Copyright 2001, Society of Petroleum Engineers Inc.

This paper was prepared for presentation at the Annual TechnicalConference and ExhibitionConference held in New Orleans, 30-Sep to 03-Oct 2001.

This paper was selected for presentation by an SPE Program Committee following review ofinformation contained in an abstract submitted by the author(s). Contents of the paper, aspresented, have not been reviewed by the Society of Petroleum Engineers and are subject tocorrection by the author(s). The material, as presented, does not necessarily reflect anyposition of the Society of Petroleum Engineers, its officers, or members. Papers presented atSPE meetings are subject to publication review by Editorial Committees of the Society ofPetroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paperfor commercial purposes without the written consent of the Society of Petroleum Engineers isprohibited. Permission to reproduce in print is restricted to an abstract of not more than 300words; illustrations may not be copied. The abstract must contain conspicuousacknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O.Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.

AbstractThe Minagish Oolite is a thick undersaturated carbonate oilreservoir in the Minagish field in West Kuwait (Fig. 1)containing several billion STB. It is a mature but relativelyundeveloped reservoir. Since discovery in 1959, it hasproduced 10% of its OOIP under a combination of naturaldepletion, gas re-injection and aquifer drive. Initial reservoirpressure had declined by about 450 psi prior to the Gulf war in1990. The well blowouts following the war caused asignificant pressure drop of another 700 psi. Following theblowout, plans were made to redevelop the West Kuwait fieldsand increase the production rate starting in 2001 and to sustainthe plateau for at least 5 years. This strategy called for three-fold increase in the production rate of Minagish Oolitereservoir. Since the existing well inventory and the loss of thegas re-injection facility could not sustain the desired plateaurate, additional field development was required.

To achieve the production target, a multidisciplinary team wasformed to evaluate options. The recommended plan requiredthe drilling of additional producers and installing a field-wideperipheral waterflood. The reservoir, however, presented anumber of significant challenges to waterflooding, such as thepresence of a substantial and not well defined tarmat near theoil/water contact, and uncertainties of lateral and verticalheterogeneities. In 1997 a full-field simulation model wasdeveloped, but this model didn’t capture the water movementproperly because of insufficient reservoir data at that time. Asnew core was obtained, a refined reservoir description wasdeveloped. Building on lessons learned from the previousfull-field model and sector models, a new full-field model wasdeveloped which significantly improved well-by-well history

matches. Although containing twice as many grid cells, thenew model ran up to four times faster than the previous modelby making use of the Analytical Aquifer option within themodel, improved relative permeability curves and other modelrefinements.

This paper traces the history of the field and the systematicevolution of the development plan. The reservoir simulationefforts including modeling strategy, history matching events,prediction runs, future direction and challenges are alsoaddressed.

IntroductionNumerical simulators are an important tool for reservoirmanagement, providing management the ability to observehow alternate development plans and operating strategies willaffect future oil production and recovery. As additionalinformation is acquired and new technologies are developed, itis necessary to periodically update the reservoir simulationtools. This paper identifies the reasons for building a newmodel, the differences between it and the previous model, anddocuments the data-sources, files and the methodology used toconstruct the new model.

The previous model (FFM 97) was constructed andinitialized in 1997. The model was based on a course 12-layerreservoir description and history matched reservoirperformance up through the start of dumpflood waterinjection. In predictive mode, however, the model did notadequately predict the rapid water movement in the northeastquarter of the field or the arrival of initial water in theperipheral producers. Sector models constructed at the sametime indicated that a refined reservoir description thatincorporated the observed barriers and high permeabilitystreaks should provide an improved match of the observedwater movement.

Since completion of the FFM 97, significant drillingactivity and data acquisition has improved the understandingof the reservoir. Between January 1998 and August 2000, 25wells have been drilled (including 7 wells being cored) and 10wells were RFT’d across the entire reservoir. This additional

SPE 71632

A Full Field Simulation Model of the Minagish Oolite Reservoir in KuwaitSaad AL-Mutairi (KOC), Fahad AL-Medhadi (KOC), Hamad AL-Ajmi (KOC), David Meadows (BP Amoco), Oosthuizen,Ulrich R (KOC)

2 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

data, particularly the core, has significantly improved thegeological understanding of the reservoir. One significantimprovement has been in defining the areal extent and verticaldistribution of the tarmat, which is the major controlling factoraffecting water influx and pressure support from thesurrounding aquifer and dumpflood injection rates.

Building upon key learnings from the previous FFM 97and Sector models and incorporating the newly acquired data,a new Fullfield Model was constructed. Referred to as theFFM 2000, the model incorporated a 25-layer reservoirdescription and utilized different methodology to simulateaquifer influx, construct relative permeability curves, faulttransmissibility and kv/kh.

The FFM2000 represents the culmination of significantwork by the Minagish multidisciplinary team conductingreservoir surveillance, reservoir analysis and mapping andreservoir simulation.

Objective Of New ModelThe Minagish (MO) reservoir is an integral part of the WestKuwait 500 Development Plan. The Minagish contribution tothe Plan requires three fold increase in production rate andmaintain the plateau as long as possible. In order to maximizethe value of the Plan, a quality reservoir management tool wasrequired which could with confidence provide the reservoirmanagement team with accurate oil, gas and water ratepredictions, track the advance of water movement across thefield, and provide early warning of facility constraints.

The objectives of the new model were threefold:

History match performance on a well-by-well basisImproved the model visualizationReduce simulation run-time

History matching on a well-by-well basis, rather than on afield level, was required in order to generate accurate well-by-well predictions. By matching over 40 years of performance,confidence is gained that the reservoir description and baseassumptions are valid and when placed in a predictive mode,will generate accurate forecasts.

Improved visualization of the model was desired to enablethe team to visual the movement of fluid through the reservoir.In addition to the typical well-by-well performance plots ofproduction (oil, water and gas) and pressure vs time, it wasalso desired to construct routines which allowed observationof the static data (structure, φφ, permeability, thickness,net/gross) and the dynamic data (Sw, Sg, Rs, and pressure).

Reduction in simulation run-time was desired as a meansof speeding up the history matching process. It would alsohave the added benefit of reducing the time required to run a

predictive run. The goal was to reduce the simulation timeduring the history match period to less than 7 hours and inpredictive mode to 4 hours. This would allow the simulationengineer the ability to evaluate two history match runs perday, while providing the team with a “real time” predictivetool, capable of providing same day answers to reservoirquestions.

The FFM 2000 has history matched well-by-well oil andwater production, gas and water injection, aquifer influx,reservoir pressure, and RFT, TDT and PLT surveillance data.The new model has successfully predicted initial water arrivalin the applicable flank wells. The use of the AnalyticalAquifer significantly decreased simulation time whileimproving the interpretation of aquifer influx on the east andwest flanks. Visualization routines have been developedwhich provide map view and cross-section views of the keystatic and dynamic parameters.

Grid SelectionThe FFM 2000 used the same basic GRID dimensions as theFFM 97 (44 in the x(i) direction x 84 in the y(j) direction)(Fig. 2). Each grid block was 200 meters x 200 meters. TheGRID dimension in the z(k) direction, however, was increasedfrom 12 to 25 to accommodate the additional barriers and highpermeability intervals included in the new reservoirdescription.

The FFM 2000 used the Carter-Tracy Analytical Aquiferoption to define the aquifer boundary for each layer at the zerooil column height (9,950’ tvdss) (Fig. 2). No LGC or LGRwas used in this model, whereas the LGC option was used inthe FFM 97 to decrease the number of cells in the aquifer.

Reservoir DescriptionThe ability to develop an enhanced reservoir description wasmade possible by the acquisition of significant core since thedescription for the FFM 97 was developed. Since 1999,emphasis has been placed on coring each of the new injectors,since their location on the flanks would provide insight intothe development of the barriers and tarmat along the flanks, aswell as information regarding the reservoir quality of theaquifer. Although detailed core description is still in progress,sufficient information was obtained from the preliminary coredescription to enhance the understanding of the barriers,particularly on the western flank of the field. A mapillustrating the location of the cored wells is shown in (Fig. 3).

LayeringOne of the major key learnings from the FFM 97 and theSector models was the influence which barriers and highpermeability streaks have on water movement within theMinagish Oolite reservoir. Consequently a new 25-layerreservoir description was developed which included all knownareally sizeable barriers and high permeability streaks (seeFig. 4).

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 3

PorosityThe additional well penetrations since 1997 has provided asignificantly improved data source for mapping parameterssuch as ΦΦ. The data points now available are more uniformlydistributed across the Minagish Oolite and have been loggedwith a consistent logging suite, providing the petrophysicistwith improved accuracy in calculating ΦΦ. The end result issmoother maps of ΦΦ, with less bulls-eyes, which typicallyindicate data quality issues rather than actual reservoiranomalies.

PermeabilityPermeability is one of the most critical parameters indeveloping a reservoir description, since it influences fluidmovement. The most accurate permeability measurements arefrom core, however, the majority of wells have not been coredthrough the entire Minagish Oolite section. In the non-coredwells, estimation of permeability is based on empirical logrelationships derived from the cored wells. Permeabilityprediction from logs in the Minagish Oolite, however, hastraditionally been problematic as there is no simplerelationship between log responses and measured corepermeability in this formation. The primary causes of this aregrain size changes and varying amounts of microporosityleading to permeabilities varying by up to three orders ofmagnitude at any given porosity.

The Permeability derived from log was improved usingstatistical analysis. The end result was a permeabilitypredictor which was twice as good as the previous method.

Initial Water SaturationOne of the major accomplishments since development of theFFM 97 was the construction of saturation height curves forthe Minagish Oolite. These curves are based on capillarypressure measurements from special core analysis andillustrate the water saturation that would be expected at anyheight above the 0’ oil column height (Fig. 5).

In the FFM 97, the oil/water contact was accepted asbeing around 9,810’ tvdss, even though there were numerousoccurrences of mobile oil below 9,810’. In the FFM 2000, anoil/water contact was not input. Rather, a map of Sw initialwas generated for each layer in ZMap based on the empiricalSw vs Height curve developed for that layer. All points thatfell below the base of the oil column at –9,951’ tvdss wereassigned an initial Sw of 100%. Points in the reservoirbetween 9,910’ to 9,951’ appear to be in a transition zone,with Sw > 60% and little (if any) mobile oil. Points in thereservoir below the previously defined oil/water contact at –9,810’ are now indicated to contain mobile oil, although withhigh Sw.

Vertical Permeability (Kz)In the FFM 97, KZ = KX. The assumption that KV/KH was 1was based on a general trend of the available core plug data.

Work during development of the FFM 97, however, showedthere was actually degradation in KV/KH with increasingpermeability (Fig. 5-8). A relationship for the four rock types(grainstone, packstone, oolitic and micritic) is developed.Building on the previous work, the 2,500 available core plugswith measured KV and KH were sorted by model layer, whichresulted in a similar linear relationship of decreasing KV/KH,but with less data scatter. The same data was plotted oncoordinate scale to utilize the TREND function in EXCEL.Linear relationships in the form of KZ = C1*KX + C0 weregenerated for each layer.In the FFM 2000, KZ was adjusted for the above relationshipsusing Multiply and ADD commands. The use of the aboveKV/KH relationships eliminated early water arrival in MN-42and improved the water arrival in MN-28 and MN-30 towithin 6 months of actual observed water. The improvedKV/KH also resulted in minor improvement of the pressurehistory match in almost every well,

Adjustment of Kair to Koil

Laboratory measured permeability is typically reported asKair. In the reservoir, the pore space is occupied by oil andconnate water, while in the aquifer the pore space is occupiedby brine. Special core analysis conducted on core from MN-61, MN-62 and MN-63 was used to determine the relationshipbetween Koil vs Kair.

(Fig. 9) illustrates the relationship between Kair and Koil byrock type based on pore throat radius. Excluding outliers,three distinct trends were found for the Mega, Macro andMeso pore throat types, with correlation coefficients above0.85. Since a given model layer may include multiple porethroat types, it was decided to use a general correlation in theFFM 2000 based on all the data. This correlation was Koil =0.7783 * Kair, with a correlation coefficient of 0.969. Theconversion from Kair to Koil was applied globally using theMULTIPLY keyword.

Adjustment of Kair to Koil

The FFM 2000 uses a similar adjustment to correct from Kair

to Kbrine. (Fig. 10) illustrates the relationship developed fromspecial core analysis on core from MN-61, MN-62 and MN-63. The relationship Kbrine = 0.5401* Kair

0.9335 was used in theCarter – Tracy Analytical Aquifer option to adjust thepermeability at the grid face between the aquifer and thereservoir. In general, Kbrine is approximately 50% of Kair.

Carter-Tracy Analytical Aquifer ModelThe Carter-Tracy Analytical Aquifer option uses the Carter-Tracy material balance method to estimate the volume ofaquifer influx at each grid face on the reservoir / aquiferboundary based on estimation of Dimensionless Time andDimensionless Pressure. The FFM 2000 incorporated 12analytical aquifers, one for each of the AH layers. The aquiferproperties (compressibility, porosity, permeability, initialpressure, depth, radius, etc.) for each analytical aquifer werederived from the available core data within the aquifer using

4 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

the keyword AQUCT. The definition of the aquiferconnection to the reservoir was entered using the keywordAQUANCON.In AH layers that were completely surrounded by tarmat, theanalytical aquifer was turned off, since the model would yieldan error if no aquifer flow could enter an analytical aquifer.Based on the tarmat maps, the analytical aquifers below AHlayer 6 were turned off. In essence, the tarmat acts as aneffective barrier to aquifer influx into the Minagish Oolitereservoir. Only the lower permeability layers at the top of thereservoir (which did not have tarmat develop due to theirlower permeability) are experiencing aquifer influx.

Since the Carter-Tracy aquifer method calculates aquiferinflux at the aquifer boundary and not within the aquifer itself,it was therefore possible to set each of the grid cells within theaquifer inactive using the ACTNUM keyword. Sinceapproximately 1/3 of the model grid cells are within theaquifer, setting the aquifer grid cells inactive had the effect ofsignificantly decreasing simulation time.

The tarmat in the Minagish Oolite consists of a thickimmobile bituminous interval typically found in the lowerportion of the higher permeability layers. Significant workhas been devoted to understanding the deposition,characteristics and location of the tarmat in the reservoir.Since the tarmat is basically immobile and should act as aneffective barrier to aquifer influx, the FFM 2000 utilisedrecently developed maps of the tarmat location to set the gridcells containing tarmat inactive using the keyword ACTNUM.Setting the tarmat grid cells inactive has the effect ofremoving these grid cells from being included in the STOOIP,reduces the number of active grid cells requiring simulationand provides a barrier to aquifer influx. Fig. 11 shows arepresentative map of Layer 10 and an east-west cross-sectionshowing the location of the tarmat in the bottom layers.

Initial ConditionThe FFM97 input initial conditions using the equilibrationmethod, in which the initial conditions were input as tables ofincreasing depth, such as Pressure vs Depth, API vs Depth andGOR vs Depth. Alternate interpretation of the available datasince construction of the FFM97 suggested different initialconditions that were not necessarily a function of increasingdepth only. API for instance was found to decrease slightlywith increasing depth, but was more affected by the proximityof the tarmat. Swc was found to increase with depth, but thiswas a natural function of Swc vs Height above Free Water foreach rock type.For this reason, the FFM 2000 input the initial conditions astables consisting of values for each grid cell for each layer.Where possible, tables of a property vs depth or pressure wereused.

API TrackingThe API Tracking option was used in an attempt to predict theAPI of produced crude over time. This would allow KOC todevelop a profile of crude production by API for each field foruse in Crude Export Quality assessment.Eclipse 100 does not output field level API values, only wellor connection level. To overcome this limitation, a routinewas developed which combines the rate and API for each wellinto a Field level API estimate.

Fluid PropertiesOilThree tables of oil PVT properties were used in the FFM2000. These tables represented

1) light attic oil above 9,350’ tvdss2) oil between 9,350’ tvdss and free water3) oil in the transition zone immediately above the

tarmatPVT of oil in the tarmat was not input, since the tarmat isconsidered immobile and has been zeroed out in the model.WaterWater PVT functions describing the Formation VolumeFactor, viscosity and compressibility changes with pressurewere input based on 2 downhole aquifer water samplescollected from MN-95. The downhole samples, althoughcollected using pressurized sampling chambers, weretransferred to unpressurized chambers at the surface,allowing any dissolved gases to escape. Since the fluids wereno longer at reservoir conditions, no PvT analysis wasconducted.Instead, the water analysis was input into a water analysisspreadsheet to estimate the FVF, compressibility andviscosity. This data most likely does not accurately representthe true properties of the Minagish Oolite aquifer.GasThe Minagish (MO) reservoir was originally undersaturated.Between 1967 and 1990, 325 Bcf of dry gas from theMN(MO) reservoir and other West Kuwait reservoirs was re-injected to maintain reservoir pressure. This gas re-injectionresulted in the creation of a secondary gas cap. To model thegas injection, movement of the gas within the reservoir andthe production of free gas, the PvT properties of a generic gaswere input. The formation volume factor and viscosity werecalculated using Standing’s z-factor correlation and Beal’scorrelation respectively.

Reservoir PressureThe initial PR in the Minagish (MO) was 4,747 psig at a depthof 9,422’ tvdss. The initial PR in each grid cell was inputusing a table of PR vs Depth. The PR at depths above 9,422’tvdss and below 9,422’ tvdss but above the free water level at9,951’ tvdss were adjusted based on an oil gradient of 0.318psi/ft. The PR of grid cells below the free water level at 9,951’tvdss were adjusted based on an oil gradient to 9,951’ tvdssand a water gradient of 0.496 psi/ft below 9,951’ (Fig. 12).

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 5

Relative PermeabilityThe development of representative relative permeabilitycurves is the single most important step in developing anaccurate history match and in accurately predicting futureperformance. Too often, the absence of relative permeabilitydata forces the engineer to seek analog data from offset rockswhich will hopefully represent the fluid flow characteristicswithin the reservoir of interest. In the FFM97, the 9 relativepermeability curves from MN-28 were supplemented with 39relative permeability samples from the Ratawi limestone ofWafra Field. The end result was development of relativepermeability curves that better represented the Ratawi than theMinagish (Minagish Oolite).

To develop representative relative permeability curves for theFFM 2000, the first step was to group the samples accordingto similar rock types. A plot of Swi vs. Height above FreeWater showed the sample points fell into two distinctgrouping based on the Winland pore throat categories, Megaand Macro

The samples were then normalized and compared with eachother based on their estimated pore geometry. An overlay ofthe samples identified a trend of decreasing permeability withdecreasing pore throat radius (see Table 1). A semi-log plotof Kron vs Swn was generated to quality control check thesamples. Several samples were found to have anomalousshapes indicating possible testing errors. The samples werethen de-normalized to a Swi of 5% (the minimum Sw observedin the field) and the Sor to water for each respective test. Ninecurves were generated for the ECLIPSE model utilizing theabove method.

History Match ProcessThe approach to history matching used with the FFM2000 isdriven by the special features of the production history of thereservoir. These are summarized in (Fig. 13) on the next page.The field's history falls into four main periods;• An early period of production under natural depletion. Thisruns from first oil (in August 1959) to the startup of gasinjection (July 1967). Production during this period isintermittent.• A lengthy period where production, though still intermittent,was approximately matched by injection of surplus gas fromthe Burgan field.• The Gulf War period, consisting of a shut-in period, ablowout and another, longer shut-in period;• Post-war continuous production up to the end of history.

It is possible to exploit the form of this production history tosimplify the process of history-matching. Since there is nowater production to date in this reservoir, the history matchwill be purely a pressure match. However, incipient waterbreakthrough has been observed in certain flank wells, namelyMN-28 and MN-30.

Accordingly, the object of the exercise was to match observedpressure under the historical production regime, and to end thehistory period without significant volumes of water productionfrom the flank wells. However, it would be desirable for thesewells to be on the point of producing their first water.Once the reservoir starts full-scale waterflood operations,performance will be dominated by water movement.Unfortunately there are loss in field data available at presentwhich might be used to diagnose the mechanisms of watermovement in the reservoir.

History Matching ControlHistory matching was mainly accomplished by matching thepressure response during the early depletion period. Thefollowing reservoir parameters were varied in order to get ahistory-match;• Crestal fault transmissibilities.• Analytical aquifer porosities and permeabilities. These werevaried by editing the file AQUIFER.INC. In principle theaquifer properties could be varied in any of the 12 aquiferzones.• The decision was taken early on not to change the in-placeoil volumes to achieve a history-match.• Reservoir vertical permeability has been correlated tohorizontal permeability for each layer. This from severalavailable core analyses data .

History Match ResultsSeveral history matching events noticed in this model. Theseare:

• All wells have a good and acceptable pressure match.Fig 14.15,16 shows samples of pressure matching.

• The secondary gas cap extent predicted accurately.This by matching the RFT of well showing gas in theupper layer . (Fig 17)

• Initial water arrival in the applicable flank wells wasmatched example of that is MN-28 .

• The North-East parts of the reservoir exhibit a veryeffective barrier. This barrier caused to shut-in twodump-flood injectors because of bad performance, sincethe water is sweeping only layers above that barrier andcontinue rapidly taward the crest. This movement ofwater was matched accurately in the model. A reservoircross section showing this movement of water isillustrated in Fig. 18.

PredictionPredictions were made by specifying the maximum liquid rateproduction for each tubing size. Lift curves has been generatedfor each type of well, natural flow or ESP or power injector.The model was run assuming the current operating conditions.Result indicated desired plateau length of 6 years. Also itshowed that a constraint on gas production as part of noflaring strategy effect the production target rate. Whichrequires a gas production management and this of course

6 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

reflected on the perforation strategies. The new model is beingused to locate the remaining injection and producing wells andin developing offtake strategies, gas cap managementstrategies, plateau extension options and infill and horizontaldrilling options. Fig. 19 shows the basic development plan forthis reservoir

AcknowledgmentOur gratitude goes to the management of the Kuwait OilCompany and to Oil Ministry of the State of Kuwait forpermission to publish this work.

References1] Matar, S., et al: Multidisciplinary approach for accelarateddevelopment of a giant carbonate reservoir in Kuwait - SPE53199, MEOS 1999[2]. Al-Shammari, Ali : Active Uncertainty management of anearly water flood development of Minagish field, westKuwait. SPE 63220, ATCE Dallas October 2000[3] Al-Ajmi, H., Brayshaw and Gaur: The Minagish FieldTarmat: Formation, Distribution and Impact on Waterflood -paper presented at GEO’98, the 3rd Middle East GeosciencesConference & Exhibition, Bahrain, 20-22 April 1998 (inproceedings).[4] D.F. Maye, A Full-Field Reservoir Simulation Model ofthe Eastern Shallow Oil Zone in the Elk Hills Field,California . spe 35671

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 7

N

KUBER ISLAND

UMM AL-MARADEM ISLAND

QAROH ISLAND

Bahrah

Khashman

Medina

RaudhatainAbdali

Dharif

Wafra

Umm Gudair

Abduliyah

Minagish

AL-KHIRAN

Ratqa

GreaterBurgan

Sabiriyah

FAILAKA ISLAND

Saudi Arabia

Iraq

Kuwait

ArabianGulf

Figure 1

Figure 2

8 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

1.1

barrier 2.2

2.1

2.3

barrier 3.2

3.3

3.1

barrier 5.2

5.3

5.1

barrier 6.3

high k streak 6.1

6.2

6.4

)barrier-like in some mapped places (7

barrier 8.2

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Upper oolites 9

Lower oolites 10

barrier 11.1

high k streak 11.2

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Figure 3

Sw vs Height Above Free WaterMinagish (MO) Reservoir

9,000

9,050

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9,200

9,250

9,300

9,350

9,400

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Dep

th (f

eet t

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)

AH1

AH2,5,6

AH3

AH7,8

AH9

AH10

AH11

AH12,13

IOWC assumed in FFM97 @ -9810' tvdss

Figure 4

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 9

KV vs KH Minagish (MO) Core Plugs

0.1

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KH (mD)

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Selected Data

KV/KH = 10.0

KV/KH = 1.0

KV/KH = 0.1

KV/KH = 0.01

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KV vs KH Minagish (MO) Core Plugs

0.1

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KV/KH = 10.0

KV/KH = 1.0

KV/KH = 0.1

KV/KH = 0.01

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P

Figure 5: KV/KH of Grainstones

Figure 6: KV/KH of Packstones

10 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

KV vs KH Minagish (MO) Core Plugs

0.1

1.0

10.0

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KV/KH = 10.0

KV/KH = 1.0

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KV vs KH Minagish (MO) Core Plugs

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KV/KH = 10.0

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Figure 7: KV/KH of Oolite

Figure 8: KV/KH of Micrite

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 11

Figure 9

Kbrine vs Kair

y = 0.5401 x0.9335

R2 = 0.9484

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Kair vs Kbrine @ 4500 psi

Power (Kair vs Kbrine @ 4500 psi)

Figure 10

Koil vs K air

by Pore Throat Classification

y = 0.7791 x

R2 = 0.9169

y = 0.6754 x

R2 = 0.8413

y = 0.6374 x

R2 = 0.8542

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R2 = 0.969

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Mega Pore Throat Outliers Not Included in Trend

Macro Pore Throat: 2-10 microns

Macro Pore Throat Outliers Not Included in Trend

Meso Pore Throat: 0.5- 2 microns

Micro Pore Throat: 0.2-0.5 microns

Linear (Mega Pore Throat: 10-80 microns)

Linear (Macro Pore Throat: 2-10 microns)

Linear (Meso Pore Throat: 0.5- 2 microns)

Linear (Composite)

Minagish Oolite trend for FFM 2000

12 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

Figure 11

Reservoir Pressure vs DepthMinagish (MO) Reservoir

9,000

9,100

9,200

9,300

9,400

9,500

9,600

9,700

9,800

9,900

10,000

10,100

10,200

10,300

10,400

10,500

4,500 4,600 4,700 4,800 4,900 5,000 5,100 5,200 5,300

Reservoir Pressure (Psig)

Dep

th (

tvds

s)

FREE WATER LEVEL

Figure 12

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 13

-

-

-

-

-

/

3,600

3,800

4,000

4,200

4,400

4,600

4,800

59 64 69 74 79 84 89 94 99

PR

(psia@

9422

'tvdss)

Pinit4,747

Minagish MO Production History

Figure 13

Figure 14

14 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

Figure 15

Figure 16

SPE 71632 A FULL FIELD SIMULATION MODEL OF THE MINAGISH OOLITE RESERVOIR IN KUWAIT 15

Start Injectionin 1971

In 1974

In 1977

In 2000 RFTshows gas inlayer 2 only

Figure 17

16 SAAD AL-MUTAIRI, FAHAD AL-MEDHADI, DAVID MEADOWS SPE 71632

Figure 18

80% of theinjected watersweep abovethe barrier

Minagish (MO) Field Summary

02000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Stb/d orMscf/d

Base Oil Rate

Base Gas Rate

Base Water Rate

Base Water Inj Rate

Three fold increase in oilproduction start in mid 2001

Maximum water production due tofacility constraints

Figure 19

5 Year Plateau