trends in reservoir management - schlumberger/media/files/resources/oilfield_review/ors92/... · 10...

As oil becomes harder to find and known reserves must be more

phase than the industry has ever experienced.

Trends in Reservoir Management

Twenty-five years ago, oil companies couldhope for continuing discoveries of giantfields and highly profitable exploitationonce oil was found. Today, the tables haveturned. More than three-quarters of currentadditions to the world’s oil reserves comesfrom better management of existing reser-voirs. Less than one quarter comes from dis-covery of new oil. Profitability in today’sharsher economic climate depends onincreasing recovery from producing fields. Ifrecovery is being optimized better now thanin years past, at least four factors couldclaim credit:

First is the oil companies’ clear vision thata cross-disciplinary approach must prevail. Ifproducing oil requires the expertise of geol-ogists, geophysicists, petrophysicists, reser-voir engineers and numerous other special-ists, it is best that the experts work togetherrather than separately. It sounds simple, butentrenched management structures canmake this difficult to put into practice.1

Second is dramatic innovation in interwellmeasurements, notably three-dimensional(3D) seismics, and perhaps, in the future,interwell seismic tomography. Developedinitially to aid exploration and improveunderstanding of complex structure, 3Dseismics is being used increasingly to

Prepared with assistance from:

Peter Briggs, Manager of Reservoir TechnologyBP Exploration Uxbridge, England

Tony Corrigan, PartnerCorrigan AssociatesDitchling, England

enhance reservoir description.2 Still lackingthe resolution to systematically pick out finesedimentological structure, it has neverthe-less revolutionized the mapping of faultsand illuminated well-to-well correlation incomplex environments where logs andcores offer poor or negligible correlation.Three-dimensional seismic techniques havealso aided fluid monitoring in certainenhanced oil recovery (EOR) schemes, buthave yet to be proved capable of monitoringconventional water- and gasfloods.3

The third factor is increasing computerpower, which has made possible the disci-plines of geostatistics and reservoir simula-tion. We may tire of the computer industry’sdramatic predictions of undreamed-of com-puter power, but must remember that so farthe predictions have come true. Computerpower has allowed geologists and reservoirengineers to create a range of probabilisticmodels that fill space between wells wheremeasured data are lacking. The models areused as input to fluid-flow simulations,another activity that benefits directly fromadvances in computer technology.

The fourth factor is horizontal well tech-nology, which changes all the rules aboutproducing from both simple and complexstructures. The industry has learned how to

Michael Fetkovich, Sr. Principal Reservoir EngineerPhillips Petroleum Company Bartlesville Oklahoma, USA

Michel Gouilloud, Executive Vice-PresidentSchlumberger Ltd Paris, France

drill these wells and is mastering how tocomplete and stimulate them. Less clear ishow horizontal wells can best benefit flood-ing strategies and enhanced oil recovery(EOR) schemes.4

Given the increasing complexity of devel-oping many of today’s discoveries, particu-larly those in deep formations and offshore,these innovations are giving reservoir man-agement the edge it needs to make exploita-tion worthwhile. The basic principles ofreservoir management, though, remainunchanged. Every reservoir progressesthrough the same phases in its producinglife and similar decisions must be made atany given phase (next page).

The most critical occur during the earliestphases—discovery and appraisal—when theleast data are available. With scanty geo-logic information, with the exploration seis-mic survey, and with cores, logs and testsfrom a handful of wells, oil companies haveto rapidly assess reservoir size and pro-ducibility, decide well locations and drivemechanism, and then commission surfacefacilities that may cost billions.

As the field is drilled—the developmentphase—an abundance of data becomesavailable, allowing more detailed under-standing of production. Simulation that was

Oilfield Review

Tien-when Lo, Project Scientist Exploration and Production Technology DepartmentTexaco Inc.Houston, Texas, USA

Björn Paulsson Senior Research GeophysicistChevron Oil Field Research CompanyLa Habra, California, USA

In this article, Array-Sonic and Formation MicroScan-ner are marks of Schlumberger.

1. Thakur GC: “Reservoir Management: A SynergisticApproach,“ paper SPE 20138, presented at the 1990Permian Basin Oil and Gas Recovery Conference,Midland, Texas, USA, March 8-9, 1990.

2. Robertson JD: “Reservoir Management Using 3D Seis-mic Data,“ Journal of Petroleum Technology 41 (July1989): 663-667.

3. Greaves RJ and Fulp TJ: “Three-Dimensional SeismicMonitoring of an Enhanced Oil Recovery Process,”Geophysics 52 (September 1987): 1175-1187.

4. Horizontal well technology is described in severalarticles in the July 1990 issue of Oilfield Review.

5. Hansen T, Kingston J, Kjellesvik S, Lane G, l’Anson K,Naylor R and Walker C: “3D Seismic Surveys,” Oil-field Review 1, no. 3 (October 1989): 54-61.

carefully exploited, reservoir management is entering a tougher, more challenging

DiscoveryAppraisal

Development

Decline

Plateau

nPhases in afield’s exploitation.

previously based on a simple reservoirmodel because of limited data can nowgrow more sophisticated. As the field entersthe so-called plateau phase, when produc-tion reaches planned levels, there is also anaccumulation of production data that simu-lation can history match. The net result ismore reliable prediction of future produc-tion. This helps prepare the way for thedecline phase, when the oil company mustdecide how to extract the most from itsdying asset. Issues range from whether toinfill drill—and if so, where—to modifyingsurface facilities, and finally perhaps toplanning EOR (see “A Niche for EnhancedOil Recovery in the 1990s,” page 55).

January 1992

Nansen Saleri, Manager of Reservoir EngineeringChevron Exploration and Production Services, Co.Houston, Texas, USA

John Warrender, Staff Geologist Reservoir DevelopmentConoco (U.K.) Limited, Aberdeen, Scotland

More or less paralleling this saga is agradual narrowing of focus for the datagatherers—a continuing quest for finerdetail. At every scale, their primary quest isto better understand reservoir heterogeneity.Heterogeneity governs not only connectiv-ity—the degree to which the permeablezones are interconnected and connected towells—but also horizontal and verticalsweep efficiency and residual oil saturationin swept zones. All are critical factors thatdetermine recovery. The ongoing challengefacing operators is learning enough aboutthe heterogeneity that may influence thenext phase of the reservoir’s life (next page).

Koenraad Weber, Professor of Production GeologyDelft Technical University, The Netherlandsand Consultant in Reservoir GeologyShell Internationale Petroleum Maatschappij BV,The Hague, The Netherlands

At the appraisal phase, the concerns aretwofold: determining reservoir boundaries,including those of the driving mechanism,and determining large-scale heterogeneitiesthat complicate the reservoir’s internal struc-ture. This means identifying the main depo-sitional units and the boundaries betweenthem, and identifying faults and fractures.

The extremities of the reservoir and itsfaults are exclusively provided by seismicdata, although gross reservoir size and dis-tances to certain boundaries can be esti-mated from well tests.5 A system of sealing orpartially sealing faults can completely changethe way a field should be produced. Know-

10 Oilfield Review

nReservoir heterogeneities versus scale and the data required to characterize them. At the beginning of a field’s life, attentionfocuses on large-scale structure. As a field matures, attention shifts to finer detail. (From Weber and van Geuns, reference 22.)

Fracturing

-tight

Boundaries genetic units

Textural types

Mineralogy

Laminationcross-bedding

Baffles within genetic units

Permeability zonation within genetic units

Sealing fault

Semi-sealing fault

Nonsealing fault

Sweep efficiency

Rock samples

Well loggingReservoir pressure

Production data / tests

Recovery

DataReservoir heterogeneity

Strong effect Moderate effect

Microscopicheterogeneity

ing the fault system, then determining iffaults are sealing may be the most importantinformation an operator should acquire as itcontemplates development. This is illus-trated by yearly estimates of recoverablereserves required of operators by the UKgovernment. These estimates show trendsthat correlate with the field’s tectonic historyand its faulting system in particular.6

In tectonically quiescent areas with littlefaulting, operators tend to increase reservesestimates (below). Many of these North Seafields were deposited as submarine fans,and the sands have a more or less uniformmorphology. They have limited faulting andproduce with waterdrive that leads to more

January 1992

illion

Forties

Claymore Field

Dunlin N W Hutt

Tartan

Thistle

efficient drainage resulting in a continualupgrading of reserves. In tectonically activeareas, reserves estimates tend to decline.Operators found these fields to be morefaulted than expected, and in some casessaddled with high permeability contrasts.

The industry’s solution is 3D seismics, lotsof it. Take Shell Expro’s Cormorant field thatlies in the highly faulted Brent province inthe northern North Sea in the UK sector.The southern part of the field was devel-oped in the 1970s before 3D seismicsbecame commercial, and production startedin 1980. Reserves estimates dropped steadilyduring the buildup to production as reser-voir engineers gradually perceived the

aureen

Magnus

nNorth Sea opera-tors’ changing esti-mates of theirfields’ recoverablereserves—the spotsindicate beginningof production. Intectonically quiet,relatively non-faulted fields (red),estimates tend togo up becauseoriginal forecastswere conservative.In highly faultedfields (greens), esti-mates go down asoperators come togrips with reservoircomplexity. Thesetrends show howimportant it is foroperators to under-stand complexstructure as earlyas possible in thelife of a field. Fortypical North Seacrudes, 1 tonne isequivalent to 7.53barrels. (From Corri-gan, reference 6.)

faulted nature of their asset. By 1981, whenBlock IV in the north of the field was drilled,reservoir managers had the benefit of a reli-able 3D survey (next page, top). This reaf-firmed the complex faulting and enabledreservoir managers to ensure that injector-producer well pairs were at least in thesame unit.7

Another 3D seismic survey was commis-sioned in 1984 to provide yet more detail,the previous survey having suggested thatthe average distance between faults wasabout the same as or even less than the sur-vey line spacing. The more closely spacedsurvey showed the same big picture, butenough detail was different to merit fine-

6. Corrigan T: “Factors Controlling Successful ReservePrediction: A Cautionary Tale from the UK NorthSea,“ presented at the 2nd Conference on ReservoirManagement in Field Development and Production,Norwegian Petroleum Society, Stavanger, Norway,November 14-15, 1988.

7. Gaarenstroom L: “The Value of 3D Seismic in FieldDevelopment,” paper SPE 13049, presented at the59th SPE Annual Technical Conference and Exhibi-tion, Houston, Texas, USA, September 16-19, 1984.Ruijtenberg PA, Buchanan R and Marke P: “Three-Dimensional Data Improve Reservoir Mapping,”Journal of Petroleum Technology 42 (January 1990):22-61.Grant I, Marshall JD, Dietvorst P and Hordijk:“Improved Reservoir Management by IntegratedStudy: Cormorant Field, Block 1,” paper SPE 20891,presented at Europec 90, The Hague, The Nether-lands, October 22-24, 1990.

8. “CAT-Scanning the Subsurface,” Oilfield Review 2,no. 2 (April 1990): 4-6.

9. Paulsson BNP, Fairborn JW, Cogley AL, Howlett DL,Melton DR and Livingston N: “McKittrick Cross-WellSeismology Project: Part I. Data Acquisition andTomographic Imaging,” Expanded Abstracts, 60thAnnual International Meeting and Exposition, Societyof Exploration Geophysicists, San Francisco, Califor-nia, USA, September 23-27, 1990: 26-29.Lo T-w, Inderwiesen PL, Howlett DL, Melton DR, Liv-ingston DN, Paulsson BNP and Fairborn JW: “McKit-trick Cross-Well Seismology Project: Part II. Tomo-graphic Processing and Interpretation,” ExpandedAbstracts, 60th Annual International Meeting andExposition, Society of Exploration Geophysicists, SanFrancisco, California, USA, September 23-27, 1990:30-33.

10. Lasseter T, Karakas M and Schweitzer J: “Interpretingan RFT*-Measured Pulse Test with a Three-Dimen-sional Simulator,” SPE Formation Evaluation 3(March 1988): 139-146.

11. Slentz LW: “Geochemistry of Reservoir Fluids as aUnique Approach to Optimum Reservoir Manage-ment,” paper SPE 9582, presented at the SPE MiddleEast Oil Technical Conference, Manama, Bahrain,March 9-12, 1981.Gibbons K: “Use of Variations in Strontium IsotopeRatios for Mapping Barriers: an Example from theTroll Field, Norwegian Continental Shelf,” presentedat the 6th European Symposium on Improved OilRecovery, Stavanger, Norway, May 21-23, 1991.

12. Lachance DP and Rezk AS: “Resolution of FaultBlock Communication Leading to an Optimal Planof Depletion, Abu Gharadig Gas Field, Egypt,” paperSPE 17993, presented at the SPE Middle East OilTechnical Conference and Exhibition, Manama,Bahrain, March 11-14, 1989.

13. Weber KJ, Mandl G, Pilaar WF, Lehner F and Pre-cious RG: “The Role of Faults in HydrocarbonMigration and Trapping in Nigerian Growth FaultStructures,” paper OTC 3356, presented at the 10thAnnual Offshore Technology Conference, Houston,Texas, USA, May 8-11, 1978.

illion

75 77 79 81 83 8785

nAn increasinglycomplex view ofthe fault system inBlock IV of ShellExpro’s North SeaCormorant field.Two 3D seismicsurveys, in 1981and 1984 respec-tively, progres-sively clarified thepicture. By 1989,data from newlydrilled wells addedmore detail. Themost recent simu-lation (far right)used a curvilineargrid to follow thefaulting. (FromRuijtenberg et al, ref-erence 7.)

12 Oilfield Review

tuning the locations of wells to be drilled.Shell Expro’s estimates of the Cormorantfield recoverables have rebounded and nowremain relatively constant (below).

The newcomer in detecting large-scalestructure is well-to-well tomography, a tech-nique that measures the acoustic signaltransmitted from a source located in onewell to a receiver located in a neighboringwell.8 Measurements are made for multiplecombinations of receiver and source depths,creating a large data set from which com-puter processing recreates an acousticvelocity map of the interwell terrain. The

1974-19752D Seismic

19813D Seismic

1983-19843D Seismic

Platform

OilWaterVoid blockFault

0 2 km

North Sea

Orkney Isles

East Shetland Basin

Shetland Isles

Norway

Aberdeen

Cormorant Field

0 100 miles

N.Cormorantplatform

CormorantAlpha platform

0 2 km

Block IV

nEstimates of recoverable reserves in theCormorant field. Initially, only the south-ern part of the field was developed. Itscomplex structure caused estimates ofreserves to drop. Cormorant Block IV wasdeveloped three years later and benefitedfrom 3D seismic surveys mapping its com-plex structure. Reserves increased afterthe addition of the new field andremained steady with time because theoperator better understood its structure.

technique was conceived in the 1960s, butimplementation is still hampered by techni-cal difficulties, notably the engineering of asufficiently powerful downhole source. Incurrent experiments, acoustic frequency liesin the hundreds of hertz (Hz), between thelow frequencies of surface and boreholeseismics (10 to 100 Hz) and the high fre-quencies of acoustic logging (20,000 Hz).This is designed to provide both formationpenetration and spatial resolution. Mostexperiments so far have been in shallow for-mations. Texaco Inc. and Chevron Oil FieldResearch recently performed a tomographicsurvey to clarify reservoir structure in theshallow McKittrick oil field in California,USA (right ).9 The image created by twoabutting tomograms maintains a resolutionof 40 ft [12 m], reveals details of overthrustfaulting and provides a substantiallyimproved picture of the field’s heterogene-ity. However, much work remains to ensurethe reliability of tomographic processing.

Locating faults is just half the story,though. Also crucial is determining whetherthere is fluid communication across a faultwhen sand abuts sand. Several methodshelp clarify the sealing question. In interwelltesting, a flow disturbance is created in awell on one side of the fault and monitoredusing pressure gauges in a well on the otherside, either at surface or downhole. Lack ofreaction to the disturbance may indicatesealing.10 In tracer tests, radioactive orchemical tracers injected in one well aremonitored in neighboring producers. Notracer appearing in the producer may indi-cate sealing. Chemical analyses of forma-tion water and hydrocarbons on both sidesof a fault may also give insight into connec-tivity across it, the analyses matching if thefault is nonsealing.11 Material balance cal-culations that indicate the volume of theconnected reservoir offer another diagnos-tic—the reservoir will appear larger if a faultis nonsealing.12 In a reservoir that has pro-duced for some time, a common method isto make pressure measurements using anRFT (Repeat Formation Tester) tool in wellseither side of the fault. Differing pressuredeclines across the fault indicate sealing.

A nondirect method is based on thehypothesis that faults seal because clay bedscut by fault displacement smear plasticallyinto the fault, filling it and preventing com-munication (right). Clay smearing has beenreproduced in laboratory experiments andalso observed in situ down mines.13 Claysmearing is more likely to seal a fault ifthere is plenty of clay available—this can bedetermined from logs. But it is less likely themore the fault has been displaced—dis-

nFault sealingthrough claysmearing, a phe-nomenon in whichclay smears plasti-cally in a growingfault creating abarrier to fluidflow. The likeli-hood of a sealingfault due to claysmearing can beestimated from thethickness ofnearby clay zonesand the throw ofthe fault. (FromWeber et al, refer-ence 13.)

13January 1992

Well 1 Well 2

nTwo abuttingtomogramsrevealing possi-ble fault structurebetween wells inthe shallowMcKittrick oilfield in California,USA. Tomogramsare obtained bytransmittingacoustic signalsbetween the wells(see inset below)—the technique isexperimental.The data wereobtained jointlyby Texaco andChevron; thetomogram wasprocessed andinterpreted byTexaco Inc. (From Lo et al, refer-ence 9, courtesy ofTexaco Inc. andChevron Oil FieldResearch.)

placement can be estimated from seismicdata and in some cases from logs in neigh-boring wells. Both factors can be workedinto a quantitative prediction of fault com-munication and integrated into reservoirsimulation, a feat recently performed for theCormorant Block IV field.14

A yet more difficult task awaits the opera-tor when evaluating a reservoir’s naturalfracture system. That fractures influencegross field behavior is demonstrated in arecent report surveying 80 fields from pro-ducing areas worldwide and covering everyproduction method from waterdrive to gas-drive to surfactant flooding.15 The surveyshows that preferential flooding directionclosely parallels the direction of maximumhorizontal stress, the same direction a natu-ral fracture system takes (right). The surveyrules out the possibility that induced frac-tures may be causing flooding directional-ity—the correlation improves with greaterspacing between wells, unlikely unless thefractures are natural.

nCorrelation between preferential flood-ing orientation and direction of maximumhorizontal stress determined from well-bore breakouts, for 80 fields worldwidewith a variety of flooding mechanisms.This result reinforces the importance ofunderstanding a reservoir’s natural frac-ture system and its role in determiningwaterflood efficiency. (From Heffer and Lean,reference 15.)

Detecting a natural fracture system andestimating its directionality is thereforemandatory, and needed as early as possiblein the development of a field. The questionis how? Apart from regional stress studies,little can be done before wells are drilledand logs and cores become available. Con-ventional 3D seismics fails to see naturalfractures. There is hope, however, that shearseismic surveys, both from the surface andthe borehole, may help. Shear waves vibratetransversely to the wave direction and canbe split into two parts by fractures. Shearsurface seismic experiments made byAmoco Production Co. have demonstratedthis splitting as have shear borehole seismicsurveys in the Paris basin, France and Silofield, Wyoming, USA.16 Shear seismics is inits infancy, though, and one stumbling blockmay prevent the technique ever maturing: itis practically impossible to generate shearwave energy in marine sediments becausethe ocean separating source from formationdoes not support shear propagation. Allexperiments so far have been on land.

14 Oilfield Review

nConfirmation of natural fractures from cores and logs, in a Texas carbonate. Fractures are visible on the borehole televiewer andFormation MicroScanner logs (black streaks) at 2234 and 2238 ft. They also appear as two peaks on the Stoneley fracture width logwhich is derived from the Array-Sonic log (far right). (From Adams et al, reference 18.)

Generalchannelstrends

Range of majorhorizontal stress

Preferentialflooding direction

Concrete proof of natural fractures finallyemerges when wells are drilled and frac-tures are recognized in cores and on logs(previous page, bottom). Cores and logs alsoherald the beginning of serious depositionalstudy. With the help of a standard petro-physical interpretation of conventional logs,use of dipmeter logs17 and more recentlyFormation MicroScanner logs18 can revealimportant clues about the depositional pro-cess (right). Skillfully interpreted, all theselogs together with core data allow a pictureof the reservoir’s internal structure to gradu-ally emerge. Particularly crucial are perme-ability barriers between units and high-per-meability streaks that allow production tobypass large regions of the reservoir. Barriersmay be suggested by depositional analysis,but must be corroborated with pressuremeasurements and well testing.

Of increasing use in clarifying deposi-tional environment is, once again, the 3Dseismic survey. Sophisticated processing onthe amplitude data that reveals dip andazimuth, shaliness, and even net pay is

14. Bentley MR and Barry JJ: “Representation of FaultSealing in a Reservoir Simulation: Cormorant BlockIV, UK North Sea,” paper SPE 22667, presented atthe 66th SPE Annual Technical Conference andExhibition, Dallas, Texas, USA, October 6-9, 1991.

15. Heffer KJ and Lean JC: “Earth Stress Orientation—aControl on, and Guide to, Flooding Directionality ina Majority of Reservoirs,” presented at the 3rd Inter-national Reservoir Characterization Technical Con-ference, Tulsa, Oklahoma, USA, November 3-5,1991.

16. For a review of shear seismics and its application toidentifying fractures:“Formation Anisotropy: Reckoning with its Effects,”Oilfield Review 2, no. 1 (January 1990): 16-23.For surface shear seismics:Lynn HB and Thomsen LA: “Reflection Shear-WaveData Along the Principal Axes of AzimuthalAnisotropy,” Expanded Abstracts, 56th Annual Inter-national Meeting and Exhibition, Society of Explo-ration Geophysicists, Houston, Texas, USA (1986):473-476.For borehole shear seismics:Crampin S, Lynn HB and Booth DC: “Shear-WaveVSP’s: A Powerful New Tool for Fracture and Reser-voir Description,” Journal of Petroleum Technology41 (March 1989): 282-288.

17. Gilreath JA: “Strategies for Dipmeter Interpretation(Part 1),” The Technical Review 35, no. 3 (July1987): 28-41.Adams J, Bourke L and Frisinger R: “Strategies forDipmeter Interpretation (Part 2),” The TechnicalReview 35, no. 4 (October 1987): 20-31.

18. Adams J, Bourke L and Buck S: “Integrating Forma-tion MicroScanner Images and Cores,” OilfieldReview 2, no. 1 (January 1990): 52-65.Darling H, Patten D, Young RA and Schwarze L:“Single-Well Data Integration,” Oilfield Review 3,no. 3 (July 1991): 29-35.

nDepositional interpretation from well data facilitated by the integration of petrophysi-cal logs, Formation MicroScanner logs and computer-aided interpretations. In con-structing this composite display, a geologist has reviewed the Formation MicroScannerlog—left track in “Sedimentology/Structure”—on an interactive workstation and sym-bolically coded an interpretation that appears to the right. The “Petrophysics” and“Rock Classification” tracks are computer-interpreted from conventional logs. (From Dar-ling et al, reference 18.)

15January 1992

proving that minute changes in the seismicsignal may reflect real geologic events andhave an important story to tell.19 A timeslice from a survey in the Matagorda area ofthe Gulf of Mexico reveals a meanderingstream channel (next page).20 Amplitudemaps from the top and base of anotherchannel sand from one of Shell’s offshorefields in Sarawak, Malaysia, obtained byautomatic tracking on the 3D seismic ampli-tude data of the relevant horizons, display adistributary channel and crevasse splay.21

Both examples are from less than 1000 m[3200 ft], shallow enough to preserve thehigh seismic frequencies required to see thiskind of detail. Obtaining the same resolu-tion at greater depths that currently attenu-ate high frequencies will depend on techni-cal improvements to the acquisitionprocess.

The general problem facing the entirereservoir management team, as eyes focuson smaller-scale heterogeneity, is the blankarea between wells. 3D seismic data mayreliably outline the overall reservoir archi-tecture and the fault system with an occa-sional clue to deposition, and well data mayreveal the detailed depositional environ-ment close to wells, but the huge spacebetween wells is mostly unknown. True, indepositionally simple areas, features on logs

may correlate from one well to the next, andthe reservoir structure emerges quite readily.But in complex areas, correlation may besparse or nonexistent. The only recourse isfor the geologist to dig into a repertoire oftypical sizes, shapes and juxtapositions fordepositional units and fill in the blank spacewith as plausible a picture as possible.

For clastic reservoirs, this art has been for-malized by Weber and van Geuns of Shell(below).22 Reservoir architecture is dividedinto three types—layer cakes, jigsaw puzzlesand labyrinths. Layer cakes describe reser-voirs deposited by a single depositionalmechanism that show excellent correlationbetween wells. In jigsaw puzzle reservoirs,different sand bodies fit together withoutmajor gaps but with occasional interveninglow-permeability zones. Labyrinths representmore or less random arrangements of sands,usually discontinuous.

The first step is to recognize which type ofarchitecture is present. The next step—which becomes harder with more complexarchitecture—is to draw on knowledge ofhow particular sand bodies are shaped anddistributed and then create plausible scenar-ios for the reservoir geometry. This hasspawned two disciplines. One involvespatient hours in the field studying outcropsand compiling statistics on the geometry

and occurrence of depositional units andtheir heterogeneity, a labor often subcon-tracted by operators to university depart-ments. The second takes place in front of aterminal connected to a powerful computer.Here, a geostatistician uses the outcropstatistics to help create probabilistic modelsof the reservoir (for detail on outcrop studiesand reservoir model building, see “ReservoirCharacterization Using Expert Knowledge,Data and Statistics,” page 25).23

A probabilistic reservoir model first hon-ors known, or deterministic, data from wellsand then fills the empty space with sandbodies both shaped and placed in spacerandomly. The result is called a realization,a term coined by statisticians to describeone outcome of a random process. Manyrealizations are required to judge variationsin architecture caused by the random ele-ment of the model building. In simple layercake architectures, most of the model maybe deterministic with little or no probabilis-tic content. Labyrinth architectures, on theother hand, have little deterministic contentand are mostly probabilistic.

Probabilistic model building comes in avariety of guises, and models can be con-structed at all scales. Some of the finest scaleclastic models are being built by Shell usingtheir proprietary software package,

16 Oilfield Review

Layer cake

Jigsaw puzzle

Labyrinth

listic

nClassification of large-scale sand geometries into layer cakes, jigsaw puzzles and labyrinths. Layercakes are deposited in one environment, have excellent well-to-well correlations and can be modeleddeterministically. Jigsaw puzzles represent sand bodies that fit together without major gaps, but withoccasional low permeability barriers. Correlation may be difficult and modeling must have a probabilis-tic content. Labyrinths represent discontinuous sands with poor well-to-well correlation. Modelingrequires a strong probabilistic content. (From Weber and van Geuns, reference 22.)

19. Sonnelund L, Barkved O and Hagenes O: “ReservoirCharacterization by Seismic Classification Maps,”paper SPE 20544, presented at the 65th SPE AnnualTechnical Conference and Exhibition, New Orleans,Louisiana, USA, September 23-26, 1990.

20. Riese WC and Winkleman BE: “Shallow OverlookedChannels, Offshore Gulf of Mexico: Application of3D Seismic Analysis to Stratigraphic Interpretation,”in Bally AW (ed): Atlas of Seismic Stratigraphy, vol.3. Tulsa, Oklahoma, USA: American Association ofPetroleum Geologists (1989): 59-65.

21. Rijks EJH and Jauffred JCEM: “Attribute Extraction:an Important Application in any Detailed 3D Inter-pretation Study,” Geophysics: The Leading Edge ofExploration (September 1991): 11-19.

nTwo examples ofchannel sandsidentified with 3Dseismic data:Left: amplitudemaps of two hori-zons picked from a3D seismic data setobtained in one ofShell’s offshorefields in Sarawak,Malaysia. The hori-zons show the topand bottom of adistributary chan-nel sand. The tophorizon clearlyshows a crevassesplay, later con-firmed by logs.(From Rijks and Jauf-fred, reference 21,courtesy of Shell Inter-nationale PetroleumMaatschappij B.V.and Geophysics: TheLeading Edge ofExploration.)Right: a time slicefrom a survey con-ducted by ARCO inthe Matagordaarea of the US GulfCoast reveals ameanderingstream channel,probably gas filled.The meander of thestream suggests achannel width of15 ft [4.5 m], whileseismic resolutionwas estimated atonly 40 ft [12 m].The better-than-expected accuracymay be caused byinterference or bythe presence ofgas. (From Riese andWinkleman, reference20, courtesy of ARCOOil and Gas Companyand the AmericanAssociation ofPetroleum Geologists.)

22. Weber KJ: “How Heterogeneity Affects Oil Recov-ery,” in Lake LW and Carroll HB Jr. (eds): ReservoirCharacterization. Orlando, Florida, USA: AcademicPress Inc. (1986): 487-544..Weber KJ and van Geuns LC: “Framework for Con-structing Clastic Reservoir Simulation Models,” Jour-nal of Petroleum Technology 42 (October 1990):1248-1253, 1296-1297.

23. Haldorsen HH and Damsleth E: “Stochastic Model-ing,” Journal of Petroleum Technology 42 (April1990): 404-412.

17January 1992

Distributary Channel

CrevasseSplay

Base sand

Top sand

0 1 2km

Channel

nTracking fluid fronts using MONARCH,Shell’s probabilistic reservoir modelingpackage. MONARCH divides space intomillions of voxels, small volume elementsmeasuring typically 50 m x 50 m x 0.6 mthick. The models honor data measuredat wells (grey vertical columns), but fillthe rest of space probabilistically.MONARCH models permit analysis of for-mation connectivity and also of fluid dis-tributions throughout the reservoir.

This example shows part of a North Seareservoir early in the reservoir’s life andafter ten years of production. The modelsare viewed from the south and do not showan overall 8° westerly dip. Given the dif-fering vertical and horizontal scales, a truevisualization is obtained by tilting up theright-hand edge of the figure by about 25°.

There are three types of sand, identifi-able by color if oil saturated. All threetypes are uniformly colored blue if watersaturated and green if gas saturated.Shales are transparent. The rightwardprogress of the waterfront is clearly evi-dent. Ten years on, several pockets of oil-saturated sand remain unswept. (FromBudding et al, reference 24, courtesy of Koninkli-jke/Shell en Produktie Laboratorium.)

Channel-fill sand

Sheet sand

Coarsening-upward sand

Early in life of reservoir Ten years later

Sand, all types

Foreground scale

MONARCH, which divides space into vox-els, the three-dimensional version of a pixel,each measuring about 50 m × 50 m × 0.6 mthick [164 ft × 164 ft × 2 ft]—the exactdimensions can vary.24 The model honorswell data from logs, down to the 0.6-m verti-cal resolution, uses structural informationprovided by seismic and dipmeter data. Itensures a given sand-shale ratio and distin-guishes between at least three different sandtypes—for example, in a fluvial environmentbetween channels, mouth bars, and crevassesplays. Finally, it obeys the statistics ondepositional unit width, thickness and lengthas derived from outcrop or other studies.

The result is a three-dimensional matrix ofmillions of voxels. Although this must bereduced in size—scaled up, in simulationparlance—by almost two orders of magni-tude for simulating fluid flow, the detailedmodel provides insight into gross reservoirconnectivity by tracking flow paths throughthe voxels. Applied to two reservoir units inthe Cano Limon field in Colombia, one unitproducing and the other overlying unit notyet completed, a MONARCH model showedthat 24 existing wells tapping the producingunit would also tap 60% of the overlyingunit if it was completed. This is invaluableinformation for reservoir managers needingto decide if extra wells are needed to tap theoverlying unit.

Programmed to track different fluids in thesand bodies, MONARCH-type models canalso integrate production logs and pulsedneutron logs that measure saturation behindcasing. This is a major advance. Currently,the commonest data used to monitor reser-voir performance are well pressures andproduction, usually from individual wellsbut sometimes from groups of wells. Thesedata track gross well performance at best,masking the relative contributions of differentproducing layers. MONARCH models cantrack flood advances in detail and identifyunswept parts of the reservoir (above).

Tracking fluids through voxels at one par-ticular moment in time, though, is a far cryfrom reservoir simulation which builds aflow model of the reservoir from past pro-duction data—the history matchingphase—and then predicts futureproduction.25 In flow simulation, the reser-voir is divided into a large number of inter-connecting homogeneous tanks called gridblocks, and then multiphase fluid flowthrough them is solved as a function of time.The computation requires the largest com-puters, and maximum model size is cur-rently about 50,000 grid blocks, each blockbeing more than 200 times the volume of avoxel. Most simulations use fewer and evenlarger blocks, particularly during theappraisal phase when data are scarce.

Oilfield Review

Full FieldSectional

ProducerInjector

Single Well

nVarieties of reservoir simulations. Reservoir management may begin with a simplesimulation model and then evolve to more complex representations as more data

Opinions on the value of simulationvary—from being an unproductive chore,required for unitization or by governmentregulation, to being the key tool in reservoirmanagement. Nevertheless, most fieldsundergo some form of simulation as soon asthe discovery well hits pay. The pessimist’sview stems in part from unreasonableexpectations about what simulation canbring, which in turn depends on when sim-ulation is used in the life of the reservoir.26

During discovery and appraisal phases,simple simulations with few grid blocks rep-resenting little more than an extension ofclassical reservoir engineering techniquescan assist major decisions on productionfacilities and how the reservoir should beproduced. With little data to go on, such asimulation cannot be expected to accuratelypredict production. Rather, its use is to testproduction sensitivity to different drivemechanisms and to variations in large-scalestructure, such as external boundaries, strati-fication and whether faults are sealing, par-tially sealing or open.

As the field matures and more databecome available, the simulation growsmore complex with an increasing numberof grid blocks. Prediction becomes morereliable and helps guide all manner of reser-voir management decisions—about infilldrilling, perhaps the drilling of horizontalwells, evolving surface facilities to copewith changing production, modifying thedriving mechanism, or justifying workover(see “Drilling for Maximum Recovery,” page21). Yet, simulation remains essentially aqualitative tool. Like weather forecasting, itstrives to predict a potentially chaotic situa-tion from a huge number of initial condi-tions—pressure everywhere in space forweather forecasting and pressure and satu-ration in every grid block for simulation.27

Both systems are what mathematicianscall overdetermined. In simulation, the

January 1992

24. Budding MC, Flint SS, Paardekam AHM andDubrule ORF: “Three-Dimensional Reservoir Geo-logical Modeling of the Cano Limon Field, Colom-bia,” AAPG Bulletin 74, no. 5 (May 1990): 621.Abstract only. Full text to appear in the AAPG Bulletin.Budding MC, Paardekam AHM and van Rossem SJ:“3-D Connectivity and Architecture in SandstoneReservoirs,” paper SPE 22342, to be presented at theSPE International Meeting on Petroleum Engineer-ing, Beijing, China, March 23-28, 1992.

25. For brief reviews of reservoir simulation:Mattax CC and Dalton RL: “Reservoir Simulation,“Journal of Petroleum Technology 42 (June 1990):692-695.Breitenbach EA: “Reservoir Simulation: State of theArt,” Journal of Petroleum Technology 43 (Septem-ber 1991): 1033-1036.

number of model parameters that can beadjusted to history match past productiondata greatly exceeds the quantity of produc-tion data being matched. This permits manypossible matches for the same data. Tomake the history match, reservoir engineerstherefore adjust certain parameters andignore the rest. Traditional favorites foradjustment are grid-block properties such aspermeability and relative permeability.Much less popular, because they are farmore trouble to adjust but maybe just as sig-nificant, are geologically dependent param-eters such as the size and placement of thegrid blocks themselves.

Simulations do not necessarily have toreproduce a reservoir in its full three-dimen-sionality. Early in the life of a field, in partic-

become available.

26. Thomas GW, “The Role of Reservoir Simulation inOptimal Reservoir Management,” paper SPE 14129,presented at the 1986 SPE International Meeting onPetroleum Engineering, Beijing, China, March 17-20, 1986.Wood ARO and Young MS: “The Role of ReservoirSimulation in the Development of Some MajorNorth Sea Fields,“ paper SPE 17613, presented atthe 1988 SPE International Meeting on PetroleumEngineering held in Tianjin, China, November 1-4,1988.Wittmann M, Al-Rabah AK, Bansal PP, BreitenbachEA, Hallenbeck LD, Meehan DN and Saleri NG:“Exploring the Role of Reservoir Simulation,“ Oil-field Review 2, no. 2 (April 1990): 18-30.

ular, much simpler simulations can yieldvaluable insight into production (below).Single-well simulators, using a radial gridsystem centered on the well, are invaluablefor studying coning, the economics of a par-tial completion, or for interpreting a welltest. Sectional simulators that model flow ina vertical plane are often used to study dis-placement behavior between an injectorand a producer. Areal simulators that modelflow in a horizontal plane may be an opera-tor’s first choice for analyzing production ina single-layered homogeneous reservoir.The results and analyses of any of these sim-ulations can always serve as input to a moresophisticated simulation.

Areal simulators were the first choice forSaudi Aramco when planning water injec-

27. Saleri NG and Toronyi RM: “Engineering Control inReservoir Simulation: Part I,” paper SPE 18305, pre-sented at the 63rd SPE Annual Technical Conferenceand Exhibition, Houston, Texas, USA, October 2-5,1988.Saleri NG, Toronyi RM and Snyder DE: “Data andData Hierarchy,” paper SPE 21369, presented at theSPE Middle East Oil Show, Manama, Bahrain,November 16-19, 1991.

nEvolving simulation complexity for one of Saudi Aramco’s largest carbonate reservoirs. The development began withareal simulations of Reservoir I, then a full-field simulation, next an investigation of the underlying Reservoir II, and finallyof the surrounding aquifer. The number of grid blocks starts at 1824 and finishes at 42,000.

20 Oilfield Review

Reservoirs I and II

2520 grid blocks

1824 grid blocks

Reservoir I

Dense limestone

Aquifer and Reservoir I

42,000 grid blocks

32,760 grid blocks

Dense limestone

1. Abriel WL, Neale PS, Tissue JS and Wright RM: “ModernTechnology in an Old Area: Bay Marchand Revisited,”Geophysics: The Leading Edge of Exploration (June1991): 21-35.

tion in their largest, carbonate field (previ-ous page).28 This first simulation wasdesigned in 1970, 20 years after parts of thefield started producing and used a 57 × 32grid, giving 1824 grid blocks. It wasenlarged in 1978 to 60 × 42, giving 2520grid blocks. These simulations were used toplan individual well productions to sustainan overall production rate, to forecast thelength of the production plateau and to esti-mate final recovery.

By 1980, water encroachment hadbecome serious enough to consider givingthe areal simulation a third, vertical dimen-sion—two horizontal dimensions rule outthe modeling of coning. Geologists identi-fied 13 layers within three major producingzones and superimposed them on the previ-ous areal grid, giving a simulation compris-ing 60 × 42 × 13 = 32,760 grid blocks. Con-currently, reservoir engineers embarked ona major program of reservoir-monitor log-ging—flowmeters and pulsed neutron mea-surements mainly—to provide sufficientinformation to history match the field’s pro-duction. By 1985, the simulator was historymatched and available for prediction stud-ies. These have included determination ofthe original oil/water contact, the problemof varying depletion from different zones,the possibility of also producing the reser-voir’s gas cap and evaluation of gas lift. Inshort, the 3D simulator has proved a keytool for most reservoir management deci-sions in the field.

About 500 ft [150 m] below this hugereservoir lies a smaller reservoir of inferiorquality with about one-tenth the individualwell productivity. By the time the first wellin the smaller reservoir (Reservoir II) wasput on production in 1954—eight yearsafter the huge reservoir (Reservoir I) hadstarted producing—Reservoir II’s pressurehad dropped by about 900 psi. This indi-cated communication between the tworeservoirs, which geologists attributed to afracture system permeating the intervening500 feet of dense limestone. The urgentquestion was how to contain the communi-cation, since it could cause both oil andwater to migrate downward from ReservoirI to Reservoir II as Reservoir II’s pressuredeclined. Juggling the options required sim-ulating both reservoirs simultaneously. Thefirst attempt divided Reservoir II into four

January 1992

28. Al-Dawas SM and Krishnamoorthy AM: “Evolutionof Reservoir Simulation for a Large Carbonate Reser-voir,” paper SPE 17938, presented at the SPE MiddleEast Technical Conference and Exhibition, Manama,Bahrain, March 11-14, 1989.

layers, which were placed below a singleareal grid simulating Reservoir I. Later, thefour layers were combined with the full 13-layer model previously established forReservoir I, giving a total of 37,800 gridblocks. This is currently being used toassess how to produce Reservoir II.

Yet more simulation has been required tostudy the extensive aquifer that drives Reser-voir I’s production and also that of othernearby fields. The aquifer was modeled withan areal grid in the middle of which Reser-voir I occupies 19 × 8 grid blocks, muchcoarser than the reservoir’s original 60 × 42areal simulation. During history matching,the aquifer and Reservoir I simulators wererun iteratively, with results from the finergridded reservoir simulation being scaled upto the coarser grid blocks of the aquifer sim-ulation. A final step in simulating this fieldhas been the use of locally refined griddingthat allows the integration of the fine 3Dreservoir model directly into the coarse,areal aquifer model, obviating the iterativeprocess. This raises the number of gridblocks to 42,000.

Saudi Aramco’s field was developed longbefore the age of computers, so simulationcould be applied only years after productioncommenced. In more recent fields, particu-larly those in geologically complex and eco-nomically harsh areas, simulation is oftenused from the moment of discovery. TheBrent field in the North Sea, jointly ownedby Shell and Esso, provides an example.

The first simulation took place during theappraisal phase using just 800 grid blocks.29

It successfully guided basic decisions onfield development and facilities planning.The next simulation built during the devel-opment phase used 11 layers and an arealgrid of 19 × 37, giving a total of 7733 gridblocks.30 This proved adequate to confirmthe water injection program, investigate fur-ther facilities requirements and estimate thelength of the plateau. As the field entereddecline phase, a third simulation was con-ducted with an even finer grid to takeadvantage of the abundant acquired dataand better track the water front. This time,21 layers and an areal grid 30 × 54 pro-duced 34,020 grid blocks. Reservoir engi-neers used the simulation to pick new welllocations and optimize a gas injection pro-gram.31 A comparison of production predic-

29. Johnson HA: “North Sea Reservoir Simulation: Prac-tical Considerations,” paper SPE 19039, presented atthe SPE Middle East Technical Conference and Exhi-bition, Manama, Bahrain, March 11-14, 1989.

30. Tollas JM and Sayers JR: “Brent Field 3-D ReservoirSimulation,“ paper SPE 12160, presented at the 58thSPE Annual Technical Conference and Exhibition,San Francisco, California, USA, October 5-8, 1983.

Drilling for Maximum Recov-ery

Whatever drive mechanism is chosen, ultimate

recovery depends on ensuring maximum connec-

tivity between wells and the producing formation.

This requires understanding the nature of the for-

mation heterogeneity and then guiding the drill

bit to reach as much connected oil as possible.

In reservoirs where faults subdivide the reser-

voir into isolated pockets, 3D seismics with its

ability to map large-scale structure offers the

best chance to ensure that each pocket gets

tapped by a well. An example is Chevron’s giant

Bay Marchand field, offshore Gulf of Mexico.1

This field, discovered in 1949, is located around

a huge salt dome and produces from highly

faulted sands. Oil production peaked at 75,000

barrels of oil per day (BOPD) in the late 1960s

and declined to just 18,000 BOPD by the mid

1980s. It looked like the end, until Chevron com-

missioned a 3D seismic survey of the entire field.

With over 60 platforms and 50 multiwell sur-

face structures scattered over the offshore site,

the logistics were daunting. Once completed,

however, the survey clarified the salt-sediment

interface, gave improved definition to the faulting

and provided a better understanding of the depo-

sitional environment. The result has been several

new producers in both mature and undeveloped

parts of the field, a realization that certain wells

were not worth maintaining, and improved water-

flood schemes. Field production now stands at

32,500 BOPD.

A different strategy is required in highly strati-

fied reservoirs where poor connectivity is caused

by discontinuous stringers, such as in Exxon’s

Fullerton field in Andrews County, Texas, USA.

Discovered in 1942, this field was rapidly

exploited with over 550 wells. By the 1960s, the

field was in decline and substantial water injec-

tion was required to maintain oil production at

around 10,000 BOPD. Although the producing

zone is several hundred feet thick, the pay is in

carbonate stringers that correlate very poorly

between wells.2 Exxon found during infill drilling

that the correlation seemed to get worse the

closer you looked. A continuity measure was

defined as the percentage of producing carbonate

that hydraulically connects between two given

wells—that is, the percentage that would theoret-

ically get produced if one well was an injector

and the other a producer. Exxon then investigated

how this continuity depended on well spacing

(above, far left). Initially, the information came

from the original wells, which were on a 40-acre

spacing.

It came as no surprise that continuity worsened

as well spacing increased. But as the field was

2. Stiles LH: “Optimizing Waterflood Recovery in a MatureWaterflood, the Fullerton Clearfork Unit,” paper SPE6198, presented at the 51st SPE Annual Technical Confer-ence and Exhibition, New Orleans, Louisiana, USA, Octo-ber 3-6, 1976.

3. Barber AH Jr, George CJ, Stiles LH and Thompson BB:“Infill Drilling to Increase Reserves—Actual Experience inNine Fields in Texas, Oklahoma, and Illinois,” Journal ofPetroleum Technology 35 (August 1983): 1530-1538.

4. McCoy TF, Fetkovich MJ, Needham RB and Reese DE:“Analysis of Kansas Hugoton Infill Drilling: Part I—TotalField Results,” paper SPE 20756, presented at the 65thSPE Annual Technical Conference and Exhibition, NewOrleans, Louisiana, USA, September 23-26, 1990.

Fetkovich MJ, Needham RB and McCoy TF, : “Analysis ofKansas Hugoton Infill Drilling: Part II—12-Year Perfor-mance History of Five Replacement Wells,” paper SPE20779, presented at the 65th SPE Annual Technical Con-ference and Exhibition, New Orleans, Louisiana, USA,September 23-26, 1990.

Fetkovich MJ, Ebbs DJ Jr and Voelker JJ: “Developmentof a Multiwell, Multilayer Model to Evaluate Infill DrillingPotential in the Oklahoma Hugoton Field,” paper SPE20778, presented at the 65th SPE Annual Technical Con-ference and Exhibition, New Orleans, Louisiana, USA,September 23-26, 1990.

5. Freyss HP and Burgess K: “Overcoming Lateral ReservoirHeterogeneities Via Horizontal Wells, ” presented at the6th European Improved Oil Recovery Symposium, Sta-vanger, Norway, May 21-23, 1991.

22 Oilfield Review

Distance between wells, ft

From 10-acre spacing

0 1000 2000 3000

nPercentage of reservoir formationhydraulically connecting two wells versusdistance between them, for Exxon’s Fuller-ton, Texas field. The data were obtainedfrom wells drilled with 40-, 20-, and 10-acre spacing. As distance between wellsincreases, continuity worsens. And asmore data become available, previousestimates on continuity appear overlyoptimistic. (From Barber et al, reference 3.)

40-acre spacing

Phase 2

- Producer - Injector

Phase 1

nTwo-phase sequence of infill drilling in Exxon’s Fullerton, Texas reservoir. In phase 1,new producers were drilled in the center line of the previous three-line drive, and otherproducers were converted to injection. In phase 2, another producer was drilled in each80-acre rectangle. The infill program tapped reserves unconnected to previous wellsand prolonged the field’s life by at least ten years. (From Barber et al, reference 3.)

1965 1975

40-acre wellsInterference

Phase 1

Other Infills

1985 1995

Phase 2

nIncrease in pro-duction from infilldrilling in Exxon’sFullerton, Texasreservoir. The inter-ference productionis that lost from theoriginal wells tothe new wells.(From Barber et al, ref-erence 3.)

drilled with denser spacings, data showed that

earlier estimates of continuity were grossly opti-

mistic.3 The only means of increasing recovery

was to drill progressively denser well spacings

(previous page, top). This was carried out in two

phases. The first took well spacing to 20 acres,

the second to 10. When the second phase was

completed, the new wells accounted for 71% of

the field’s production, and each well added an

estimated 97,000 barrels to recoverable reserves

(previous page, middle).

However tempting it may look, though, infill

drilling is not a panacea. This is the view of

Fetkovich and colleagues at Phillips Petroleum

Co. with respect to the Hugoton gas field, the

largest in the lower 48 US states, spanning parts

of Kansas, Oklahoma and Texas. The Hugoton

comprises interspersed carbonate and layered

shaly units—continuity is excellent, the log sig-

nature being consistent from one well to the next.

When the state authorities authorized infill

drilling in the late 1980s, the Phillips team

proved through studying production histories and

conducting simulations that the reservoir was

essentially layered with no vertical crossflow.

They concluded that while infill drilling might

increase productivity, the new wells would add

nothing to the field’s reserves.4 Thanks to the for-

mation continuity, all the gas was already con-

nected to the existing wells.

Production from natural fractures, such as in

the Austin chalk formations in south Texas, poses

yet another type of heterogeneity that until

recently sorely tested operators’ attempts to

secure economic recovery. The Pearsall field

exploited by Oryx is typical. The oil is contained

in successive clusters of roughly parallel subver-

tical fractures. Each cluster acts as a separate oil

accumulation and lacks communication with its

neighbors. Produced through vertical wells, these

formations provide unsubstantial economic

return. But connect several together with a hori-

zontal well, and the economics improve immedi-

ately.5 Overcoming reservoir heterogeneity was a

key impetus behind the horizontal well revolution.

tions from the second and third simulationsshows how the finer simulation provides amore optimistic, and presumed truer, sce-nario for the field’s decline phase (above).

What is the trend in simulation? Advancesin computer power will undoubtedly spursimulations with more grid blocks, repre-senting finer reservoir detail. It is conceiv-able, for example, that simulating gridblocks the size of the MONARCH system’svoxels may eventually be possible. If thishappens, reservoir management willbecome reliant on probabilistic modeling,since no field technique, even the mostexperimental, appears capable of measuringto that degree of detail between wells—allthe simulations described in this article andalmost all described in the literature aredeterministic. The future may lie in con-structing a geologically probabilistic modelfrom the beginning and then firming it updeterministically as data become available.The latest simulation work in the Brent fieldrepresents one of the first applications ofprobabilistic modeling.32

The Brent field actually comprises twomajor reservoirs, the middle Jurassic Brentreservoir and the lower Jurassic Statfjordreservoir, that are separated by 250 m [820ft] of shale. Some of the most complexreservoir sediments and therefore mosttroublesome during history matching arechannel sands in the middle part of theStatfjord unit. It was therefore decided toconstruct a detailed probabilistic model of

these sands for a 3- by 2.5-kilometer [1.9-by 1.6-mile] sector in the southern part ofthe reservoir (next page, top). The sectorwas chosen because it had abundant welldata—six oil producers, three water injec-tors and one gas injector. The probabilisticmodel was then sandwiched betweendeterministic models of the upper andlower parts of the Statfjord reservoir, andfinally the whole thing was run through asimulator. The results were compared witha simulation of the Statfjord reservoir con-structed entirely deterministically.

Using the MONARCH package, three real-izations of the channel sands were con-structed using 172,000 voxels, each measur-ing 75 m × 25 m × 1.2 m thick [250 ft × 80 ft× 4 ft]. Each realization had to be reduced toabout 10,000 grid blocks before sandwich-ing and simulation. The comparisonsshowed that simulations using the proba-bilistic realizations predicted water break-through far more accurately than an entirelydeterministic simulation. Credited with theimprovement was MONARCH’s ability tocreate a more realistic picture of shale barri-ers within the channel sands. These appearto influence not only water breakthrough inthe channels, but also breakthrough in theoverlying and underlying units that weremodeled deterministically.

Simulation requires intense collaborationbetween geologists and reservoir engineers,a cross-disciplinary challenge that operatorsface in virtually every area of reservoir man-

23January 1992

01977 1979 1981 1983 1985 1987 1989 1991 1993 1995

2nd 3rd

nProduction forecasts from second and third simulations for Shell and Esso’s North SeaBrent field. The second simulation, made in 1982 during field development andintended to investigate plateau-phase production, gave a reasonable forecast for fiveyears. The third simulation, made in 1988 during the decline phase, gives a moreaccurate picture of the field’s later life and allows planning of remedial programs. (Thefirst simulation, not shown, was made at very coarse scale during the appraisal phaseof the field.) (From Johnson, reference 29)

31. Tollas JM and McKinney A: “Brent Field 3-D Reser-voir Simulation,” paper SPE 18306, presented at the63rd SPE Annual Technical Conference and Exhibi-tion, Houston, Texas, USA, October 2-5, 1988.

32. Keijzer JH and Kortekaas TFM: “Comparison ofDeterministic and Probabilistic Simulation Modelsof Channel Sands in the Statfjord Reservoir, BrentField,” paper SPE 20947, presented at Europec 90,The Hague, The Netherlands, October 22-24,1990.

nIncreasing complexity in modeling the producing layers in the Brent and Statfjordreservoirs of Shell and Esso’s North Sea Brent field. In the most recent simulation, sev-eral layers in the Statfjord reservoir were modeled probabilistically and sandwichedbetween deterministic layers. (The first simulation, not shown, was made at very coarsescale during the appraisal phase of the field.)

nOrganizationalchanges thatConoco (U.K.) Ltdimplemented toensure a cross-dis-ciplinary approachwhen planning ahigh-angle well intheir North SeaMurchison field.After restructuring,the key disciplines(boxed)—drillingengineers, geolo-gists, reservoirengineers and geo-physicists—allworked in one teamin the same office.(From King and War-render, reference 33.)

agement. Other options and decisions inreservoir development involve expertisefrom a plethora of disciplines—drilling engi-neering, environmental engineering, facili-ties engineering to name a few. Integratingthem can be hard work.

Conoco (U.K.) Limited has identified sev-eral factors that help.33 On a team of differ-ent experts, there may have to be a boss,but no single expertise should be allowed todominate. As far as management is willingto devolve responsibility, the team shouldset its own goals and audit its achievements.The team should be as independent as pos-sible from the parent structure, and thushave the freedom to react and make deci-sions rapidly—in other words, act likeentrepreneurs (below, left). Last, there mustbe persistent cross-disciplinary communica-tion and education, not only betweenexperts, but also a reaching out to financialand business colleagues in the parent group.

Conoco put this theory into practice whileplanning a highly deviated well in their geo-logically complex North Sea Murchisonfield. The well was intended to tap multipletargets in the main field and south flank.Geoscientists made a detailed interpretationof the south flank so the planned well hitthe targets; drilling engineers decided if themore than 80-degree well was drillable anddesigned a casing program that could han-dle the varying depletion pressures in thedifferent units; and reservoir engineersinvestigated whether the casing programcould be simplified by shutting in existingproducers or injectors to adjust these pres-sure differentials. The design process wasiterative and had to involve partners andoutside specialists. Yet, it was done speedilybecause all experts worked together andwere in constant communication.

In tomorrow’s world, every aspect ofreservoir management will be developedand managed through synergy—by integrat-ing data, by coupling compatible method-ologies and by building teams. Add bettermeasurements for seeing between wells andalmost unimaginable increases in computerpower, and we may see hydrocarbonexploitation becoming as much a science asan art. —HE

24 Oilfield Review

33. King W and Warrender J: “The Murchison Field: AMultidisciplinary Approach to Reservoir Manage-ment,” presented at Advances in Reservoir Technol-ogy, Edinburgh, Scotland, February 21-22, 1991.

345678 9

2ndSimulation

3rdSimulation

Probabilisticsimulation

Statfjord

Probabilistic

GeologicalUnit

Reservoir

Aberdeen

Before

Aberdeen

London

Engineering Development

Operations

Exploration

Production

Drilling

Geology Geophysics

Engineering Reservoir development

Drilling Reservoir Geology Geophysics

Reservoir

trends in reservoir management - schlumberger/media/files/resources/oilfield_review/ors92/... · 10...

Documents

a two host shared macroparasite with spatial heterogeneities

x-ray microdiffraction characterization of deformation...

parameterization of subgrid heterogeneities for hydrologic

heterogeneities and complexity in earthquake dynamics

nanoscale heterogeneities in monolayer mose2...

heterogeneities in fullerene

effect of reservoir heterogeneities on elastic and …

relationship banking and heterogeneities in interest …

sequence heterogeneities among 16s ribosomal rna sequences

large heterogeneities...

imaging geochemical heterogeneities using inverse...

disparate forms of heterogeneities and interactions among

university of groningen the influence of reservoir ... ·...

length scales of mantle heterogeneities and their

effect of the torso conductivity heterogeneities on the

uncertainties in seismic facies analysis for reservoir...

reservoir characterization using expert knowledge,...

working paper 36 – heterogeneities within industries and...

the flow of viscous heterogeneities in mantle plumes

modeling geological heterogeneities and its impact on flow...