Oilfield Modeling and Optimization of a Mature Field using Integrated Production Modeling Approach.

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Oilfield Modeling and Optimization of a Mature Field using Integrated Production Modeling Approach.

Julius Wosowei (Researcher)1; Prof. Chandrasekar Shastry (Guide)2

1Computer Science and Engineering, Jain (Deemed to be) University), India

2Dean, PG Studies, FET, Jain (Deemed to be) University, India

***

Abstract TheIntegratedProductionModelingApproachis essentially a design methodology that integrates the subsurface andsurface facilities as a single system as opposed to a silo design. It integrates the inflow and outflow performance of wells and multiphase flow analysis through the wellhead to the surface processing plant. This paper models and optimizes a mature oilfield of two (2) reservoirs and two (2) wells with both tied to a central inlet manifold by two separate flowlines and fluid delivered to a central separator at the process plant with limited capacity thereby requiringoptimization. The models are implementedutilizing Petroleum Experts’(PETEXs) Integrated Production Modeling (IPM) tool kit comprising Pressure, Volume and temperature Package (PVTP), Material Balance Software (MBAL) for the Reservoir modeling, the Production and System Performance Analysis Software (PROSPER) for well modeling and nodal analysis, the General Application Package (GAP) for multiphase network modeling and optimization. The IPM toolkit also provides for a field numerical reservoir modeling called REVEAL and an Interface called RESOLVE for explicit coupling of the reservoir and network simulator. The facility achieveda combinedproductionof20,806STB/day exceeding the process facility separator capacity of 18,000STB/day which resultedinoptimizingthe productionbychokingbacka well thereby achieving an optimized production rate of 17,000STB/day. The accumulatedforecast productionstands at 117MMSTB over the period from 2008 to 2030.

Key Words: Oilfield, Integrated Production Modeling, ProductionOptimization,MBAL,PROSPER,GAP

1. INTRODUCTION

Oilfield, Integrated Production Modeling, Production Optimization,MBAL,PROSPER,GAP.

2. RELATED LITERATURE

Dempsey et al [12] pioneering integrated design was embraced by multinational oil and gas companies who developed their respective integrated designs in their organizations[13,14,15,16].

The Petroleum Experts’ (PETEXs) Integrated Production Modelling (IPM) suite comprising (PVTP), (MBAL),

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Factor value:

(PROSPER)andthe(GAP)suiteprovidesanefficientmulti/ cross disciplinaryunderstandingofthecompleteproduction process.Theintegratedmodelcomprisesthereservoirsand wells (sub surface) and the surface facilities. The IPM providesarobustintegratedanalysisofcomponentsleading toeffectivedevelopment,forecasting,productionnetwork, and optimization. The IPM provides users with an MBAL toolkitforreservoirmodelingandafieldnumericalreservoir modelingtoolcalledREVEAL.

IPM also contains a module called PROSPER for well modeling and nodal analysis and a multiphase network modeling and optimization model called GAP. It also provides for an interface called RESOLVE that does the explicit coupling of the reservoir and network simulators. [17].PETEXreleaseditsfirstcommercialversionoftheIPM suitein2006andconsolidatedonafairmarketshareand was subsequently adopted as a tool for field design and managementbymajoroilcompaniesasacorporatestandard [18,19,20,21,22].TheIPMsuitecanbedepictedas:

Fig1.ProductionSystemModelling

Gina Vega Riveros et al [23] work combined volumetric analysis,MonteCarlos,and material balanceandoutcome led to improved recovery factor of original oil in place (OOIP). Tuong Van Nguyen [24] “Novel methodology suggested a processing plant design that maximizes hydrocarbonproductionandminimizespowerconsumption, cooling and heating demands. The methodology layout includedpredictionoftheproductionprofile,processplant assessment, process plant optimization, plant sizing, and heatingandcoolingdemands.

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Somecrediblelessonslearnedshowthatthe difference in weights in IPM simulation compared to stand alone is a functionoftheaccuracyofboundaryconditions.Hatviketal [25]madeaperformancecomparisonamong;astand alone dynamicreservoirmodel,astand aloneflownetworkmodel, andafullycoupledreservoirnetworkmodelandconcluded that a fully coupled model is the only one that reflected integrated behavior of the entire system that reduces the uncertaintyorforecast.

3. METHODOLOGY

3.1 Development of reservoir Model (MBAL)

TheintroductionofMBALaccountsformaterialsenteringor exitingthesystem.Thesetofcalculationsderivedconsiders thereservoirasalargetankandusesmeasurablequantities to ascertain materials that are difficult to measure. The measurablequantitiesarethecumulativefluidforwater,oil, andgas,fluidproperty,andreservoirpressure.Thematerial balanceispremisedonthemassconservationprinciple.

Initial Hydrocarbon originally in place = Fluid produced+Remainingfluidinplace

Production=STOIIP*UnitExpansion+WaterInflux

Materialbalanceimpliesproducingacertainamountoffluid and measuring the average reservoir pressure before and afterproduction,andwiththehindsightofPVTpropertiesof thesystemcalculateamassbalance.TheMaterialBalance Equation[MBE]wasmodifiedbyHavlenaandOdehtoderive a straight line equation with parameters expressed as a function of others [26]. The MBE can be mathematically expressedas: Np*[Bo+(Rp Rs)*Bg]+WpBw = N*[(Bo Boi) + (Rsi Rs)*Bg + MNBoi*(Bg/Bgi 1)+(1+M)*NBoi*(CwSw+Cf)∆P/1

Equation(1)

Thesimplifiedstraight lineformcanbegivenas: F=N*(E

Equation(2)

Therefore,takingaplotof[F/(E

E

VsW

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PROSPERisforthemodelingofthewell.Itservesasatool for the modeling of Well and pipelines as well as for the nodalanalysisfortheutilizationofspecificfieldinformation. TheWellmodelcreatedformsthelinkbetweenthereservoir and surface production system components [27]. The characteristicsoftheWellhoweveraccountedforthefluid characterization (PVT) and other essential components of thePROSPERsuitearetheVerticalLiftPerformance(VLP), InflowPerformanceRelationship(IPR),TubingTransverse curves,andAbsoluteOpenFlow(AOF).

3.3 Development of a Surface Facility Model (GAP)

While the MBAL and PROSPER are used for the Reservoir andWell,theGAPsuiteisusedfordevelopingthesurface facility model [28]. The creation of GAP requires all Well details (Well type, name, and location), flowline and pipe specifications(landroughnessanddiameter),andelevation. In the surface model, all active and inactive Wells are includedinthesurfacenetworkobservedinbothReservoir andWelldevelopment.TheGAPdesigninthisModeldoes not have a compressor due to low gas requirements. The generalGAPworkflowisasdetailedbelow:

Constructasurfacemodel(GAP).

LinkMBALandPROSPERmodelstoGAP.

AddQmaxandDowntimeorWellheadabandonment pressureandMRTLL.

GenerateIPRandVLPcurves.

PerformSimulation.

3.4 Input Parameters

The Input parameters for the MBAL, PROSPER, and GAP modelsareasfollows:

3.4.1 MBAL:TheMBALinputcomprisesthePVTdata,Tank data, history matched aquifer properties, relative permeabilitydata,productiondata(history),andreservoir thickness. The input parameters are summarized in the tablesbelow:

E

givesa linearrelationshipestimatingthe Original Hydrocarbon in Place (OHIP) with a unit slope meaning a reservoir model and the aquifer is identified. A situation wherethisdoesnotexistimpliesthedeviationisadynamic mechanismandfurthertuningofparametersisrequiredto obtainlinearityandthepresenceofcorrupteddataforthe analysis.

3.2 Development of Well Model (PROSPER)

PROSPERisapackageofthePETEXIPMsuiteforproduction modeling. While MBAL is used to model the reservoir,

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Table1PVTData

Table5ReservoirXData

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Table2TankData

Table3RelativePermeabilityofX

Table6ReservoirYData

3.4.2 PROSPER Model: ThePROSPERinputWellX1datais ascontainedinthetablesbelow;

WaterCut:22.2%

ProductivityIndex=11.6STB/day/psi ReservoirPressure:4680psig TotalGOR:325.028SCF/STB

Table7WellDeviation

Table4RelativePermeabilityofY

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Table8DownholeEquipmentDataforWellX1

Table9GeothermalGradientforWellX1

Table10TestDataPointforWellX1

Theinput Well Y1 datais:

WaterCut:0%

ProductivityIndex=7.03stb/day/psi ReservoirPressure:4660psig

TotalGOR:768scf/stb

Table11WellDeviationforWellY1

Table12DownEquipmentDataforWellY1

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Table13GeothermalGradientforWellY1

Table14TestDataPointforWellY1

3.4.3 GAP Model:TheinputparametersfortheGAPsurface facilitiesmodelisasinthetablebelow(Pipelineproperties). SeparatorCapacity:18,000bbl/day SeparatorPressure:250psig

Table15PipelineProperties

4. DATA COLLECTION AND ORGANIZATION.

4.1 Data Integrity Check

Datapreparationandconsistencycheckswerecarriedout ontherelevantinputparameters.TheseincludePVTdata, the average pressure, production history, and aquifer parameters. The available PVT data were matched using different Black Oil PVT models to select the model that provides the best match for the acquired data. The Glaso correlationandthePetroskywereuseful.

4.2 The Reservoir System and Correlation

TheavailablePVTdataforReservoirXwasmatchedusing different Black Oil PVT models to select the model that provides the best match to the acquired data. From the analysis,theGlasocorrelationwasfoundtoprovidethebest match for Bubble point, Oil formation volume factor, and solution Gas Oil Ratio whereas the best matches for gas

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formationvolumefactor,gasviscosity,andoilviscositywere offeredbythePetroskycorrelation.However,forReservoir Y,theVasquez Beggscorrelationwasfoundtoprovidethe bestmatchforBubblePoint,SolutionGas Oilratio,andOil formationvolumefactor.TheBealetalcorrelationprovided the best match for Oil viscosity, Gas viscosity, and Gas formationvolume.

4.3 Data Analysis and Validation

Field data is generally prone to several errors including samplingerror,systematicerror,randomerror,andothers. Therefore,theresearchdatawasvalidatedbycarefulreview, accuracychecks,andconsistency.Thecomparisonbetween laboratory PVT data and the Black Oil PVT model was adequateandconsistent.

4.4 History Matching

The Energy needed to drive the hydrocarbon from the reservoir to the surface comes basically from three (3) sources namely: Fluid expansion, PV compressibility, and waterinflux,andthisisdeterminedbyhistorymatching.It determinesthesourceofthedrives,sizeandaquifertype, andalsoitsstrength.Thebestfitisderivedthroughatrial erroronmaterialbalancebycomparingtheobserveddata andcalculatedvalueatazero dimensionallevel.

4.5 Analytical Method

The analytical method is a nonlinear regression based technique employed in estimating the unknown reservoir and the aquifer parameters. It minimizes the difference between the observed and measured reservoir model productionandassessestheeffectofparametervariations. Theregressionqualityexplainsthedifferencebetweenthe model standard deviation and measured values. The analyticalplotdeterminestheOOIP,innerandouterradius, encroachmentangle,andaquiferpermeability.

4.6 Graphical Method

Afteraproperqualitymatchobservationfromtheanalytical plot,HavlenaandOdelinearplot(F/EtvsWe/Et)canbeused todeterminethesizeoftheaquiferinthegraphicalmethod. This is also known as the Campbell plot with no initial aquifer and flow expansion becoming the only source of energydriveofthereservoir.

4.7 Energy Plot

The energy plot defines the existing energy drive of the reservoir. These are either or all of the fluid expansion, waterinflux,andinjectionorpore volumecompressibility. Thisistheenergysystemcontributiontothereservoir.

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4.8 Material Balance Evaluation Assumptions

Duetothevulnerabilityofmaterialbalancecalculationseven withsmallpressurechanges,certainassumptionsaremade:

Constanttemperature

Pressureequilibrium

Constantreservoirvolume

4.9 Black Oil correlation model:Thisdescribedthefluid behaviorinbothwellsXandYduetolimitedPVTdata.The blackoilmodelusuallyaccountsforretrogradecondensate fluidsandallowsfortheproductionofliquiddropoutinthe Wellbore.

4.10 Stable and Cyclic Wells: Wells can be classified as either stable or unstable. Wells producing at constant WellheadRate(WHR)areclassifiedasstablewhereascyclic (unstable)WellsexhibitconstantBHPpressurebuild upin short bursts of Gas and under liquid loaded conditions. ReservoirYinourstudycontainsvolatilecrudewhereasX doesnot.

4.11 IPR/ VLP Match

BeforemyanalysisiscarriedoutinPROSPER,theIPRand VLP must be matched with correlations for accurate sensitivity analysis. IPR is defined as “the Well flowing bottom holepressure(Pwf)aboutproductionrate”.Itshows whatreservoirscandelivertothebottomhole.Itdescribes the flow rate behavior with respect to pressure and represents an important tool to understand productivity. VLPcurveshowstheamountofpressurerequiredtoliftan amountoffluidtothesurfaceatagivenWHP.Theessenceof the matching is to ascertain the percentage difference betweenthemeasuredrate andcalculatedrateofgasand Bottomholepressure.

5. RESULTS AND DISCUSSION FOR FIELD X

5.1 A brief History of field X

Reservoir X is an undersaturated oil reservoir with the followingspecifications:

Initialpressure=5150psia

Temperature=2150F

Bubblepointpressure=1537.85psia

API=35.2

InitialsolutionGasratio=352.028scf/STB

Thickness=120ft

InitialOilinplace=425MMSTB

ResultsofHistoryMatching

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Fig.2: Plot of the Drive mechanism for field X

5.2 Energy Plot

After a proper aquifer fitting was performed on historical productionandaquiferparameters,apictorialviewofthe fractional distribution of energy responsible for hydrocarbonrecoveryoffieldXwasobtainedasshownin figure 2. The energy plot shows that fluid expansion was initiallythemajordrivemechanism,afterwhichwaterdrive becameamajorcontributortoproductionandPoreVolume compressibilitytheleast.

Fig.3: Graphical plot (Campbell) for field X before Regression

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Fig.4: Analytical plot results for field X before Regression

5.3 WITHOUT AQUIFER

From the production history match without adding an aquifer, the above plots were obtained for the analytical and graphical methods asshowninfigures3and4.From the Campbell plot, the history data points do not lie in a straightline,showingthatagoodmatchhasnotbeenmade andtheremaybethepresenceofanaquifer.

The Analytical plot also shows a mismatch between historicalcumulativeproductionandthatderivedfromthe model. It shows an under prediction of cumulative oil produced for a given pressure drop. For this reason, the presenceofanaquiferisalsosuspectedtobecontributingto historicalproduction.

Fig.5: Graphical plot (Campbell) for field X after Regression

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Fig.6: Analytical plot results for field X after regression

5.4 WITH AQUIFER:

Amodifiedvan EverdingenandHurstaquifermodelwasset up to match historical production and the aquifer parameterswiththehighestuncertaintieswereregressedto matchhistoricaldata,allwithinwell definedboundariesthat suit reasonable engineering and geological judgment. The parameters regressed include The encroachment angle, outer/inner radius, and aquifer permeability. The plots in figures5and6weregeneratedaftertheregressiononthe differentparameters.

Afterdefiningtheaquifer,andregressingontheuncertain parameters, it can now be seen that the graphical plot (Campbell) nowfallsonastraightlineandthe Analytical plot nowfollowsthehistoricaltrend.Thematchedaquifer propertiescanbeseenintheanalyticalplotwhichshows: encroachment angle 360(degrees), calculated Aquifer volume(113975mmft3),Aquiferpermeability(9.93591mcl), andOIP(425.704MMSTB).Withthis,agoodhistoricalmatch hasbeenmadeandpredictionscannowbecarriedoutafter agoodfractionalflowmodelisobtained.

5.5 Results and discussion for field Y

5.6 A brief History of field Y

Reservoir Y is an undersaturated oil reservoir with the followingproperties:

Reservoir X is an undersaturated oil reservoir with the followingspecifications:

Initialpressure=4800psia

Temperature=2150F

Bubblepointpressure=2786.84psia API=51.84

InitialsolutionGasratio=768scf/STB Thickness=110ft

InitialOilinplace=762MMSTB

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Fig.7:PlotoftheDrivemechanismforfieldY

5.7 Energy Plot

After a proper aquifer fitting was performed on historical productionandaquiferparameters,apictorialviewofthe fractional distribution of energy responsible for hydrocarbonrecoveryoffieldYwasobtainedasshownin figure 7. The energy plot shows that fluid expansion was initiallythemajordrivemechanism,afterwhichwaterdrive becameamajorcontributortoproductionandPoreVolume compressibilitytheleast.

Fig.8: Analytical plot results for field Y before regression

Fig.9: Analytical plot results for field Y after regression 5.8 Analytical plot

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Fromtheproductionhistorymatch,thefollowingAnalytical plots as in figures 8 and 9 were derived for without/with Aquifer respectively. The plot without Aquifer shows a mismatchbetweenhistoricalcumulativeproductionandthat derived from the model. This signifies the presence of an aquiferandisalsosuspectedtobecontributingtohistorical production.Whileafterdefiningtheaquifer,andregressing on the uncertain parameters, it can now be seen that the Analytical plot nowfollowsthehistoricaltrend.Withthis,a good historical match has been made and predictions can now be carried out after a good fractional flow model is obtained.

5.9 Model Validity

BasedontheAnalyticalplot,pressuresimulationwasalso carriedouttodeterminethevalidityofthemodel,asshown belowinfigure10.BothHistoryandsimulationplotslieon thesamelineshowingagoodmatch.

Fig.10:PressureSimulationshowingthevalidityofthe model

From the pressure simulation, we can see a good match between historical pressure and simulated pressures for reservoir Y. More so, using the historical data, a good fractionalflowmatchwasalsoobtainedasshowninfigure 11.

Fig.11:ShowsFractionalFlowbetweenHistoricaland Simulatedpressures.

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6. Well Model (PROSPER): Thismodelthewellfor optimizationandperformance.

6.1 WellX1

6.2 IPR

Fig.12:DownholeSchematicsofWellX1

Fig.13:PlotofIPRshowingAbsoluteOpenFlow(AOF)

After PVT matching and defining the well properties, the well IPR was modeled as shown in figure 13 with the AbsoluteOpenFlowPotentialtobe46621.6STB/day. Sensitivitieswerealsocarriedonreservoirpressureandthe IPRcanbeseentovaryasshownbelowinFigure14

Fig.14:PlotsofIPRafterSensitivityonReservoirPressure

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6.3 VLP

Infigure15differentcorrelationswerematchedtothetest pointtoobtainthetubingtraversecurve,allgivingagood matchatthetestdatapoint.However,thePetroleumExperts 2correlationwasselectedasitshowstogivemorecorrect predictionsoveralargerrangeofdata.

Fig.15:VLPshowingtubingtraversecurve(PressureVs MeasuredDepth)

6.4 VLP/IPR Match

The IPR is the Well flowing bottom hole pressure (Pwf) in relation to production rate and the VLP curve shows the amountofpressurerequiredtoliftanamountoffluidtothe surfaceatagivenWHP.Thematchingiscarriedouttoshow the measured percentage difference concerning the calculated percentage difference of gas and Bottom hole pressure.VLP/IPRisneededforaccuratesensitivityanalysis asseeninfigure16showingagoodmatchatthetestrate andbottomholepressure.

Fig.16:VLP/IPRMatch

With the good match obtained for VLP/IPR, sensitivities were carried out, and lift curves were generated for Production Performance Prediction as shown in figure 17 below.

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Fig.17:VLP(Tubing)curvesforProductionPerformance Prediction

7. WELL MODEL(PROSPER)

7.1 Well Y1

7.2 IPR

Fig.18:DownholeSchematicforWellY1

Fig.19:PlotofIPRshowingAbsoluteOpenFlow(AOF)

AfterPVTmatchinganddefiningthewellproperties,the wellIPRwasmodeledasshowninfigure19withAbsolute OpenFlowPotentialtobe24052.6STB/day

Sensitivitieswerealsocarriedonreservoirpressureand theIPRcanbeseentovaryasshownbelowinFigure20.

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Fig.20: PlotsofIPRafterSensitivityonReservoirPressure

7.3 VLP:

As shown below in figure 21, different correlations were used to match the test point, to obtain the right tubing traverse curve. However, only the Petroleum experts 2 correlationwasabletocorrectlymatchthetestdatapoint.

Fig.21:VLPshowingtubingtraversecurve(PressureVs MeasuredDepth)

7.4 VLP/IPR Match

The IPR is the Well flowing bottom hole pressure (Pwf) in relation to production rate and the VLP curve shows the amountofpressurerequiredtoliftanamountoffluidtothe surfaceatagivenWHP.Thematchingiscarriedouttoshow the measured percentage difference with respect to the calculated percentage difference of gas and Bottom hole pressure.VLP/IPRisneededforaccuratesensitivityanalysis asseeninfigure22showingagoodmatchatthetestrate andbottomholepressure.

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Fig.22:VLP/IPRMatch

Withthegoodmatch,sensitivitieswerecarriedout,andlift curves were generated for production performance prediction,asshownbelowinfigure23.

Fig.23:VLP(Tubing)curvesforProductionPerformance Prediction

8. SURFACE MODEL (GAP)

Fig.24:GAPModelforFieldsXandY

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Figure 24 above is the generated GAP Model for the reservoirs and wells in the study. It consists of two reservoirs,eachofwhichisproducedbyonewell.Thetwo wellsaretiedtoacentralmanifoldbyseparateflowlinesand productionisdeliveredtoacentralseparator11kmaway. Theseparatorisoperatingatapressureof250psigandcan processabout18,000STB/dayofoil.Thismodelwillhelpto optimizerecoveryfromthesewellsbyprovidingchokeback options,tomeetthecapacityofthecentralseparator.

8.1 Without optimization (Wells fully open)

The combined production for both wells is about 20,806 STB/day, as shown below. This is above the separator capacityof18,000 STB/day andneedsto beoptimized by chokingbackonthewells.

8.3 PRODUCTION PREDICTION:

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Fig.25:GAPModelforFieldsXandYwithoutOptimization

8.2 After optimization (Choke back option)

The well combined rate to the separator is now 17011 STB/day,whichwasobtainedbychokingbackwellX1and leavingwellY1fullyopened,asshowninfigure26.

Fig.27:ShowsProductionPredictionfrom01 10 2008to 01 01 2030.

The plot above shows how the oil production rate will changeovertime,from2008to2030.Cumulativeproduction ofabout117MMSTBofoilwouldhavebeenproduced.

8.4 General Result and Discussion

Observation 1.

The results derived from MBAL analysis indicate that reservoirsXandYhavebeenaffectedbyadjoiningaquifers whichmayhavealsoaffectedthehistoricaldatausedinthe analysis. From the MBAL analysis, a significant aquifer permeabilityof10mband19.439mbandanencroachment angleof360degreesand359.739degrees respectively for reservoirsXandYindicatetheattainmentofa radial.The energyplotsindicatethatfluidexpansionandwaterdrive arethemajorsourcesofenergy.

Observation 2

The MBAL method was used to estimate the hydrocarbon reserveinpreferencetoothermethods.Othermethodsmay include Volumetric estimation, Numerical reservoir simulation,Carbonreservoirestimationmethod,Uncertainty modeling,Probabilisticmethod,MonteCarlotechnique,or Hypercube.Sincethebasicassumptionsforeachmethodare quitedifferent,themethodsmaynotaccountforthesame volumehencedifferentestimates.

Observation 3

After proper PVT matching with well properties properly defined, the IPR was modeled and the Absolute Oil Flow Potentialsshowed4662.6STB/dayand24052.6STB/dayfor fields X and Y respectively which represent the maximum flowrateofawellatazeroback pressureatperforations.

Fig.26:GAPModelforFieldsXandYwithOptimization.

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Observation 4

The VLP/IPR match relates the well flowing bottom hole pressure in relation to the production rate and pressure requiredtoliftanamountoffluidtothesurfaceatagiven WHP. It measures the percentage difference of the measured/calculatedrateofoil/gasatagivenBHP.Itshows 13970.0 and 13967.5STB/day for the measured and calculated respectively and a percentage difference of 0.017742 for liquid rate and 2671.30 and 2671.01Psig measured/calculatedandapercentagedifferenceof0.11086 forBHPpressure.

Observation 5

Theprocessseparatorcapacityis18000STB/daywhichis lessthanthe20806STB/dayproductionhencetheneedfor optimizationbychokingbackawellwhichbringsthetotal productionto17011STB/day.Thecumulativeexpectedoil production from 2008 to 2030 is seen to be at 117MMSTB/day.

9. CONCLUSIONS

Theconclusionsdrawnfromthework areasfollows: The work considered a comprehensive oilfield study by deploying IPM to optimize the fields. It modeled and optimizedthereservoir,wellandsurfacefacilityusingMBAL to model the reservoir, PROSPER for the well, and GAP to modelthesurfaceproductionfacility.



Flow expansion and water drive mechanisms are the predominant sources of energy for both reservoirsXandY.Theworkfurthershowsthatthe analytical method is not adequate proof for the usage of a particular model with aquifer support hence the need for a graphical method for verificationforbothreservoirsXandY.

CGR CondensateGasRatio

Ct TotalCompressibility

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

Thedatausedislackinginthegeologicaldimension of (Area in acres) needed to estimate HC reserve usingthevolumetricmethodwhichwould enable some comparative analysis of HC reserve using differentmethods.

Cw WaterCompressibility

EOR EnhancedOilRecovery

GA GasAnalysis

GAP GeneralAllocationPackage

QC QualityCheck

GOR GasOilRatio

IPM IntegratedProductionModeling

IPR InflowPerformanceRelationship

K Permeability

KrgmaxMaximumGasRelativePermeability

krwmax MaximumWaterRelativePermeability

MBAL MaterialBalance

MRTLL MinimumRatetoLiftLiquids

N STOIIP

Np CumulativeHydrocarbonProduction

OGIP OriginalGasinPlace

PETEX PetroleumExperts

Pres AverageReservoirPressure

PROSPER ProductionandSystemsPerformance AnalysisSoftware

PVT Pressure,Volume,andTemperature

PVTP Pressure,Volume,andTemperature

Package

Pwf

AverageFlowingBottomHolePressure

Q BottomHoleFlowRate

Qmax MaximumFlowRate

Qmin MinimumFlowRate

qg GasFlowRate

RD Outer/InnerRadiusRatio

RP ProducingGasOilRatio

Rs SolutionGasOilRatio

w WellRadius

Sgmax MaximumGasSaturation

Sgr ResidualGasSaturation

STOIIP StockTankOriginalOilinPlace

Swc ConnateWaterSaturation

T Time



Noalarmingvarianceisobservedshowingthatthe use of MBAL for estimation of HC reserve is appropriate else a dynamic model like Eclipse wouldhavebeenrecommended.

NOMENCLATURE

Bg GasFormationVolumeFactor

Bgi

InitialGasFormationVolumeFactor

BHP BottomHolePressure

Bo OilFormationVolumeFactor

Boi

InitialOilFormationVolume

Factor value:

T Temperature

U AquiferConstant

VLP VerticalLiftProfile

WGR WaterGasRatio

WHP WellheadPressure

WHR WellheadRates

Z CompressibilityFactor

Viscosity

GasDensity

LiquidDensity

Porosity

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