Maintaining the Quality of the MPFM Measurements over the Life of the Field Author: M.M. Zoainat (Mohamad Mah’d Zoainat)
Co-Author: Alexandre Martins
1. Abstract Accurate production and reliable flow measurements are essential for making intelligent decisions on oil and gas production wells. Reliable flow rates are important to determine the reserves, the economics of continued operations to evaluate projects to improve oil and gas production and/or reduce water production–either means to increase well profitability and reserves. In this area of production measurement, Multiphase Flowmeters play a major role and is far more complex, both in terms of hardware and in terms of fluid flow dynamics. The challenges, however are in the reliability of the equipment, operational costs and the remote monitoring capability. Despite its robustness, the quality of measurements from a multiphase Flowmeter is highly influenced by the validity of the following inputs. • • • •
PVT’s Composition variation. Fluids densities variations Validity/Quality of the empty pipe Calibration. Scale deposit.
The multiphase flowmeter of this particular interest uses dual energy gamma attenuation principles combined with a venturi mass flow rate measurement. Measurement of phase fractions are based on atomic principles and with the help of periodic maintenance schemes, accurate and reliable measurements can be achieved at. This paper will focus on the effect of the above said factors on MPFM well testing data from Saudi Aramco- Qatif field in order to understand and qualitatively validate the meter’s output. The paper also sheds light on the effects of incorrect PVT sets used for measurements and resulting uncertainties. Effects of wax and scale deposits on the monolithic windows, that are present in the path of the nuclear measurements, are briefly discussed in this paper.
2. Introduction Multiphase flowmeter manufacturer’s have always claimed for the need of using good quality PVT data to assure acceptable metering performance. The application and performance of multiphase meters has been well documented through technical papers and industry forums, and after several years of development is maturing (Scheers 2004). Some multiphase measurement techniques can perform better, and the meters provide a more compact solution, than the traditional separation approach. Effects on multiphase flow measurements in Qatif field due to the following listed factors have been studied extensively and this exercise will prove valuable to understand the metering technology and understand the importance of setting the correct PVT information and time to time monitoring and maintenance of the MPFM. The factors that were studied are: Effects of Sulfur concentration variation Effects of density variation and input data quality Effects of H2S & NaCl (Salinity) concentration variation and composition variation Effects of CaCO3 and non stable scale deposition Effects of reference measurement quality
3. Measurement Theory 3.1. Nuclear Model
The objective of the nuclear model is to determine the three phase hold-ups, αo, αw and αg that are subsequently used to calculate the mixture density and WLR. The model uses a system of three equations to determine the phase hold-ups. The first two are nuclear spectroscopy equations and the third is the fundamental assumption of the meter that no more than three phases are flowing:
le mixture he mixture
− D µ ole . ρ o .α o + µ lew . ρ w .α w + µ leg . ρ g .α g le vacuum − D µ ohe . ρ o .α o + µ he . ρ w .α w + µ he . ρ g .α g he w g vacuum
αo + αw + αg = 1 Once the three phase hold-ups have been determined, the WLR and the mixture density can be calculated using the phase hold-ups and phase densities.
= α gas ⋅ ρ gas + α oil ⋅ ρ oil + α water ⋅ ρ water
Where: D: µ: ρ: α: o: w: g: le: he:
Diameter of the venturi throat; a known constant Mass attenuation coefficient Density Phase hold-up Oil Water Gas Low energy (32 KeV) High energy (81 KeV)
The quality of the hold-ups measurements, as described above, is a direct consequence of the quality of the inputs to the equations. 3.2. GVF model
The second model is the GVF calculation. It determines the GVF from the gas phase hold-up and other parameters. It is important to recognize the difference between the gas phase hold-up and the Gas Volume Fraction. The phase hold-up is areabased. It represents the area at the venturi throat occupied by gas at any instant. It is not volumetric and does not reflect a rate. The GVF is volume-based and represents the percent of gas flowing compared to the total fluid flowing. A GVF of 75% means that for every 1 m3 or bbl of liquid flowing (Oil + Water) at line conditions, 3 m3 or bbl of gas are flowing at line conditions. The GVF is volumetric, but does not reflect a phase velocities.
The reason that the gas phase hold-up and GVF are different is because of slip. The term “slip” refers to the difference between the gas velocity and the liquid velocity. In a multiphase environment, gas will flow faster than the liquid in a vertical pipe. The degree of slip (velocity difference) depends on many factors including the density difference between the gas and liquid phases, the liquid viscosity and the gas and liquid phase hold-ups. The GVF will never be less than the gas phase hold-up and under most conditions the GVF will be greater than the gas phase hold-up. It is a consequence of the Mutiphase Flow Meter Vx geometry, that there is no slip between oil and water phases.
3.3. Total Flow Rate Model
The last model provides the total mass flow rate. It is based on Bernoulli’s venturi equation for multiphase flow relating differential pressure and the total flow rate. Qtotal = K ⋅ C d ⋅ ε 2 ⋅ ρ mixture ⋅ ∆Pdynamic Where:
Qtotal: K: Cd: ε: ΔPdynamic: pressure)
Total mass flow rate Geometric factor Discharge coefficient, accounting for Multiphase flow Expansibility factor for gas Dynamic venturi differential pressure (accounts for the hydrostatic
3.4. Secondary Calculations
At this point, the meter’s primary outputs have been produced: total mass flow rate, WLR and GVF. The secondary outputs (oil, water and gas flow rates at line conditions) are derived from the above quantities using the following generalized approaches: qgas = GVF ⋅ qtotal qliquid = qtotal − qgas qwater = WLR ⋅ qliquid
qoil = qliquid − qwater
4. Solution Triangle Analysis The nuclear model can be understood graphically using the “solution triangle” which is a powerful tool for analyzing the behavior of the Vx meter. The graph origin point (O) represents the number of low energy and high energy photons counted at the detector if the venturi is emptied (vacuum). The X,Y axis represent the linear attenuation, which is a function of the specific phase attenuation coefficient, specific phase density and the phase hold-up.The three corners of the triangle show where the single-phase gas, oil and water produced by the well lie in this chart. These three points can be determined from direct measurements (fluid references) or calculations (operator input). All flow mixtures consisting of only gas and oil in the solution triangle will be positioned on the straight line between the pure oil point and the pure gas point. All mixtures consisting only of water and gas will be positioned on the straight line between the pure water point and the pure gas point. Flow mixtures consisting only oil and water will be positioned on the straight line between the pure oil and pure water point (Figure-1). Flow mixture of oil, water and gas will be positioned inside the triangle.
Low Energy Linear attenuation
Gas (αg=1, αw=αo=0)
Any mixture of these 3 single phases will be described by a point within this “Solution Triangle”
High Energy Linear attenuation
WLR = OA/OW Gas hold up = OB/OG
αg=αw=0) Water (αω=1, αg=αo=0)
A Figure 1 - Solution Triangle
All mixtures having 50% WLR will be on the line that goes from the gas point and splits the oil-water line in the middle (See figure-1 WLR=OA/OW). Similarly, all mixtures having 50% gas hold-up will be on the line that can be drawn from the middle of the oil-gas line to the middle of the water-gas line.
5. Literature Study Multiphase flow meters based on dual energy gamma-ray attenuation are investigated by many researchers. Thorn  analyzed different types of multiphase flow meters and came to a conclusion that “… while in principle dual energy gammaray attenuation methods are elegant, in practice a number of difficulties have to be overcome. As with all radiation measurement methods, because of statistical nature of the source there is a compromise between measurement time and accuracy. The greater the accuracy required, the longer will be the measurement period. More intense sources can be used to reduce the measurement period, but at the expense of increased safety precautions.
Although gamma-ray methods can be used over the complete range of component fractions, the salinity of the water component can cause problems. Since salt has a high attenuation coefficient compared to that of water, a change in the salinity of the water phase will cause a significant error in the measured water fraction, unless this is compensated for. All of the dual-energy methods described so far use a single radiation beam. The limitation of single-beam methods is that they are flow regime dependent. The measured component fractions will only be representative of the complete flow cross section if the oil, water and gas components are homogeneously mixed. Multibeam arrangement may be used to overcome the problems of flow regime dependency, although they are more complex and more expensive than single-beam devices.â€? E. Abro used the low-energy multi-beam gamma-ray densitometer  to expand the measured fluid zone to the total pipe cross section. To reduce the measurement errors they used three or four gamma-ray detectors positioned around circumference of measured pipe. M. Al-Khamis investigated the effect of H2S contamination of measured fluid on the performance of dual energy multiphase flow meter  and found that water liquid ratio (WLR) is greatly overestimated due to H2S presence in the measured fluid. G. Segeral [5, 8] proposed a method for detecting and identifying in-situ the composition of scale deposits found onto the inner surfaces of multiphase flow meter. The method consists of measuring the fluid gamma ray attenuation at three energy levels: 32 keV, 80 keV and 356 keV. It uses the fact, that attenuation coefficients of different types of scales and measured fluid components (gas, oil and water) are different at different gamma energy levels.
6. Sensitivities Study As explained previously, the gamma ray attenuation is used to determine the individual fluid phase hold-ups. And by looking at the equations in section 3, we can find that the Vx meter will be sensitive to composition (mass attenuation
coefficients) changes of individual phases (Oil, Water and Gas) and density changes. Below is a discussion about the most common issues (but not restricted) that may affect measurements quality. Lately, a common request about the effects of salinity changes to the quality of the Vx measurements has been recurring. But the fact is that the Vx technology is not sensitive to changes in salinity due to conductivity effects on the produced water [as in the meters based on permittivity measurements], but is sensitive to variations in both density and composition (mass attenuation coefficients) as it was mentioned above. 6.1. Density Variation
It can be seen from the equations mentioned in section 2, that the individual densities for oil, water and gas are part of nuclear model and the mixture density calculation, which means any wrong density input into the model will negatively affect the output. The effect of the density change will be on the linear attenuation for both low (32 Kev) and high energy (81Kev) levels (X, Y axis). An incorrect oil density for example, will in effect move the oil point (if calculating reference point by operator input option, or even conducting an in-situ reference measurement) diagonally upwards or downwards on the oil-gas line depending (see figure below) if the oil is less dense or denser, than our reference. The water reference will be affected in the same manner and the reference point will move diagonally upwards or downwards on the water-gas line. This change would affect the phase hold-up and consequently the WLR. Being aware of this effect is important, when operating at high pressure or working with condensates. A wrong density input would also affect the mixture density calculation, which is a direct input into the venturi equation that calculates the total mass flow rate. This error propagation will increase the uncertainty of the measurement obtained, and will be also be dependent on the flowing conditions (GVF, WLR and flow rates). The example below shows a case with 2 different oil density inputs to the software, keeping all other parameters the same. Figure 2 shows the solution triangle in a case of oil density 927.466 Kg/m3, and it can be seen the operating point is within the working envelope (the original case). In Figure 3,
the oil density input has been changed to 880.996 Kg/m3 to simulate a wrong density input, and the result is that the solution triangle has changed because of the change of the linear attenuations due to the density change, and this could change the outputs that are on the left side of the triangle in these snap shots. In figure 4, we can see the effect of the previous mentioned example on the flow rates.
Figure 3 - Density 880.996 Kg/m3
Figure 4 - Flow rate difference due to wrong oil density Input
Therefore, any density input during fluids in situ references has to be accurate in order to reduce errors in outputs and consequently guarantee the quality of the measurements. 6.2. Composition Variation
Produced well fluids generally are water and hydrocarbons (Oil & Gas). In some cases, these fluids could be contaminated with H2S or CO2, which will affect the measurement if not accounted for. This effect will be different depending on which phase the H2S or CO2 are in (liquid or gas). The Vx software can be configured to account for such composition changes. However, the contamination has to be quantified by having the fluid composition analyzed at a PVT lab, and then inputted into the software by the user after selecting the appropriate fluid properties model. It has to be noted that the composition analysis results must be accurate and representative of the actual flow. Failing to do so, will result in an increased
measurement uncertainty. The error in the Vx output in this case comes mainly from the gamma system measurements due to the fact that Sulphur in H2S and the Oxygen in CO2 have a larger atom size than the carbon and hydrogen, and consequently will have larger mass attenuation, this will affect the Gamma attenuation, the calculated hold-up, and consequently GVF and WLR. To have some examples, in the case of CO2 where it will be in gas phase, the effect will be only at higher GVFâ€™s, as the presence of Oxygen in the gas phase will increase the mass attenuation and in effect the linear attenuation causing the operating point to shift towards the water point causing the WLR to be overestimated, the GVF will increase slightly, causing a slight underestimation of the liquid phase. But if the GVF is very high (e.g. GVF> 95%), the accuracy of the composition becomes very important and almost mandatory in some cases, as a slight change in the reference point position could lead to negative values. Another significant case is the presence of H2S in the produced fluid, as it tends to move between the liquid and gas phases depending on the pressure. The larger effect on measurements will be when it is in the liquid phase, this is mainly due to the fact that Sulphur atoms are more close to each other in the liquid phase than in the gas phase which will result in larger mass attenuation in the liquid phase. Because of this property for the H2S, it becomes difficult to predict how the H2S will behave across the range of operating pressures, therefore the PVT analysis should account for the whole planned operating range. Below are some examples that show how inaccurate H2S fractions input to the software (in the case of operator input option for the reference points) would affect the oil reference point (oil corner in the solution triangle) affecting WLR, GVF and consequently flow rate measurements.
Figure 5 - Original case (no H2S)
Figure 6 - Sulphur added to oil (0.3 mass fraction)
Figure 7 - Sulphur added to gas (0.3 mole fraction)
6.3. Sulfur effect on MPFM output values 
The effect of Sulfur contamination of measured multiphase fluid was studied by introduction of several Sulfur concentration values into MPFM software and calculating the corresponding changes in measured output values. The Table 1 shows how the MPFM output values depend on Sulfur concentration in the measured multiphase fluid.
Table 1. Sulfur effect. Year 2009, calibrated with: H2S concentration = 0.126 molar fraction, NaCl concentration = 14.807 g/l Sulfur concentration, % by weight
Oil flow rate, bpd 7750 8137.3 Water flow rate, bpd 1954 1611.2 Gas flow rate, mmscfpd 9.9 10 water cut, % 20.1 16.5 GOR, scf/stb 1280.4 1224.9 Normalized to Sulfur concentration 0.0082% by weight Oil flow rate 1 1.049 Water flow rate 1 0.82 Gas flow rate 1 1.01 water cut 1 0.82 GOR 1 0.96
8564.5 1235 10 12.6 1169.8
9036.9 822.3 10.1 8.3 1115.2
1.10 0.63 1.01 0.63 0.91
1.17 0.42 1.02 0.41 0.87
normalized MPFM output
oil flow rate water flow rate gas flow rate water cut gas oil ratio
Sulfur concentration, % by weight
Fig.8. Normalized MPFM output values vs. Sulfur concentration.
Fig. 8 shows [in normalized form] the MPFM output values as a function of Sulfur concentration in the measured multiphase fluid. We can see, that gas flow rate is
the least affected by Sulfur contamination, while water cut and water flow rate are affected the most â€“ these values are reduced by ~40% for every 0.02% increase in Sulfur concentration. 6.4. H2S effect on MPFM output values 
The effect of H2S contamination of measured multiphase fluid was studied by introduction of several H2S concentration values into MPFM software and calculating the corresponding changes in measured output values. The Table 2 shows how the MPFM output values depend on H2S concentration in the measured multiphase fluid.
Table 2. H2S effect. Year 2009, calibrated with: Sulfur concentration = 0.0360% by weight, NaCl concentration = 14.807 g/l H2S concentration, mol. fraction 0.0264 0.0514 Oil flow rate, bpd 7744.1 8084.7 Water flow rate, bpd 1958.1 1656.8 Gas flow rate, mmscfpd 9.9 10 water cut, % 20.2 17 GOR, scf/stb 1281.5 1232.3 Normalized to H2S concentration 0.0264 molar fraction Oil flow rate 1 1.04 Water flow rate 1 0.85 Gas flow rate 1 1.01 water cut 1 0.84 GOR 1 0.96
0.0764 8413.1 1367.6 10 14 1188.7
0.1014 8730.2 1089.6 10 11.1 1149.9
0.126 9036.9 822.3 10.1 8.3 1115.2
1.09 0.70 1.01 0.69 0.93
1.13 0.56 1.01 0.55 0.90
1.17 0.42 1.02 0.41 0.87
normalized MPFM output
oil flow rate water flow rate gas flow rate water cut gas oil ratio
H2S concentration, molar fraction
Fig.9. Normalized MPFM output values vs. H2S concentration.
Fig. 9 shows [in normalized form] the MPFM output values as a function of H2S concentration in the measured multiphase fluid. We can see, that gas flow rate is the least affected by H2S contamination, while water cut and water flow rate are affected the most â€“ these values are reduced by ~30% for every 0.05 molar fraction increase in Sulfur concentration. 6.4.1. NaCl effect on MPFM output values 
The effect of NaCl contamination of measured multiphase fluid was studied by introduction of several NaCl concentration values into MPFM software and calculating the corresponding changes in measured output values. The Table 3 shows how the MPFM output values depend on NaCl concentration in the measured multiphase fluid. Table 3. NaCl effect. Year 2009, calibrated with: Sulfur concentration = 0.0360% by weight,
H2S concentration = 0.126 molar fraction NaCl concentration, g/l 14.807 Oil flow rate, bpd 9036.9 Water flow rate, bpd 822.3 Gas flow rate, 10.1 water cut, % 8.3 GOR, scf/stb 1115.2 Normalized to NaCl concentration 14.807 g/l Oil flow rate 1 Water flow rate 1 Gas flow rate 1 water cut 1 GOR 1
20 10048.9 975.3 9.4 8.9 935.1 1.11 1.19 0.93 1.07 0.84
normalized MPFM output
oil flow rate water flow rate gas flow rate water cut gas oil ratio
NaCl concentration, g/l
Fig.10. Normalized MPFM output vs. NaCl concentration.
Fig. 10 shows [in normalized form] the MPFM output values as a function of NaCl concentration in the measured multiphase fluid. We can see, that all MPFM output values are affected by NaCl contamination, while water flow rate and gas oil ratio are affected the most â€“ water flow rate is increased by 20% for increase in NaCl concentration by 5 g/l, while gas oil ratio is reduced by 16% for the same NaCl contamination level.
6.5. Scale deposition effect on MPFM output values, measured by B. Theuveny.
Scale deposition effect: change in measured WLR [water liquid ratio] due to deposition of 0.3 mm of CaCO3 from 5% to 45% [3, p.9] was recorded during operation of dual energy spectral gamma ray â€“ venturi multiphase flow meter.
Fig.11. Gradual increase of WLR reported by the multiphase flow meter .
Fig. 11 shows the MPFM output value - water liquid ratio as a function of scale deposition thickness, as it was changing in time. It was found that the scale
deposition thickness developed during the time of the test was 0.3 mm. That scale deposition was the reason of increase in water liquid ratio ~40%.
6.6. Quality of the Empty Pipe Measurement
A final point to be taken into consideration as per the equations on section 2 - is the empty pipe reference (referred as Nvacuum) for both energy levels. Analyzing on the premise that the original empty pipe measurement was correctly performed, the main issue regarding sensitivities to variations on the number of detected gamma in vacuum are solely related to the stability of the used gamma detector over time. The detector used by the Vx technology is known to have the best long term stability within the industry. Therefore, if the empty pipe reference measurement is performed periodically as per the maintenance recommendations no effects on the measurements are expected.
6.7. Summarized Results
1. Measured Oil flow rate depends on Sulfur, H2S and NaCl concentration: it is increased by 17% for Sulfur concentration increase from 0.008 to 0.036 % by weight, it is increased by 17% for H2S concentration increase from 0.026 to 0.126 molar fraction. It is increased by 11% for NaCl concentration increase from 14.8 g/l to 20 g/l. 2. Measured Water flow rate depends on Sulfur, H2S and NaCl concentration: it is reduced by 58% for Sulfur concentration increase from 0.008 to 0.036 % by weight, it is reduced by 58% for H2S concentration increase from 0.026 to 0.126 molar fraction, it is increased by 19% for NaCl concentration increase from 14.8 g/l to 20 g/l. That conclusion is supported by data by M. Al-Khamis , when increase in H2S concentration in the measured fluid resulted in overestimating the water production (WLR). 3. Measured Gas flow rate practically does not depend on Sulfur and H2S concentrations, but it is reduced by 7% for NaCl concentration increase from 14.8 g/l to 20 g/l. 4. Measured Water Cut depends on Sulfur and H2S concentration similar to Water flow rate, and it is increased by 7% for NaCl concentration increase from 14.8 g/l to 20 g/l. 5. Measured GOR value depends on Sulfur, H2S and NaCl concentration: it is reduced by 13% for Sulfur concentration increase from 0.008 to 0.036 % by weight, for H2S concentration increase from 0.026 to 0.126 molar fraction, it is reduced by 16% for NaCl concentration increase from 14.8 g/l to 20 g/l. 6. Systematic error in measured WLR [water liquid ratio] due to CaCO3 deposition with thickness of 0.3 mm is 40%. That deposition can be removed by using HCl acid wash. Error due to other types of deposition, like BaSO4 and ZnS cannot be considered as purely systematic, because of non-stable scale deposition thickness. It depends on operating conditions: flow rate, pressure or temperature, it also depends on multiphase fluid composition. This systematic error can be compensated to some extent by using the method disclosed in , based on the use of the third gamma energy source with higher energy level: E=356 keV.
7. Final Considerations
During the previous sections the aspects affecting the quality of the measurements were studied separately to simplify the understanding. In the real flow however, everything is interconnected. Variations in the water properties will be virtually irrelevant for low WLR wells. Variations of the H2S content in the gas phase will have a more important role as the GVF increases. In such a complex system the entire flow model such as the proper PVT model are to be accounted for an effective study. In order to simplify this task Schlumberger have developed a sensitivities analysis module within the Vx Advisor software. The fact that density and composition variations can be detected by analyzing the solution triangle is not a weakness but rather a strength that can be used even further for different types of production diagnostics. This is due to the fact that the measurement principle, that is used to determine the multiphase flow fractions, is simple and robust which enables us to characterize almost any change in flowing condition that might impact the density or composition during the life of the well and correct for any deviation, as long as the properties of these changes are known.
8. Conclusions 1. Systematic error in MPFM output signals due to Sulfur and H2S contaminations in the measured fluid can range from 17% to 58% for Sulfur concentration change from 0.008% to 0.036% by weight and for H2S concentration change from 0.026 to 0.126 molar fraction. 2. Systematic error in MPFM output signals due to change in NaCl concentration in the measured fluid can range from 7% to19% for concentration change from 14.8 g/l to 20 g/l.
3. Systematic error in WLR [water liquid ratio] due to CaCO3 deposition with thickness of 0.3 mm can reach 40%. This error can be partially compensated by using attenuation measurement from the third gamma energy source.
9. Recommendations 1. 2. 3. 4. 10.
MPFM periodic full calibration is required. One single MPFM should be installed per single well. Reservoir PVT verification is required. Pressurized Down Hole sample analyses are required every 10 years.
References 1. Field test results 2. B. Theuveny et al., Detection and Identification of Scales Using Dual Energy / Venturi Subsea or Topside Multiphase Flow meters – OTC 13152, Presentation at the 2001 Offshore Technology Conference, Houston, Texas, 30 April- 3 May 2001, p.1-10. 3. Mohammed N. Al-Khamis et al., Evaluation of PhaseWatcher Multiphase Flow Meter (MPFM) Performance in Sour Environments – OTC 19152, 2008 Offshore Technology Conference, Houston, Texas, 5-8 May, 2008. 4. Gerard Segeral et al., Real-time Method for the Detection and Characterization of Scale, Patent Application WO2003/042675, Priority Date - 16 November, 2001. 5. R. Thorn et al., Recent Developments in Three-Phase Flow Measurements – Meas. Sci. Technol., 1997, v. 8, p.691-701. 6. E. Abro et al., Void Fraction and Flow Regime Determination by Low-Energy Multi-Beam Gamma-Ray Densitometry – 1st World Congress on Industrial Process Tomography, Buxton, Greater Manchester, April 14-17, 1999, p.339-343. 7. J.-P. Poyet et al., Real-Time Method for the Detection and Characterization of Scale – SPE 74659, SPE Oilfield Scale Symposium, Aberdeen, UK, 30-31 January, 2002.
8. Vx Theory of Operation (6010-0032-D), 3-Phase Measurements Rev A by Jennifer Trittschuh and Eric Toskey, Rev B by Marwan Kareen Ali, Jennifer Trittschuh and Andrew Baker 9. Handbook of Multiphase Metering, The Norwegian Society of Oil and Gas Measurements by: (in alphabetical order) Corneliussen, Sidsel: BP Norway Couput, Jean-Paul: TOTAL Dahl, Eivind: Christian Michelsen Research Dykesteen, Eivind: Roxar Flow Measurement FrĂ¸ysa, Kjell-Eivind: Christian Michelsen Research Malde, Erik: ConocoPhillips Moestue, HĂĽkon: Norsk Hydro Moksnes, Paul Ove: Framo and Schlumberger Scheers, Lex: Shell GS International Tunheim, Hallvard: Norsk Hydro 10.Additional resources: -Vx Post Processor Software.
Published on Aug 28, 2013
This is a SPE paper; which was written by Mohamad Zoainat back in 2009-2011 with the help and support of Schlumberger Saudi Arabia namely; A...