the source to be deployed, either the density of the receivers was increased in surrounding areas, or marsh phones were used to maintain data coverage.

Due to the variable bathymetry, two vessels of different sizes were used for the source operations: a larger 24h operational vessel for deeper waters and a smaller vessel for shallower zones for daylight only operations. Seismic energy was generated using two airgun arrays with volumes of 450 and 480 cubic inches,

Onshore

Offshore

Initial proposal

45,000 Receivers: 20 m x 200 26,000 Sources: 20 m x 300 m

860 Receivers: 300 m x 200 m 110,000 Sources: 20 m x 20 m

Preplot

45,000 Receivers: 20 m x 200 m 26,000 Sources: 20 m x 300 m

2,000 Receivers: 160 m x 160 m 38,000 Sources: 20 m x 60 m

Postplot

33,752 Receivers 23,957 Sources

1,842 Receivers 36,758 Sources

Table 1 Acquisition designs and their evolution for both offshore and onshore portions.

Figure 5 Survey geometry layout: theoretical preplot (left) versus after acquisition postplot (right). Sources are marked in red and receivers in blue.

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Figure 6 The Quantum® node on the buoys records its position continuously at least every 10 minutes. These co-ordinates (blue dots) were used to determine the COG (centre of gravity, black points) versus the buoy drop position (red points). The figure shows a good match between the COG and the dropped position.

respectively. Both arrays were operated at a depth of two metres and a working pressure of 2000 psi.

A total of 36,758 source points were acquired, including infill source lines around non-accessible areas such as Nekselø island, as if undershooting an obstruction, to maximise coverage on mid and far offsets. Data were recorded using 1842 buoy-mounted nodes. The offshore acquisition began on 7 March 2025 and was completed on 28 April 2025.

The key part of the offshore acquisition was the innovative use of onshore nodal systems for data recording across the entire survey area, including offshore. Specifically, the project utilised Quantum nodes from Inova, which were originally designed for land operations and were successfully adapted for deployment in marine conditions. The nodes were mounted on surface buoys, each of which was connected to a hydrophone that was lowered and laid on the seafloor. The buoys and hydrophones were stabilised using anchors.

The Quantum® nodes deployed on buoys were fitted with the HyperQ feature which was a key factor in the success of the offshore campaign. It enables the nodes to communicate wirelessly to a central location over a range of several kilometres and to provide regular operational status updates. This allowed the crew to continuously monitor node performance and respond quickly to any anomalies, significantly reducing the risk of data loss. As a result, the number of buoys lost throughout the entire offshore operation was only 4, which is a remarkably low number given the challenging marine environment.

The final positioning of the offshore receivers was determined using the internal Global Navigation Satellite System (GNSS) of each node. Geofizyka Toruń then used an in-house processing solution to clean and refine the raw positioning data, enabling the precise determination of the final centre of gravity (COG) coordinates for each receiver. This ensured that the recorded data was precisely spatially referenced, thereby contributing to the overall quality and consistency of the seismic dataset (Figure 6).

Onshore The onshore phase of the Kalundborg CCS 3D seismic survey required careful consideration of the staggered environmental regulations and constraints on land access. Protected areas were either excluded from the survey (Saltbæk Vig Lake, coastal zone, birds nesting locations, etc…) or had limited access (Nekselø Island, low lands, etc…) with only a limited number of source and receiver points deployed.

Furthermore, access to some private properties and farmland was not granted, which also shaped the final survey footprint.

Dynamic and real time adjustments of the receiver layout were made regularly to account for permitting conditions throughout the campaign. Using a nodal acquisition system was crucial to maintaining flexibility and enabling the team to adapt the grid as needed, especially to prioritise farmers to conduct agricultural work on their fields. Additional source and receiver points were included where necessary to maintain fold coverage in areas with restricted access.

Figure 7 Overview of seismic survey operations. Left side – onshore operations: a heavy vibrator operating in a field and a mini vibrator working along a coastal road in Havnsø. Right side – offshore operations: one of the source vessels and node on the buoy deployment process. In the middle – a node mounted on a buoy. Photo credit: Karim Souissi, Ionut Popa, Mariusz Wisnowski, Branislav Berger.

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Figure 8 Post acquisition fold map (left); black line corresponds to the seismic brute post-stack migration with elevation statics and residual static correction with post-stack processing (right).

Source point acquisition on land was carried out using the slip-sweep technique, with a standard configuration of one 60,000 lb vibrator and a 60-second sweep. Four heavy vibrators were used across most of the survey area, while two mini-vibrators were deployed in more sensitive locations, such as Nekselø island and the urban settlements of Havnsø and Jyderup. Traffic management measures and peak particle velocity (PPV) monitoring were employed to ensure operations were conducted safely and without any effects on local infrastructure.

To complement the land-based acquisition, buoy-mounted nodes were deployed on Skarresø Lake using a small electric-powered boat. A compact airgun array configured from two 40 cu.in units and towed by a customised rigid inflatable boat (RIB) was utilised as source. Compressed air on the RIB was supplied by a set of high-pressurised air bottles, pre-filled on the shore of the lake.

with limited access or heightened environmental sensitivity.

The robust design, adaptive planning and flexible deployment strategies enabled the project to achieve full coverage of the target area while being fully compliant with environmental regulations.

Using a homogeneous nodal recording system for the entire survey area, both onshore and offshore, enabled seamless dataset integration, QC and processing, significantly reducing logistical complexity, and allowing for on-demand and remote health monitoring of nodes without the requirement to pass each node separately. The quality of the seismic data acquired was consistently high in both land and marine environments (Figure 8) and exceeded expectations.

Consistency in acquisition geometry and equipment type minimised discrepancies between different survey segments, contributing to the clarity and reliability of the final seismic volumes.

Summary The acquisition campaign, which spanned from 7 March to 26 July 2025, delivered a comprehensive seismic dataset across both onshore and offshore areas. A total of 60,715 source points were recorded, including 36,758 offshore and 23,957 on land. Offshore operations accounted for over 60% of the total source points, with the majority executed in deep water. The combination of robust equipment and advanced QC functionality provided by HyperQ proved stable and reliable and was essential to the successful execution of the offshore phase. Onshore nearly 24% of the VPs were performed using mini-vibrators to ensure a minimum impact on infrastructure and surrounding nature. This proportion reflects the logistical complexity of the survey, particularly in areas

Acknowledgements The authors gratefully acknowledge Equinor and the partners for giving permission to publish this paper.

References Clark, A., Trela, J., Potepa, P., Ziółkowski, S. and Pavel, D. [2025].

Developments in nodal data acquisition in the transition zone and shallow water. First break, 40(1), 51-56.

Zappalá, S., Malehmir, A., Papadopoulou, M., Gregersen, U., Funck, T., Clausen, O. and Nørmark, E. [2024]. Case History, Combined onshore and offshore wide-scale seismic data acquisition and imaging for carbon capture and storage exploration in Havnsø. Denmark. Geophysics, 89(4), B257-B272, doi: 10.1190/GEO2023-0503.1.

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Forty years of deep geothermal experience in Switzerland: lessons learnt and looking forward Andrea Moscariello1* and Ladislaus Rybach2 present a regional exploration strategy needed to develop a viable geothermal industry and ensure successful pathways to unlock the full deep subsurface geothermal potential of Switzerland.

Abstract Switzerland benefits from strong social and political support for energy transition policies aimed at eliminating around 12 million tons of CO2 per year to achieve carbon neutrality by 2050. Geothermal energy is widely regarded by society and by both federal and cantonal authorities as a key contributor to this objective. While Switzerland is a global leader in the deployment of borehole heat pumps, significantly reducing fossil fuel use for heating in domestic, industrial, and agricultural sectors, efforts to exploit high-temperature rocks and fluids in the deep subsurface over the past three decades have delivered mixed results.

Outcomes from numerous deep wells drilled since 1988, including Reinach, St Moritz, Bulle, Weissbad, Thônex, Saillon, Yverdon, Basel, Triemli, St. Gallen, GEo-01, GEo-02, and more recent projects such as Lavey-les-Bains, Venzel/La Côte, and Yverdon II, show that deep geothermal potential has not yet been exploited as initially expected. Nevertheless, successes such as GEo-01 in the Geneva Basin and the repurposing of wells at Triemli, Weissbad, and Thônex demonstrate that geothermal resources exist and that giving initially disappointing wells a productive second life is a viable strategy.

This paper reviews four decades of deep geothermal projects in Switzerland and distills the main lessons learnt. Two key insights emerge: first, a viable geothermal industry requires a mature geo-energy exploration mindset supported by substantial upfront investment; second, the Swiss subsurface remains insufficiently understood, particularly regarding the controls on porosity and permeability at basin and reservoir scales. Addressing these gaps demands a co-ordinated regional exploration strategy rather than isolated, one-shot projects.

Introduction Geothermal energy represents one of the most promising renewable energy sources available today, offering a clean, reliable, and locally sourced solution to meet growing global energy demand.

The Earth’s internal heat is vast, widely distributed, and, in many regions, sufficiently accessible to support large-scale energy production. In sedimentary basins in particular, geothermal resources are relatively well understood due to decades of geological and geophysical exploration, often originally conducted

for hydrocarbon prospecting. The technologies required to access geothermal energy — especially deep drilling, well completion, and subsurface engineering — are mature and have been successfully applied in both the oil and gas industry and in conventional hydrothermal geothermal systems worldwide.

Thermal energy demand for space heating, cooling, industrial processes, and electricity generation remains high, and geothermal systems are well suited to address these needs in a sustainable and continuous manner. Unlike intermittent renewable sources, geothermal energy can provide baseload power and heat with a very small surface footprint and minimal emissions. For these reasons, geothermal energy has long been considered a cornerstone of long-term decarbonisation strategies.

Despite this strong scientific, technical, and economic rationale, the widespread deployment of deep geothermal energy in Switzerland and comparable regions remains limited. This situation raises a fundamental question: if the geothermal resource exists, the technology is proven, and the demand is urgent, why has deep geothermal energy not yet been successfully developed at scale? Addressing this paradox requires moving beyond purely geological or engineering considerations and examining a broader set of constraints, including regulatory frameworks, economic risks, institutional capacity, public acceptance, and governance structures.

In 2014, top management of the geothermal program at the Swiss Federal Office of Energy, stated in an interview with swissinfo.ch, after publication of a major assessment of Swiss geothermal potential (Hirschberg et al., 2015), that ‘we still have to learn how we will get to the heat deep below the surface’. More than a decade later, it is legitimate to ask whether the geothermal community has made sufficient progress to demonstrate its ability to reliably and safely extract deep geothermal heat in Switzerland.

This paper addresses the state of exploration, development, and progress of deep geothermal energy resources in Switzerland, focusing on systems deeper than approximately 700-1,000 m.

While Switzerland has achieved remarkable success in shallow geothermal applications — particularly ground-source heat pumps, with more than 350,000 installations by 2020 (approximately one unit per 25 inhabitants; FWS, 2025) — it remains true that no industrial-scale, commercially viable deep geothermal project for

1

GeoEnergy Group, University of Geneva | 2 Institut für Geophysik ETHZ

*

Corresponding author, E-mail: Andrea.Moscariello@unige.ch

DOI: 10.3997/1365-2397.fb2026006

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either heat supply or electricity generation has yet been fully realised within Swiss territory, despite several promising initiatives.

Geothermal energy in Switzerland The development of geothermal energy has long been recognised as a key pillar of Switzerland’s strategy to reduce greenhouse gas emissions and transition toward a carbon-neutral energy system (Rybach, 1992). This vision is embedded in the Swiss CO2 Law and national energy strategies (SFOE, 2020), which aim to reduce reliance on fossil fuels while promoting renewables, including geothermal energy. Within this framework, the Swiss Federal Office of Energy (SFOE) has implemented support mechanisms — most notably pilot and demonstration (P&D) projects — to promote geothermal exploration and development.

The P&D programme provides financial support for early-stage geothermal initiatives, subsidising feasibility studies, exploration drilling, and pilot installations to reduce investment risk in capital-intensive projects facing technical and economic uncertainty. While these subsidies have helped to sustain interest in geothermal energy, they have not been sufficient to overcome the substantial challenges confronting deep geothermal development.

The Swiss geothermal sector has faced a long and difficult path toward economically viable deep geothermal projects for both heat and electricity. Since the drilling of the Thônex well in Geneva in 1993, progress has been characterised by experimentation, isolated successes, and repeated setbacks. High-profile failures include the Basel EGS project (2006-2009), which was halted after induced seismicity culminated in a magnitude 3.5 earthquake (Häring et al., 2008; Mukuhira et al., 2013, 2015), and the St Gallen project (2012), which was abandoned after a similar seismic event (Diehl et al., 2017).

Other projects have highlighted different risks. At Schlattingen (2012), drilling unexpectedly encountered hydrocarbons, increasing costs and public concern (Frieg et al., 2015) and underscoring the importance of predicting subsurface fluid types.

The La Côte project sacrificed a promising shallow target in pursuit of deeper objectives, ultimately reducing project viability.

More recent projects, including Lavey-les-Bains and the Stoll projects in 2023, also failed to meet technical or economic expectations, further illustrating the complexity and risk of deep geothermal development in Switzerland (Géothermie-Suisse and Ruralis, 2024).

Success stories and adaptive reuse

Despite these challenges, the sector has demonstrated resilience.

The Riehen project in Canton Basel-Stadt stands out as a major success, with a deep geothermal doublet supplying district heating reliably for more than 30 years. Commissioned in the early 1990s, it exploits a deep aquifer at 1500-1600 m depth with temperatures of 65-70°C (Kaufmann, 2023). The system now also provides cooling and, since 1997, has supplied heat across the border to Lörrach (Germany), becoming the world’s first cross-border geothermal district heating network.

The Riehen project is notable not only for its technical success but also for its strong public acceptance, careful geological assessment, and absence of induced seismicity. The extension of the heating network across the Swiss-German border into Lörrach in 1997 made it the world’s first cross-border geothermal district heating system. Riehen stands as a reference case demonstrating that deep geothermal systems can be safely and effectively integrated into urban energy infrastructures.

Other positive examples include the adaptive reuse of underperforming geothermal wells. In Triemli (Zurich) and Thônex (Geneva), wells that failed to deliver sufficient flow rates for direct geothermal use were repurposed as borehole heat exchangers coupled with geothermal heat pump systems.

These systems now contribute meaningfully to low-temperature district heating networks. Such cases demonstrate that even when initial expectations are not met, geothermal investments can still provide long-term value through flexible system design and integration with other technologies.

What is holding back geothermal success?

One of the fundamental challenges facing deep geothermal development in Switzerland is limited knowledge of the deep subsurface. While Switzerland has an internationally respected tradition of surface geological mapping, it lacks a strong oil and gas industry that, in many countries, has driven deep exploration, data acquisition, and technological innovation. As a result, geological knowledge beyond a few hundred metres depth remains sparse, and the domestic service sector for deep subsurface projects is underdeveloped.

This knowledge gap has translated into higher uncertainty, increased costs, and elevated risk for geothermal developers.

However, significant progress has been made in recent years

Figure 1 Swiss Geothermal energy production present vs future in 2020 and 2050. (Source: GeothermieSuisse, 2023).

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Figure 2 Evolution of understanding of the structural framework of the Geneva Basin through time since 2014 and 2022. Despite the additional 2D seismic data over the years and their reinterpretation, the real game changer was the 3D data, which enables the identification of major structural features crossing the basin, which were identified earlier. These include the Rhone Fault (Moscarielo et al., 2024), one of the main targets for future geothermal exploration activities.

through the acquisition of high-resolution 3D reflection seismic data. Originally developed for hydrocarbon exploration, this technology has proven transformative for geothermal exploration by providing unprecedented insights into subsurface structural frameworks (Moscariello, 2024).

Understanding fault systems and fracture networks is particularly critical in Switzerland, where matrix porosity and permeability have been strongly reduced by diagenesis. Fluid flow in deep geothermal reservoirs is therefore controlled primarily by structural features. Past projects relying on legacy 2D seismic data often failed to capture this complexity, contributing to unsuccessful outcomes.

A striking example is the Geneva Basin, where almost 1200 km of 2D seismic profiles acquired since the 1960s failed to reveal major east-west trending faults (Figure 2). A recent 3D seismic survey fundamentally revised the geological model and identified structures now considered to be key geothermal fluid pathways (Moscariello et al., 2024). While seismic data cannot directly measure permeability, it remains the most effective tool for imaging reservoir heterogeneity compared to gravity, magnetic, electrical, or ambient noise methods.

In addition to geological uncertainty, deep geothermal development in Switzerland is hindered by fragmented regulations, underdeveloped legal frameworks, and limited experience within cantonal administrations. Harmonising and simplifying regulatory processes would significantly improve investment conditions and reduce project delays.

The high time of deep drilling in Switzerland Between 1988 and 1998, Switzerland experienced its most intensive period of deep geothermal drilling, largely due to the Swiss Geothermal Risk Coverage System (SGRCS). Inspired by the

success of geothermal district heating in the Paris Basin and the French risk insurance system established in 1982, Swiss authorities introduced a similar mechanism to mitigate drilling risk.

The SGRCS covered drilling projects deeper than 400 m and reimbursed up to 50% — and in some cases 80% — of drilling and testing costs. Approved by parliament in 1986 and implemented between 1988 and 1998, the system supported 13 drilling projects across 11 cantons. These projects yielded mixed results: five successes, one partial success, and seven failures.

Nevertheless, the program generated valuable technical, organisational, and procedural experience.

The Riehen project emerged as the flagship success of this period. However, once the SGRCS ended, drilling activity declined significantly. Subsequent wells, including Basel, Triemli, and St Gallen, failed to deliver expected results.

Under the Energy Strategy 2050, which entered into force in 2018, new funding instruments were introduced, including the P&D programme and the CO2 ordinance. Between 2018 and 2024, these mechanisms supported 14 projects with more than $250 million in total subsidies. While none of the drilled wells resulted in commercial geothermal discoveries, they significantly improved subsurface knowledge and data availability.

Lessons learnt from past geothermal development One of the most important lessons from deep geothermal development in Switzerland is the reluctance to fully adopt oil and gas (O&G) best practice in exploration and project design.

This hesitation stems partly from the absence of a strong domestic O&G sector and from cultural scepticism towards technologies associated with fossil fuels. The clean image of geothermal enerFIRST

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gy has sometimes encouraged the belief that it should follow a different, ‘softer’ development path. As a result, proven methods such as 3D seismic acquisition, basin modelling, and risk-based well planning have occasionally been sidelined, despite being essential for deep, structurally controlled geothermal resources.

A second lesson concerns the ‘one-shot’ approach of many early projects. Exploration permits were often granted to individual municipalities or utilities to pursue site-specific developments tailored to local needs. While this bottom-up model reflected strong initiative, it was frequently premature, with projects launched in areas of high subsurface uncertainty and limited regional understanding. Lacking sufficient data, guidance, and risk awareness, many of these pioneering efforts incurred high financial and reputational costs, leading to delays or failure.

Together, these lessons highlight the need to align geothermal development with established subsurface exploration practices and to adopt strategic, phased approaches based on regional or basin-scale resource assessments. The future of geothermal energy in Switzerland will depend not only on technical advances, but also on bridging idealism and realism through co-ordinated national strategies that support informed and lower-risk investment.

Understanding the subsurface

A key lesson from geothermal exploration is that the subsurface is complex and heterogeneous, and, needless to say, the functioning of deep geothermal reservoirs differ fundamentally from shallow subsurface systems feeding ground-sourced heat pumps. In regions such as the Swiss Plateau, geological evolution has produced low-permeability systems where fluid flow is controlled mainly by faults and fracture networks rather than primary porosity. Understanding the stress and strain state of these structures is therefore essential for identifying viable targets and ensuring safe development.

Managing this complexity requires integrated high-resolution 2D and 3D reflection seismic imaging, seismic monitoring, baseline geodetic data, and insights from neotectonics to track

subsurface stress and fault activity. In addition, multiscale laboratory experiments at sites such as Mt Terri, Grimsel, and Bedretto (e.g. Amann et al., 2018; Ziegler and Loew, 2019; Bröker et al., 2024) help to simulate deep conditions and characterise fractured rock behaviour. Although fractures dominate flow, matrix permeability can still contribute to reservoir performance and should be included in predictive models. Addressing this complexity is crucial to reducing exploration risk and improving deep geothermal success rates.

The need for a basin-scale approach

A basin-scale approach is fundamental to the successful development of deep geothermal energy. Relying on isolated or ‘spot’ projects in complex geological settings such as tectonically deformed sedimentary basins often results in fragmented efforts, inefficient resource use, and higher exploration risk. A strategic exploration block approach — similar to that used in the oil and gas industry (about 200-250 km² per block size) — should therefore be adopted, as it enables broader geological understanding, improved data integration, and better optimisation of drilling targets.

In addition, a basin-wide framework fosters collaboration and synergies among operators, investors, and public authorities.

Shared infrastructure, data, and risk-management strategies reduce costs and enhance investment attractiveness. Ultimately, moving from isolated pilot projects to a co-ordinated, multi-stakeholder basin strategy is essential to unlocking the full potential of deep geothermal energy.

Maintaining momentum through public support

Maintaining momentum in deep geothermal development requires consistent federal support. Public funding is crucial to derisk projects that would otherwise be too financially uncertain. The P&D Programme covered up to 40% of non-amortisable additional costs beyond conventional energy systems, including development, construction, operation, monitoring, and communication.

Figure 3 Overview of past and publicly announced future deep geothermal projects in Switzerland.

Symbols indicate purpose and depth of the well (original data modified from Link et al., 2025).

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Open to companies, universities, public institutions, and utilities, and free of duration or budget limits, it was a key instrument for innovation and risk sharing. In parallel, the CO2 Ordinance, effective since 1 January, 2018, allows reimbursement of up to 60% of exploration and prospection costs, including surface data acquisition, drilling, and well testing — high-risk but essential activities for deep geothermal advancement.

The recent discontinuation of the P&D programme therefore represents a major setback, weakening the momentum that had begun to build among industrial stakeholders and public utilities.

To sustain and accelerate progress, Switzerland must renew or replace these supportive funding mechanisms.

Data accessibility and transparency

A major barrier to advancing deep geothermal energy in Switzerland is the limited and fragmented access to subsurface data.

Despite decades of research and drilling, much information remains siloed or inconsistently shared, particularly among smaller actors, hindering collective subsurface understanding and increasing project risk.

Encouraging progress has been made in recent years. Swisstopo has improved the collection and organisation of subsurface data from recent wells (e.g. Boulicault et al., 2017), representing an important step that should be sustained and expanded. In parallel, Géothermie-Suisse has fostered knowledge exchange through its ‘retour d’expérience’ and ‘lessons learnt’ initiatives (e.g. Géothermie Suisse and Ruralis, 2024), creating a valuable repository of practical insights from past and ongoing projects.

As aptly stated by a former director of the Norwegian Petroleum Directorate, ‘Data have no value per se; their interpretation does’. Without accessible, interpretable data, progress in understanding complex geological systems — and in developing reliable geothermal energy — remains limited. Greater collaboration, data centralisation, and openness are therefore essential for the sector’s future success.

Managing ambition and phasing projects

A key lesson from past geothermal developments in Switzerland is the risk of launching overly ambitious projects when subsurface knowledge and local experience in complex drilling and reservoir management remain limited. The failures of major projects such as Basel (2009) and St. Gallen (2013) highlight the consequences of proceeding without sufficient geological understanding, technical preparation, and risk mitigation (Wiemer et al., 2017; Heuberger et al., 2016).

The ongoing Haute-Sorne project provides a more realistic model. Although technically advanced, aiming at electricity production through two deviated low-angle wells in the Jura basement, it is being implemented stepwise. Despite delays and local opposition, this phased approach enables the integration of lessons from earlier stages, particularly pilot wells, and progressively reduces subsurface and operational risks. The same approach has been implemented by SIG in the canton of Geneva since 2014.

The conclusion is clear: ambitious geothermal projects are feasible only when operators are scientifically, technically, and financially prepared. A staged, data-driven strategy supported by

P&D activities and the ability to rapidly implement alternative plans, such as side-tracking toward more favourable reservoirs identified by downhole seismic imaging, can significantly improve success rates and limit costly failures.

Education and capacity building

A sustainable geothermal future depends on educating and training the next generation of engineers and geoscientists.

Despite growing demand, Switzerland lacks a dedicated university-level curriculum covering the full geo-energy spectrum, including geothermal energy, CO2 storage, hydrogen storage, and hydrocarbons. Most institutions, such as ETH Zurich, EPFL, and cantonal universities, address these topics only marginally within general Earth Sciences programs, which is insufficient to build a skilled, multidisciplinary workforce.

Notable exceptions include the long-standing MSc in Hydrogeology and Geothermics at the University of Neuchâtel and the CAS in Deep Geothermal Systems, which provide strong foundations for professional practice. The ELSTE joint MSc program (Universities of Geneva and Lausanne) further advances education through its Earth Resources track, integrating geothermal energy with broader geo-resource, economic, and policy perspectives. Expanding such targeted educational pathways is essential for developing the expertise needed to drive Switzerland’s energy transition.

Stakeholder engagement

Successful geothermal projects depend not only on technical excellence but also on early and proactive stakeholder engagement (Ejderyan et al., 2019; Cousse et al., 2021). Public perception, education, and social acceptance often determine whether projects advance smoothly or face delays and opposition.

Given the inherent uncertainties of geothermal exploration, particularly subsurface risks, stakeholders must be well informed (Cousse et al., 2024). Clear communication about exploration activities, potential environmental impacts, and risk-mitigation measures builds trust and credibility with local communities, public institutions, and political actors. Educating the public and decision-makers on geothermal benefits, technical choices, and economic and environmental trade-offs fosters a supportive environment. Early engagement enables more inclusive decision-making and leads to more robust and resilient project outcomes, making stakeholder management a strategic necessity.

Structural and economic challenges Deep geothermal deployment faces intertwined structural, technical, and economic challenges that demand coordinated policy, innovation, and financing. A major barrier is the high upfront cost of deep exploration and drilling. Unlike shallow heat pumps, deep projects are capital-intensive and often seen as feasible only for large, well-funded actors, limiting competition and slowing innovation.

Progress depends on stronger knowledge transfer from the hydrocarbon sector, which offers proven expertise in subsurface exploration, well design, and risk management. Yet institutional and cultural divides continue to hinder this transfer. Cost-effective exploration methods are also a priority (Guglielmetti et al., 2021).

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Although programs such as SCCER and SWEET have advanced research (Giardini et al., 2021a, 2021b), sustained effort is needed beyond these frameworks, particularly in high-resolution geophysical imaging (especially seismic), predictive geological modelling, and adaptive drilling to improve well success rates.

Human capacity is another bottleneck, with shortages in subsurface geology, reservoir engineering, and HSE expertise.

Building competence will require targeted investment in university education and vocational training. Regulatory and institutional reforms are equally important: rights are typically granted wellby-well or commune-by-commune rather than by basin or block, fragmenting exploration and creating uneven timelines. Better alignment across federal, cantonal, and communal governance would increase predictability for investors.

Limited competition further slows development, while grants remain uneven across cantons and often insufficient to de-risk early stages. Finally, banks and insurers are reluctant to support exploration due to high geological uncertainty and long payback times (Schultz et al., 2010), creating a funding gap that only strong public backing or major energy companies can bridge. Overcoming these barriers is essential to unlocking Switzerland’s deep geothermal potential and scale this low-carbon energy source.

and safely operating the geothermal systems of the future — making them key actors in driving the energy transition forward.

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Novel Approach for the Exploration of the Muschelkalk Aquifer in Switzerland for the CO2-free Production of Vegetables. World Geothermal Congress 2015, Proceedings, 10 pp.

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Conclusion We are living in a pivotal and exciting era where society, policymakers, geopolitical forces, and economic models are being compelled to realign with the limits and dynamics of natural systems — particularly in the context of climate change and resource sustainability. In this transformative landscape, geothermal energy emerges not just as an alternative, but as a vital component of the energy transition solution.

In its ability to provide baseload, low-emission, locally sourced energy positions, it is a reliable and scalable tool in the urgent pursuit of decarbonisation. As the world grapples with complex challenges, geothermal energy stands ready to play a central role in reshaping how we generate and consume energy sustainably and responsibly.

The development of deep geothermal energy in Switzerland is progressing steadily and holds great promise, but it clearly needs a strong acceleration to meet national energy and climate goals.

Unlocking its full potential will require not only sustained investment and supportive policies but also bold strategic coordination across stakeholders.

The financial risk associated with project failure is a critical barrier when expected geothermal resources are not found. The lack of successful examples so far makes investment less attractive, prompting discussions around potential solutions like risk guarantee schemes or diversified project portfolios. To advance the sector, effective communication and public engagement are essential to maintain trust and interest. Additionally, strengthening experience sharing and offering continued education will be vital to building domestic expertise and ensuring the long-term growth of deep geothermal energy in Switzerland.

As we shift away from fossil fuels, geoscientists and engineers will once again play a critical role in shaping the energy landscape, just as they did during the oil and gas era over the past century. Their expertise will be vital in designing, developing, 78

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Rybach, L. [1992]. Geothermal potential of the Swiss Molasse Basin Eclogae Geol. Helv. 85/3, 733-744.

SFOE. [2020]. Energieperspektiven 2050+ Swiss Federal Office of Energy, Bern. https://www.bfe.admin.ch/bfe/de/home/politik/energieperspektiven-2050-plus.html Wiemer, S., Tormann, T., Herrmann, M., Karvounis, D., Kraft, T. and Marti, M. [2017]. Induzierte Erdbeben im Nachgang des eingestellten Geothermieprojekts in Basel. Schweizerischer Erdbebendienst (SED) an der ETH Zürich, 12 pp.

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Bridging acquisition and processing: A practical data-driven approach Nabil Khadiri Yazami1*, Van Chuong Do1, Guillaume Friess2 and Stéphane Laroche2 present an efficient and low-impact methodology that delivers data-driven diagnostics to inform both ongoing and future acquisition and imaging strategies.

Introduction A successful implementation of seismic technologies critically depends on the optimal integration of both mature and emerging technologies in acquisition systems, instrumentation, and imaging methodologies. From an acquisition standpoint, the primary objective is to maximise the informational content of the recorded wavefield by enhancing data quality, increasing signal-to-noise ratios, and accurately capturing the near-surface and subsurface responses of the Earth.

Effective collaboration between acquisition and imaging experts requires a robust data framework to support quantitative analysis and methodological feedback. Ongoing seismic operations provide a valuable context for the acquisition of experimental datasets, provided that such investigations have a negligible impact on production activities. This is typically achieved by temporally constraining test scopes and relying exclusively on existing equipment. To enable this, we have developed an efficient and low-impact methodology that delivers data-driven diagnostics to inform both ongoing and future acquisition and imaging strategies. This approach involves continuously recording repeated shots from a fixed source position across the full active spread, while temporarily suspending all other field operations. This configuration isolates the environmental and subsurface responses, minimising operational interference and enabling a controlled assessment of acquisition performance.

The simplicity, flexibility, and operational compatibility of this procedure allow tests to be implemented at virtually any stage of a seismic survey, regardless of scale or configuration.

The resulting experimental datasets provide a rigorous empirical basis for investigating a broad range of acquisition-related questions, including sensor coupling and deployment geometry, source strength and stability, phase and amplitude fidelity, near surface-induced distortions, data robustness in the event of seismic disturbance such as earthquakes, simultaneous-source acquisition feasibility, and the design and validation of source-encoding schemes.

Field experiments The experimental dataset analysed in this study was acquired over an operational 3D receiver spread consisting of 56 active receiver

lines, each 23.6 km in length and spaced 100 m apart (Figure 1).

Receiver stations were deployed at 25 m intervals along each line and instrumented with an array of nine 10-Hz geophones (three connected in parallel and three connected in series). For comparative analysis, 16 single-sensor micro-electro-mechanical systems (MEMS) units were deployed along 16 of the receiver lines, each colocated at the barycentre of a geophone array and spaced 100 m apart.

The source consisted of a single 60,000 lb seismic vibrator operating with a customised low-frequency control system. A 12 s force-pilot sweep was employed, covering a frequency bandwidth of 1.5-96 Hz with a flat amplitude spectrum. A low-frequency harmonic distortion reduction algorithm was used to generate a more stable and precise ground force.

A series of repeated sweeps was conducted at a fixed source location. The time interval between successive vibrations was sufficient to avoid residual ground motion interference from previous shots. The sweep repetition strategy was designed to (1) evaluate the accuracy and repeatability of the ground-force signal, (2) identify the record exhibiting the lowest ambient noise level across the active spread for subsequent quantitative analysis, and (3) diversity-stack all repeated records into a single common-shot gather (CSG) with enhanced signal-to-noise ratio, suitable for simultaneous-source simulations.

The complete experiment was executed within approximately three hours. During this period, all production shots and ancillary

Figure 1 The light-green horizontal lines correspond to the production spread. The red vertical lines correspond to the production sources. The red circles correspond to the repeated source test positions. The dark-green line corresponds to the positions of the MEMS sensors.

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Saudi Aramco | 2 Sercel

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Corresponding author, E-mail: nabil.khadiriyazami@aramco.com

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field operations across the spread were temporarily suspended to minimise operational interference and ensure data integrity.

Native data to physical unit conversion The native field data are recorded in volts for geophone sensors and in pseudo volts for MEMS sensors (Tellier, 2019). To enable a meaningful comparison between datasets acquired using two sensor technologies, arrays of nine planted 10-Hz geophones and a single MEMS node placed on the ground (neither planted nor buried), a conversion is necessary. This step involves converting respective native units to physical quantities such as particle velocity (m·s-¹) or displacement (m). Moreover, a correction must be applied to account for the frequency-dependent response of the geophones. This pre-processing step has become a prerequisite in the context of full waveform inversion (FWI), which requires both modelled and recorded data to be expressed in consistent physical units. The data correction process is deterministic, being derived directly from the analytical relationships between ground motion and sensor output.

For the geophone, the relationship between the frequencyand the ground particle velocity dependent native data reads:

With its sensitivity

stacking and migration. They can also be further attenuated through signal processing techniques designed to remove spatially uncorrelated noise. To compensate for the absence of array-based spatial filtering, it is generally recommended to increase the trace density by increasing receiver and/or source density (carpet shooting concept). The major conclusion drawn from this result is that the seismic signal provided by the acquisition to processing is invariant for the geophone and MEMS sensor.

To go one step further, we also compared the uncorrelated displacement recorded by a geophone array and a single node placed near the vibrators. In this case, the two were not co-located at the array barycentre, but instead positioned at the geophone closest to the source. The purpose of deploying the node near the vibrator was to observe how the low-dwell portion of the

being the geophone response characterised by , resonant frequency and damping factor

For the MEMS, the relationship between the frequency-dependand the ground particle acceleration ent native data reads:

With

being the volt-equivalent sensitivity.

The particle motion expressed in acceleration, velocity or is related according to: displacement

The MEMS nodes were co-located at the barycentre of each geophone array over 16 aligned cross-line positions (one per receiver line with 100 m spacing between lines). Figure 2 compares the single MEMS data (expressed in m·s-¹) with the geophone array data after vibrator pilot correlation. In Figure 2c, it can be seen that only the unfiltered random noise and air wave (f > 8 Hz) in the MEMS data are visible. The absence of coherent seismic energy in the difference sections validates the correct application of the geophone’s inverse and integration (acceleration to velocity domain) filters on the MEMS data. The only remaining differences are attributable to the well-known short-wavelength filtering effect of the field array. The trace-to-trace uncorrelated residuals are naturally removed during stacking processes such as normal move-out 80

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Figure 2 Comparison of the particle velocity field (m·s-¹) across 16 sensing positions spaced 100 m apart, for both full-band and sub-band frequency ranges: (a) array of nine planted geophones, (b) single ground-laid MEMS sensor, (c) difference between (b) and (a).

SPECIAL TOPIC: LAND SEISMIC

Figure 3 Comparison of the ground force (black curve) with displacements (m) measured by the nearest single MEMS sensor (green curve) and by the geophone array (red curve). A near-perfect correspondence is observed between the displacements recorded by both sensing systems, each accurately reproducing the low dwell-time frequency sweep emitted by the vibrator.

Figure 4 Band-pass filtered CSG along a receiver inline. The wavefield complexity induced by the near-surface signature is illustrated by the presence of multimodal dispersive surface waves and guided refractions.

sweep was recorded by both instruments. Figure 3 shows the relative positions of the geophone array and the MEMS node with respect to the source. A near-perfect phase match can be observed between the array and the single sensor. Both sensors capture the same instantaneous frequency as the ground force.

This illustrates the signal equivalence between the geophone array and the ground-laid MEMS sensor for both near-field and far-field measurements.

Near-surface signature The effect of the near surface in land seismic is often compared to condensation on a window: although only a thin layer, it can significantly blur the image of what lies behind. Here, we confirm that this analogy holds true. The (x,t) and (f,k) representations of a common shot gather (Figure 4) illustrate how a three-layer near-surface structure with strong velocity contrasts gives rise to complex, multimodal surface waves as well as guided dispersive head waves. These patterns are accurately captured and can be used as input for the simultaneous inversion of both wave types to build a multi-layer near-surface velocity model.

The guided waves formed between the free surface and the high-velocity layer generates multiple reverberations that act as a dephasing and modulation filter on the low-frequency components of the propagating waves, as shown in Figure 5. This observation calls for a proper deconvolution for near-surface effects. At frequencies below 8 Hz, one can clearly observe how backscattering inside the direct ground roll cone masks the

Figure 5 Illustration of the amplitude frequency filtering induced by the near surface.

underlying reflections. The removal of the back scatter apex is best addressed with a multi-azimuth high-density acquisition FIRST

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geometry which will allow processing to stack out the erratic time of the back scattering while stacking in phase the subsurface-reflected signal. Among all acquisition options, trace density has to be preferred to source intensity.

Active low-frequency emission The instantaneous force generated by a vibroseis source is frequency-dependent. It starts low at low frequencies, and progressively increases at higher frequencies to reach a maximum peak force. This yields low amplitude output for the low frequency if a constant sweep rate is applied. To compensate for this behaviour, the sweep rate of the pilot can be adjusted according to the vibroseis source’s mechanic and hydraulic characteristics as detailed in Tellier et al. (2014). Consequently, a longer emission time is allocated to low frequencies compared to higher frequencies.

Following this approach, we can demonstrate the generation of energetic low-frequency seismic waves across the entire active spread, characterised by a high signal-to-noise ratio (SNR). This is illustrated in Figure 6, which presents for five frequencies an overlay of the amplitude and phase rings of the recorded temporal data comprised between 5 s and 7 s after correlation with the pilot sweep. The results highlight the

Figure 6 Overlay of amplitude and phase rings for five frequencies over a (5-7s) time window.

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Figure 7 (f, k x, k y) amplitude spectra over frequencies 1,4,6,10,20Hz. .

spatial radiation of a powerful direct surface-wave wavefront, exhibiting comparable amplitudes at 2 Hz and 8 Hz, thereby confirming the source’s effectiveness in generating strong low-frequency energy. The superposition of phase and amplitude rings makes it possible to correlate the amplitude of the various surface-wave modes with their apparent wavelengths which relate to their apparent slowness. The direct ground roll propagates coherently along well-defined rings, followed by a random but still energetic backscattered wavefield. The phase rings associated with the rapidly propagating first arrival head waves also display strong coherence, indicative of a high SNR. The amplitude spectrum derived from the phase rings displayed in Figure 7 further corroborates these observations.

It reveals distinct outer circles corresponding to high-SNR surface waves and inner circles associated with the refracted wavefield, thereby providing additional evidence of the vibroseis source’s high efficiency in generating coherent broadband seismic energy.

Simulation of blended acquisition.

To simulate a blended acquisition continuously recorded on a common receiver gather (CRG) with the receiver located at the source position, we applied the reciprocity principle (Source, Receiver) = (Receiver, Source). This approach allows us to interpret a common shot gather (CSG) with a single source and multiple receivers as a CRG recording wavefield generated by multiple shot positions. To reproduce a specific source blending scenario, we generated a long continuous record by summing the unitary traces corresponding to the reciprocal shots, each delayed by a chosen time shift. To minimise the impact of environmental noise, repeated shots at the same position were diversity-stacked and subsequently filtered in the FX domain using the Cadzow algorithm (Trickett, S., 2002, 2003).

The three-step process is illustrated in Figure 8. The main advantage of this physical blending simulation, compared to numerical wave-equation modelling, is that it naturally incorporates real ground conditions, including all the complexities of the near surface. This method is easy to perform, requires minimal time, and can be applied in any

SPECIAL TOPIC: LAND SEISMIC

Figure 9 (x,t) and (Log(f), k) of an inline receiver section: velocity (m.s-1, after deconvolution of the geophone response), displacement (time integrated velocity).

Figure 8 a) CRG derived from field CSG using reciprocity principles. Processing applied: Diversity stack of the 36 shots followed by an FX Cadzow filtering; b) blended continuous record derived from the stack of the individual traces with a delay according to the simultaneous shot scenario. CRG (x, y) RMS amplitude maps over (0-7s) c) before blending d) after a given blending scenario e) after deblending.

situation where an active recording spread is available. The results of this simulation enabled the application of an inversion-based deblending for various simultaneous-source scenarios, providing valuable insights into both acquisition-time efficiency and deblending performance (Guillouet et al., 2016).

Passive seismic Seismic records in the production area are often affected by earthquakes, which manifest as low temporal frequency and low spatial wavenumber waves. These events are clearly visible in the low-frequency region of the spectra of CSGs, or when converted to displacement in the (x,t) domain (Figure 9), the preferred format for vibroseis data processing.

Historically, shot records contaminated by earthquakes had to be reacquired. This required continuous monitoring of seismic activity and real-time communication with the vibrator fleets to halt operations and repeat the shot, a procedure that inevitably impacts productivity. This approach is applicable to both cablebased and nodal acquisition systems.

During our repeat-shot tests, some shots were contaminated by an earthquake. This provided an opportunity to evaluate whether the active seismic signal could be preserved while strong seismological waves crossed the spread. It was verified that the direct difference between an uncontaminated shot and a

Figure 10 a) CSG before earthquake, b) repeated CSG during earthquake and c) difference.

contaminated shot contained no residual source imprint, leaving only the earthquake records, as if no active seismic source had been activated (Figure 10).

From there, we evaluated the possibility of separating the active and passive wavefield components. Earthquakes are characterised by very long correlation lengths along both the in-line and cross-line directions of the recording spread. This property makes Cadzow-type filtering highly effective (Trickett, S., 2002,2003). Its application on uncorrelated continuous records proved to be particularly advantageous for two reasons: it avoids edge effects associated with data chunking, and it allows greater amplitude focusing on the earthquake signal. These observations indicate that continuous recording mode enables the recovery of active seismic data without the need to re-shoot shots contaminated by earthquakes.

An additional benefit of delivering uncorrelated, continuous field data is illustrated in Figure 11, which presents the recording of very low-frequency surface waves from natural seismicity. These signals provide valuable information for near-surface to deeper characterisation. The integration of passive and active seismic responses, Figure 12, enables the inversion of seismic data across an extended range of temporal frequencies, thereby enhancing the resolution and accuracy of subsurface models.

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Figure 11 Passive seismicity and earthquake (0.3Hz < f < 0.6Hz). a), b) time slices of ocean wave seismicity, c) associated (f, kx , ky) spectra; d), e) time slices at earthquake time.

Conclusion This study demonstrates the efficacy of a practical, data-driven methodology designed to enhance the integration between seismic acquisition and imaging disciplines. By employing continuous recording of uncorrelated, time-separated repeated shots, we demonstrate that signals acquired from both conventional geophone arrays and ground-laid single MEMS sensors exhibit comparable fidelity and coherence across near- and far-field domains.

The implementation of continuous recording facilitates the robust discrimination between active seismic signals and naturally occurring earthquakes, thereby obviating the need for redundant shot repetitions during seismological events. The high-quality near-surface signature from active seismic and passive ocean wave interferometry captures a complete broadband suite of wave types, enabling inversion for a multilayer near-surface model. Additionally, the quantified backscattering level provides an effective indicator of the trace density required for optimal stacking and coherent noise suppression.

This approach further supports the construction of CRGs for any source code and distance-time activation criteria, to identify the acquisition strategy that minimises residual deblending noise while maximising operational efficiency.

Overall, this operationally flexible and low-impact framework is applicable across multiple stages of seismic surveys and provides a robust foundation for the optimisation of future acquisition and imaging workflows. The findings establish a clear link between acquisition and imaging processes, underscoring the critical role of data-driven methodologies in addressing contemporary challenges in land seismic exploration.

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Figure 12 Simultaneous passive and active interferometry for an extended broadband subsurface characterisation.

Acknowledgements The authors acknowledge Stéphane Baris, Raphael Bouvet, Philippe Feugère, Hugo Gomez Ochoa and Philippe Herrmann from Sercel for their contribution to the experiment and for their support during the preparation of this manuscript.

References Bardainne, T. [2018]. Joint inversion of refracted P-waves, surface waves and reflectivity. 80th EAGE Annual Conference & Exhibition, Extended Abstracts.

Boucard, D. and Ollivrin, G. [2010]. Development in vibrator control.

Geophysical Prospecting, 58, 3-40.

Guillouet, M., Berthaud, A., Bianchi, T., Pignot, G., Mahrooqi, S. and Shorter, J. [2016]. Recovery of blended data: a sparse coding approach for seismic acquisition. 78th EAGE Annual Conference & Exhibition, Extended Abstracts.

Ollivrin, G. and Tellier, N. [2019]. SmartLF for robust and straightforward reduction of low-frequency distortion. 89th SEG Annual Meeting, Expanded Abstracts.

Tellier, N. and Lainé, J. [2017]. Understanding MEMS-based digital seismic sensors. First Break, 35(1), 93-100.

Tellier, N.,Ollivrin, G. and Boucard, D. [2014]. Optimising the Generation and QC of Low-Dwell Sweeps. 76th EAGE Annual Conference & Exhibition, Extended Abstracts.

Trickett, S. [2002]. F-x eigenimage noise suppression. 72nd SEG Annual International Meeting, Expanded Abstracts, 2166–2169.

Trickett, S. [2003]. F-xy eigenimage noise suppression. Geophysics, 68, 751–759.

SPECIAL TOPIC: LAND SEISMIC

Enhanced seismic imaging in the Midland Basin with multiparameter full-waveform inversion James Sheng1*, Guanghui Huang1, Terence Krishnasamy1, Andrew Peterson1, Jaime Ramos-Martínez1 and Carlos Calderón-Macías1 introduce a multiparameter full-waveform inversion (FWI) approach for land seismic imaging that jointly estimates subsurface velocity and reflectivity.

Abstract We introduce a multiparameter full-waveform inversion (FWI) approach for land seismic imaging that jointly estimates subsurface velocity and reflectivity. The method employs a scale-separation strategy to recover background velocity and high-resolution reflectivity, extending imaging beyond the depth limits of head and diving waves. To enhance robustness against noise and low-frequency limitations, we incorporate a dynamic matching objective function that aligns observed and modelled phases through multidimensional correlation, reducing sensitivity to amplitude mismatches and low signal-to-noise ratios. The reflectivity kernel further improves high-wavenumber content, delivering superior resolution and structural coherence compared to conventional imaging. Application to a Midland Basin land dataset demonstrates the method’s potential for high-resolution imaging in complex geological settings.

Introduction Full-waveform inversion (FWI) has become a powerful tool for high-resolution subsurface imaging, but its application in land environments remains challenging compared to marine settings.

Key difficulties include low signal-to-noise ratios (SNR) at low frequencies, uncertainties in source wavelet estimation, and the strong influence of surface topography. For shallow imaging, limited near-offset coverage and complex near-surface geology often obscure primary reflections required by conventional seismic imaging approaches (e.g., Reta-Tang et al., 2023).

To overcome these limitations, leveraging the full wavefield, including refracted and multi-scattered energy, can improve subsurface illumination and velocity model building. Refracted waves provide essential constraints for velocity estimation, but their penetration depth is restricted by acquisition geometry. Beyond this limit, or in zones of velocity reversal, reflected energy becomes the primary source of information for updating the velocity model.

In this work, we present a multiparameter FWI (MP-FWI) approach that jointly estimates P-wave velocity and reflectivity, addressing several of the challenges outlined above. This methodology was first introduced for acoustic media by Yang et al. (2021) and later extended to elastic cases by Huang et al. (2025). Here, we adopt the acoustic implementation and combine it with the

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TGS

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Corresponding author, E-mail: james.sheng@tgs.com

dynamic matching (DM) objective function (Huang et al., 2021) to enhance robustness against noise and amplitude mismatches. We describe the method and demonstrate its effectiveness using a land seismic dataset from the Midland Basin, targeting formations such as the Barnett Shale and Mississippi Limes.

MP-FWI for P-Wave velocity and reflectivity Our multiparameter full-waveform inversion (MP-FWI) implementation jointly estimates P-wave velocity and reflectivity through two key components: (i) a wave-equation parameterisation in terms of P-wave velocity and reflectivity, and (ii) a scale-separation algorithm applied to the FWI gradient to minimise crosstalk between these parameters.

Using reflectivity in the acoustic wave-equation parameterisation eliminates the need to estimate density for synthesizing reflected events, which is advantageous given the difficulty of recovering density from surface seismic data. This formulation also enables simulation of the full acoustic wavefield from a single equation, unlike Born-based implementations. Consequently, multi-scattering, free-surface multiples, and refracted arrivals are naturally incorporated into the inversion (Whitmore et al., 2020).

The scale-separation strategy, grounded in inverse scattering theory, decomposes the FWI gradient into two sensitivity kernels: a long-wavelength kernel for velocity updates (Ramos-Martinez et al., 2016) and a high-wavenumber kernel for reflectivity updates (Whitmore and Crawley, 2012). This decomposition improves robustness and effectiveness when jointly inverting for velocity and reflectivity.

Although recent land surveys have adopted longer offsets (e.g., Kumar et al., 2025), they remain shorter than those in ocean-bottom node (OBN) acquisitions, limiting refracted-wave penetration depth. Beyond this depth, velocity updates rely primarily on reflected energy, with the sensitivity kernel used by our MP-FWI approach, emphasising background velocity adjustments. For shallow targets, this velocity kernel mitigates high-wavenumber leakage in velocity updates caused by reflection interference.

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Parameter

Value

Nominal shot-line interval

202 m

Nominal receiver-line interval

202 m

Nominal shot interval

25 m

Nominal receiver interval

50 m

Patch size

240 × 16 channels

Maximum nominal offset

8000 m

Table 1 Acquisition parameters for the study area.

To enhance low-frequency velocity estimation, we incorporate the dynamic matching (DM) objective function. DM-FWI uses multidimensional cross-correlation to quantify time-dependent mismatches between observed and synthetic data (Mao et al., 2020; Huang et al., 2023). By maximising phase alignment, DM reduces the impact of amplitude discrepancies and low SNR conditions — critical for land FWI applications (Reta-Tang et al., 2023; Krishnasamy et al., 2023).

For reflectivity inversion, multi-scattering improves shallow subsurface illumination beyond what primary reflections provide.

The reflectivity kernel emphasises high-wavenumber content, and iterative updating reconstructs relative amplitudes, enhancing resolution and structural coherence. Likewise, multiple attenuation can be automatically addressed during the iterative inversion as the waveform match is improved.

Field data example The study area corresponds to an onshore seismic survey acquired in the Midland Basin, a sub-basin of the Permian Basin, near Odessa, Texas, USA (Figure 1). The survey was designed to support evaluation and development of multiple prospective zones, including the Barnett Shale, Mississippi Lime, and Devonian horizons (e.g., Sutton et al., 2005). Acquisition employed Vibroseis sources with a low-dwell sweep ranging from 2 to 94 Hz. Table 1 summarises the main acquisition parameters.

Initial near-surface model and preprocessing Preconditioning the seismic data prior to FWI is critical, particularly for land surveys where low-frequency signal-to-noise ratios (SNR) are often poor. The goal is to suppress energy that cannot

Figure 1 Study area location in the Midland Basin relative to the larger Permian Basin (modified from S. Dutton et al., 2005)

be reproduced by acoustic forward modelling, thereby improving inversion stability and reliability. The preprocessing workflow includes: • Harmonic-noise attenuation • Minimum-phase conversion • Low-frequency geophone-response compensation • High-amplitude noise suppression • Linear and ground-roll attenuation • Inverse-Q compensation Figure 2 shows example shot records filtered to 8 Hz before and after preconditioning. Despite these efforts, the usable starting frequency for FWI remains constrained to approximately 5 Hz due to spatially variable SNR. No static corrections — neither conventional nor residual — were applied to the data used in the FWI workflow. This choice ensures that inversion remains sensitive to near-surface velocity anomalies rather than being influenced by externally imposed shifts (Krishnasamy et al., 2025).

Figure 2 Sample recorded shot gather filtered with a maximum corner frequency of 8 Hz; a) before pre-processing b) after pre-processing and c) noise removed.

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Velocity model-building The initial near-surface model was constructed using refraction tomography, supplemented where possible by shallow sonic logs (Figure 3a). FWI began at 5 Hz using the dynamic matching (DM) objective function, initially focusing on refracted waves.

A multi-scale approach was adopted, progressively increasing frequency and offset ranges at each stage. Additionally, a data-domain quality factor was applied to down-weight low-SNR contributions, reducing noise influence and improving inversion reliability. Refracted-energy penetration is limited by available offsets; beyond this depth, multi-azimuth reflection tomography is typically employed to update deeper velocity.

With this updated model (Figure 3b), velocity refinement continued using MP-FWI with reflectivity. At this stage, addition-

al data conditioning was applied to improve waveform matching, including surface-consistent deconvolution, further noise attenuation in multiple domains, and several passes of surface-consistent scaling. Reparametrising the wave equation in terms of velocity and reflectivity enables reflectivity-driven updates beyond refracted-wave penetration depth within the same inversion framework. Scale separation in the FWI gradient provides a velocity kernel for updating background velocity (Figure 4).

Starting from the initial model (Figure 3b), velocity updates using the conventional FWI gradient (Figure 4a) are compared to those using the velocity kernel (Figure 4b). Conventional updates exhibit high-wavenumber features from specular reflections — typically an order of magnitude larger than tomographic updates — requiring additional conditioning and reflection tomography in

Figure 3 a) Initial velocity model; b) intermediate velocity used for MP-FWI c) final MP-FWI velocity model.

Figure 4 Velocity updates at one stage departing from starting velocity model (Figure 3b) using a) the conventional FWI gradient and b) the MP-FWI velocity kernel. A strong migration imprint is present in the conventional FWI update, which prevents background velocity updates with reflected energy.

Figure 5 Comparison of field (wiggles) and synthetic (colour) shot gathers. Synthetic shot gathers were computed from a) initial and b) updated velocity model; For a perfect velocity model, the positive amplitudes of the synthetic, red, should be aligned with the positive amplitude, peaks, in the observed data and the negative amplitude of the synthetic, blue, should be aligned with the negative amplitude, troughs, on the observed data.

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Figure 6 a) RTM and b) MP-FWI image along northsouth direction.

Figure 7 a), b) RTM images at depths 1.5 and 3.4 km, respectively; c), d) MP-FWII images for the same depths.

standard workflows. In contrast, updates from the velocity kernel enhance low-wavenumber components, improving background velocity convergence within the same FWI framework. Once the background velocity is refined, higher-resolution updates can be achieved using the conventional gradient. The final background velocity model is shown in Figure 3c.

Model validation was performed by comparing synthetic common-receiver gathers for the initial (Figure 5a) and final (Figure 5b) velocity models with recorded data. Positive amplitudes in the recorded data (black) show improved alignment with positive amplitudes in the synthetic data (red) for the final model.

Figure 8 Comparison of the final reflectivity (wiggles) around a well location with the synthetic trace (red wiggle) computed from well logs.

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Imaging results MP-FWI provides significant imaging benefits compared to conventional algorithms. Figure 6 compares crossline sections from MP-FWI (Figure 6b) and reverse-time migration (RTM) (Figure 6a), both computed from the final velocity model. MP-FWI delivers superior focusing and resolution, achieved through scale

SPECIAL TOPIC: LAND SEISMIC

separation that emphasises high-wavenumber features in reflectivity while reducing backscattering at high-impedance contrasts.

Figure 7 shows similar comparisons for slices at depths of 1494 m and 3408 m, where channel definition in MP-FWI images is markedly improved over RTM. Finally, in Figure 8 we show a comparison of reflectivity at a well location with the synthetic trace computed from well information. As observed, there is good match of primary reflectors.

Huang, G., Macesanu, C., Liu, F., Ramos-Martinez, J., Whitmore, D., Calderon, C. and Bloor, R. [2025]. Multiparameter elastic FWI for joint inversion of velocity and reflectivity. 86th EAGE Annual Conference and Exhibition, Extended Abstracts.

Huang, Y., Mao J., Sheng, J., Perz, M, He, Y., Hao, F., Liu, F., Yong, S.L., Chaikin, D, Ramirez, A., Hart, M. and Roende, H. [2023].

Towards high-fidelity imaging: Dynamic Matching FWI. The Leading Edge, 42, 124-132.

Krishnasamy, T., Beck, J. and Reta-Tang, C. [2025]. From statics to

Conclusions We have demonstrated the advantages of applying acoustic multiparameter full-waveform inversion (MP-FWI) for simultaneous velocity and reflectivity estimation using land seismic data from the Midland Basin, USA. Incorporating the dynamic matching (DM) objective function significantly enhances velocity estimation at low frequencies, where land data typically suffer from poor signal-to-noise ratios. The velocity kernel derived from scale separation enables reliable updates at depths where only reflected energy is available, improving convergence of the background velocity model. Reformulating the wave equation in terms of velocity and reflectivity eliminates the need for density estimation to generate synthetic reflectivity, simplifying the inversion process. Additionally, the reflectivity kernel facilitates iterative image reconstruction, delivering higher resolution, and improved continuity compared to conventional imaging approaches.

dynamics: enhancing onshore velocity models with full waveform inversion. First Break, 43(1), 63-68.

Krishnasamy, T., Sheng, J., Florendo, R., Beck, J., Sierra, A., Murphy, S., Siebens, J. and Iwo-Brown, Y. [2023]. High-resolution near-surface land FWI across the Delaware basin fill zone. 3rd International Meeting for Applied Geoscience & Energy, Expanded Abstracts.

Mao, J., Sheng, J. and Hilburn, G. [2019]. Phase only reflection full-waveform inversion for high resolution model update.

89th SEG Annual International Meeting, Expanded Abstracts, 1305–1309.

Ramos-Martinez, J., Crawley, S., Zou, K., Valenciano, A.A., Qiu, L. and Chemingui, N. [2016]. A robust gradient for long wavelength FWI updates. 78th EAGE Annual Conference & Exhibition, Extended Abstracts.

Reta-Tang, C., Sheng, J., Liu, F., Vazquez, A. and Cabrera, A. [2023].

Applications of full waveform inversion to land data: case studies

Acknowledgements We thank TGS for authorising the publication of this work and TGS Multiclient for providing the dataset. We thank our colleagues in R&D Geophysics for the fruitful discussions that contributed to improving this work.

in onshore Mexico. The Leading Edge, 42, 190-195.

Sheng, J., Mao, J., Liu, F. and Hart, M. [2020]. A robust phase-only reflection full waveform inversion with multi-channel local correlation and dynamic minimum total-variation constraint.

82nd EAGE Annual Conference & Exhibition, Extended Abstracts.

References

Whitmore, N.D., Ramos-Martinez, J., Yang Y. and Valenciano, A.A.

Dutton, S.P., Kim, E.M., Broadhead, R.F., Raatz, W.D., Breton, C.L.,

[2020]. Full wave field modeling with vector-reflectivity. 82nd

Ruppel, S.C and Kerans, C. [2005]. Play analysis and leading-edge

EAGE Annual Conference & Exhibition, Extended Abstracts.

oil-reservoir development methods in the Permian basin: Increased

Yang, Y., Ramos-Martinez, J., Whitmore, D., Huang, G. and

recovery through advanced technologies. AAPG Bulletin, 89, 553-

Chemingui, N. [2021]. Simultaneous inversion of velocity and

576.

reflectivity. First Break, 39(12), 55-59.

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