IBM -工智能时代的油气上游业务 为什么人工智能不能扩展以及如何修复它 Upstream oil and gas in the AI era Why AI isnt scaling and how to fix it

IBMInstituteforBusinessValue|ResearchBrief

UpstreamoilandgasintheAIera

WhyAIisn’tscalingandhowtofixit

HowIBMcanhelp

IBMworkswithpetroleumandchemicalscompaniestoresponsiblyscaleAIandbuildacleanenergytransition.Learnhowoursolutionscanhelpcreateadata-drivenstrategythatstreamlinesdigital

transitionandpreparesyourcompanyforasustainablefuture.Formoreinformation,pleasevisit:/industries/energy

Contents

Foreword 4

Part1

Rapidlyadaptingtoamore

complexupstreamfuture 5

Part2

WhereAIisdeliveringvalue

today—andhowthatvalueisevolving 8

Part3

WhyAIisn’tscaling—andwhatthat

revealsaboutupstreamoperations 11

Actionguide 19

2

Keytakeaways

ScalingAIrequires

redesigninghowupstreamoperationswork.

57%oforganizationscite

fragmenteddataandonly9%

reportreal-timeOT/ITintegration,whichpreventsAIfromoperating

atsystemscale.Unlockingvalue

dependsonaligningdata,decisions,andexecutionacrosssubsurface,

drilling,andproduction.

ExecutivesseeAIasa

coredriverofcompetitive

advantage,butsystem-

levelimpactremainslimited.

93%expectAItodeliver

measurableadvantage,yetmostorganizationshavenottranslatedthatconvictionintoenterprise-

wideperformance.Most

deploymentsremainfocusedon

individualworkflowsandproof-of-conceptsratherthanend-to-endoperationalprocesses,limitingtheabilitytocapturecoordinated

benefitsacrossthevaluechain.

AIisdeliveringmeasurablevalue,butprimarilywithinindividualworkflows.

Operationalgainsindrilling

non-productivetime(–12%),well

deliverycycletime(–9%),andsafetyincidents(–16%)arewellestablished.However,thesegainsremain

concentratedwithinspecific

processesratherthanextending

acrossthefullassetandvaluechain.

UpstreamoilandgasintheAIera3

ForewordPartone

|

Parttwo

|

Action

Partthree

guide

Foreword

ZahidHabib

VicePresident,GlobalIndustrialSectorLeader

GlobalEnergyandResourcesIndustryLeader

IBMConsulting

Upstreamoilandgasoperations

areenteringamoredemanding

phaseofperformance.Volatile

markets,pressuretoreducefixed

andoperatingcosts,tightercapitaldiscipline,growingemissions

expectations,andincreasingly

complexglobalportfoliosare

forcingoperatorstodelivermore

withgreaterspeed,precision,andcoordinationthantraditionalmodelsweredesignedtosupport.

Fordecades,performance

improvementscamefromoptimizingindividualdomains.Subsurface,

drilling,andproductionsystems

evolvedlargelyindependently,eachmaximizingefficiencyandreliabilitywithinitsscope.Thatmodeldeliveredsteadygainsinamorestableandlessconnectedoperatingenvironment.

Today,thatmodelisreachingits

limits.Upstreamoperationsarenowdeeplyinterconnected.Decisionsinonepartoftheassetincreasingly

dependonconditionsinotherparts.Yetdata,workflows,anddecision-makingremainfragmented.Asa

result,organizationsgeneratemoreinsightthanever,butstruggleto

translateitintocoordinatedactionacrossthesystem.

AIischangingwhatistechnically

possible.Acrossdrilling,production,andassetreliability,organizationsarealreadyrealizingmeasurablegains

includingreductionsindrilling

non-productivetime,fasterwell

delivery,andfewersafetyincidents.

Increasingly,AIisalsotakingtheformofindustrialdigitalworkersthatcancontinuouslymonitorconditions,

supportdecisions,andcoordinate

activitiesacrossoperations.YetthechallengeisnolongerwhetherAI

works.Itiswhetherorganizationsarestructuredtoscalethatvaluebeyondindividualworkflowstothelevelofthefullassetandenterprise.

Thisreportshowsthattheconstraintisnotalackofusecases,investment,ortechnicalcapability.Itisamismatchbetweenhowupstreamoperations

areorganizedandwhatisneededtooperateintelligentlyatscale.

ClosingthatgaprequiresmorethandeployingadditionalAIsolutions.Itdemandsashiftfromoptimizingdiscreteactivitiestoorchestratingend-to-endworkflowsthatconnectreservoir,drilling,andproductiondecisionsacrosstheasset.

TheleadersthatsucceedwillnotsimplyadoptAI.Theywillredesignhowtheiroperationswork.

UpstreamoilandgasintheAIera4

ForewordPartoneParttwoPartthreeActionguide

Partone

Rapidlyadaptingtoamore

complexupstreamfuture

Upstreamoilandgasoperationsarebecomingmorecomplex,moredistributed,andmoredata-intensive.

Operatorsmanageassetsacrossdiversegeographiesandenvironmentswhilebalancingperformance,cost,safety,andemissionsobjectives.Atthesame

time,activitiesacrossdomainsgeneratetremendousvolumesofdata.

Yetthecentralchallengeisnolongeraccesstodataoranalytics.Itistheabilitytoactonthatdataasacoordinatedsystem.

5

UpstreamoilandgasintheAIera

UpstreamoilandgasintheAIera6

ForewordPartoneParttwoPartthreeActionguide

FIGURE1

StrongexecutiveconvictioninAI-drivencompetitiveadvantage

Today,mostupstreamorganizationsstilloperatethroughlooselyconnecteddomains.Subsurface,drilling,andproductionsystemsgenerateinsights

independently,butdatadoesnotflowconsistentlyacrossthem,and

decision-makingisnotfullyaligned.Asaresult,improvementswithinone

domaindonotreliablytranslateintoimprovedoutcomesacrossthefullasset.

AIisbeginningtoexposeandpartiallyaddressthislimitation(seeFigure1).Organizationsareapplyingittoimprovedrillingperformance,optimizedrillpadplanningandexecution,enhanceproduction,strengthenreliability,andimprovesafetyandenvironmentaloutcomes.TheseusecasesdemonstratethatAIcangeneratemeaningfuloperationalgainsandsupportmore

predictive,data-drivendecisions.

and

88%

saythatAIwillsignificantly

enhancetheabilitytorespondquicklytomarketdisruptions.

93%

ofupstreamoilandgasexecutivessaythatinvestinginAIwilldeliverclearandmeasurablecompetitiveadvantagestotheircompanywithinthenext3years.

Source:Q1.1,Q1.8TowhatextentdoyouagreewiththefollowingstatementsabouttheuseofAIacrossyourorganization?

Atthesametime,AIistakingonabroaderrole.Itisincreasinglyembeddedinreal-timemonitoring,remoteoperations,andcontinuousoptimization

environments,enablingdecisionstobemadefasterandclosertothepointofexecution.Thissignalsanimportantchange.Performanceisnolonger

determinedbyhowwellindividualsystemsoperate,butbyhoweffectivelytheyworktogether.

UpstreamoilandgasintheAIera7

ForewordPartoneParttwoPartthreeActionguide

Thisevolutionisalsochanginghoworganizationsthinkaboutinvestment

(seeFigure2).AIismovingfromasetofdiscretetoolstoafoundationfor

moreintegrated,responsiveoperations.However,mostorganizationshavenotyetrealizeditsfullpotential.

WhileAIcangenerateinsightsacrossthevaluechain,mostorganizations

arenotyetorganizedtoactonthoseinsightsinacoordinatedway.Data

remainsfragmented,systemsremainpartiallyintegrated,anddecision-

makingauthorityisnotconsistentlyalignedwithAI-drivenrecommendations.

Theconstraintisnolongeranalyticalcapability.Itistheenterprise’sabilitytotranslateinsightintosynchronizedactionacrossend-to-endworkflows.Thisisthecriticalgapbetweenstrongexecutiveconvictionpairedwith

growingAIinvestmentandtherealizationofsystem-levelvalue.Until

organizationsconnectdata,decisions,andexecutionacrosssubsurface,drilling,andproduction,muchofAI’spotentialwillremainconfinedto

individualworkflowsratherthancoordinatedassetperformance.

FIGURE2

AIinvestmentgrowinginupstreamoperations

2023-202520262029

9%13%18%

AIspendasapercentageofannualITbudget

Source:D5.Whatis/willbeyourtotalAIspendasapercentageofyourannualITbudget?

Actionguide

Foreword

Partone

Parttwo

Partthree

UpstreamoilandgasintheAIera8

FIGURE3

OperationalperformanceimprovementsfromAIadoption

Parttwo

Improvements

valuetoday—andhowthat

valueisevolving

AIisdeliveringmeasurablevalueacrossupstreamoperations,butthatvalueremainsstructurallyconstrained.

Today,thestrongestandmostconsistentimpactisinoperationalperformance(seeFigure3).AIisreducingvariability,improvingpredictability,andenhancingexecutionacrossdrilling,production,andmaintenance.Itisalsostrengtheningreliabilityandsafetybyenablingearlierdetectionofissuesandfasterresponse.

Thesegainsarenotincidental.Theyareconcentratedinareaswithrepeatableworkflows,cleardecisionboundaries,andhighdataavailabilitywhereAIcanbeembeddedintoexistingprocesseswithrelativelylimitedorganizational

change.Asaresult,mostofthevaluecreatedtodayalignswiththetraditionalupstreammodelofdiscipline-leveloptimization.

Thisisbothastrengthandalimitation.

WhereAIisdelivering

16%

lowersafetyincidentsdisruptingoperations

12%

lowerdrillingnon-productivetime(NPT)

9%

shorterwelldeliverycycletime

8%

betterenergyefficiency(fuel/powerintensity)

5%

lowerliftingcost/OpexperBOE

5%

lowerdeferredproduction/uptime

Source:Q5.TowhatextenthasAIimpactedyourupstreamoperations’performanceinthefollowingareas?

Actionguide

Foreword

Partone

Parttwo

Partthree

ItshowsthatAIworks.Butitalsoexplainswhyitsimpactisnotextending

acrossthefullasset.Whendeployedwithinexistingworkflows,AIimprovesindividualpartsofthesystem,butdoesnotfundamentallychangehowthosepartsoperatetogether.Asaresult,gainsinonedomainsuchasdrillingor

productiondonotconsistentlytranslateintoimprovedperformanceatthesystemlevel.

Atthesametime,ashiftisbeginning.OrganizationsareexpandingAIbeyonddiscreteusecasesintomorepersistent,service-basedoperatingmodels.

MorethanhalfareembeddingAIincontinuousenvironmentssuchasremoteoperations,always-onmonitoring,andreal-timeoptimization,signaling

amovefromproject-baseddeploymenttowardoperationalcapability.

Thisreflectsagrowingrecognition.Valueisnolongercreatedsolelybyoptimizingindividualworkflows,butbycoordinatingdecisions

andexecutionacrossthem.

Yet,despitethisprogress,impactremainsbounded.

UpstreamoilandgasintheAIera9

UpstreamoilandgasintheAIera10

ForewordPartoneParttwoPartthreeActionguide

Whileoperationalgainsarewellestablishedandnewcapabilitiesareemerging(seeFigure4),theyarenotyettranslatingintocoordinated,system-level

outcomes.AIisbeingdeployedmorebroadly,buttheunderlyingoperatingmodellimitshowfarthatvaluecanextend.

TheresultisaclearAIcoordinationgap.

ClosingthatgaprequiresmorethanexpandingAIusecases.Itrequires

movingbeyondisolatedapplicationstowardAI-enabledoperational

workflowsincludingemergingindustrialdigitalworkersthatcancoordinate

activitiesandsupportdecisionsacrossfunctions.Organizationsmustconnectdata,decisions,andexecutionacrossend-to-endworkflows,fromreservoir

anddrillingthroughproductionoperations,sothatAIcancreatevalueatthesystemlevelratherthanwithinisolatedfunctions.Bydoingso,theycanextendAI’simpactbeyondindividualworkflowsandunlocksystem-levelimprovementsinproduction,reliability,safety,andcapitalefficiency.

FIGURE4

AIspendtoincreaseforinnovationanddecreaseforoperationalefficiency

BreakdownofAIspend

20262029

20%

24%

Businessmodelinnovation

Product/serviceinnovation

Efficiency/operationaleffectiveness

28%

32%

52%

44%

Source:Q2.Howis/doyouexpectyourorganization’supstreamAIspendallocatedacrosseachofthefollowing?

Actionguide

Foreword

Partone

Parttwo

Partthree

UpstreamoilandgasintheAIera11

Partthree

WhyAIisn’tscaling—andwhatthatrevealsabout

upstreamoperations

AIisnotfailinginupstreamoilandgas.Itisdelivering

measurablevalue.Whatisfailingistheabilitytoscalethatvalueacrosstheenterprise.

Mostorganizationshavealreadymovedbeyondearlyexperimentation.Theyreportstrongleadershipsupport,growinginternalcapabilities,

andincreasinguseofstrategicpartnerships.

AIisbeingdeployedacrosssubsurface,drilling,production,andsupporting

functions(seeFigure5).Theissueisnotadoption.Itisscale.Individualuse

casesandproofsofconceptcandemonstratevalue,buttheyrarelytransformperformance.End-to-endworkflowsarewhatultimatelycreatesystem-levelvalueandscale.

FIGURE5

AIadoptionacrossupstreamoperations

Productionandcoreoperations

47%

Assetintegrity

andlatelife/

decommissioningmanagement

Wellsurveillanceandanomaly

detection

Facility

operationsoptimization

Production

optimization

Predictive

maintenance

64%

68%

54%

51%

Drillingandcompletions

23%

Drilling

planning,

geosteering,andreal-timeoptimization

Completionsoptimization

49%

Subsurface

andexploration

47%

Subsurface

analysisand

reservoir

characterization

Source:Q4A.Whatisyourorganization’scurrentlevelofAIimplementationineachofthefollowingupstreamareas?(figuresinclude“Rollingout”and“Fullyimplemented”)

Coordination,

safetyandsupport

51%

HSEmonitoringandincident

prevention

50%

60%

57%

Regulatoryreportinganddocumentationautomation

Emissions

monitoring

andreduction

Fieldlogisticsandworkforcescheduling

UpstreamoilandgasintheAIera12

UpstreamoilandgasintheAIera13

ForewordPartoneParttwoPartthreeActionguide

FIGURE6

WhyAIdoesnotscaleinupstreamoperations

Therootcauseisstructural.Upstreamoperatingmodelsevolvedtooptimize

individualdisciplinessuchassubsurface,drilling,andproduction,eachwithits

owndata,workflows,anddecisionprocesses.Thatapproachdeliveredsignificantgainswithinfunctions,butitwasnotdesignedforthecoordinated,system-

57%

oforganizationscitedata

fragmentationasamajorbarriertoscalingAI.

Only

9%

levelexecutionthatAIrequires.Asaresult,theoperatingmodelitselfnowlimitshowfarAIcanscaleacrosstheenterprise.

Threereinforcingconstraintsdefinethischallenge(seeFigure6).

reportreal-timeintegrationbetweenOTandITsystems.

Source:Q9.WhichfactorsmostlimityourabilitytoimplementandscaleAIandautonomoussystemsacrossupstream?;Q11.Whichofthefollowingbestdescribesyourorganization’sOT/ITintegrationforpriorityupstreamworkflowstoday?;Q12.Whichofthefollowingbestdescribesyourorganization’s

currentdatareadinessforadvancedandagenticAIinupstreamoperations?

Just

12%

haveachievedenterprise-leveldataintegrationacross

upstreamoperations.

UpstreamoilandgasintheAIera14

ForewordPartoneParttwoPartthreeActionguide

First,AIdependsonastrongerdatafoundation.Organizationsaremaking

progresswithAI,butscalingbeyondindividualusecasesrequiresdatathat

ismoreconsistentlystructured,connected,andreusableacrosssubsurface,

drilling,andproduction.Thisbecomesevenmoreimportantasorganizations

movefromisolatedAIapplicationstowardAI-enabledoperationalworkflows,includingemergingindustrialdigitalworkersthatrelyonsharedcontextacrossfunctions.Strengtheningdatainteroperabilityhelpsmodelsoperateacross

workflows,enablesinsightstoflowbetweendomains,andincreasesthereturnonexistingAIinvestments.

Second,scalingAIrequirestighterOT/ITintegration.Greaterconnectivity

betweenoperationalandenterprisesystemscreatesthecontextAIneeds

tosupportreal-timedecisionsandexecution.AsorganizationsimproveOT/ITintegration,theycanincreasinglyembedAIintoliveworkflowswheretiming,coordination,andoperationalawarenessarecritical.

Third,AIcreatesanopportunitytomodernizedecisiongovernance.AsAI

becomesmoreembeddedinoperations,organizationsneedclearerdecision

rights,accountability,andoperationalguardrails.EstablishingthesegovernancemechanismsallowsAItoevolvefromanadvisorytoolintoamoreactive

participantinexecutionwhilemaintainingsafety,auditability,andcontrol.

Thesecapabilitiesreinforceoneanother.Improvingdatareadinessenables

greaterintegration.Greaterintegrationsupportsmorecoordinateddecision-

making.AndclearerdecisionrightsallowAItobecomemoredeeplyembeddedinexecution.Together,thesecapabilitiescreatethefoundationformoving

fromisolatedAIsuccessestocoordinated,system-levelimpact—andultimatelytowardAI-enabledoperationalworkflowswhereindustrialdigitalworkerscan

supportdecisions,coordinateactivities,andexecutedefined

tasksacrosstheasset.

UpstreamoilandgasintheAIera15

ForewordPartoneParttwoPartthreeActionguide

Thislimitationbecomesmostacuteinmoreadvanced

applicationsofAI(seeFigure7).Acrossclosed-loop

drilling,autonomousproduction,andintegrityrisk

prevention,mostorganizationsremaininpilotor

evaluationstageswithagenticAI.Movingfromdecisionsupporttoautonomousexecutionrequiresintegrated

data,synchronizedsystems,andclearauthoritythatmanyorganizationshavenotyetestablished.

Asaresult,AIimprovesindividualworkflowsbutdoesnotyetenablecoordinated,system-levelperformance.

Integrityriskprevention(detecttodiagnosetointerveneworkflows)

11%

1%

Autonomousmaintenanceorchestration

2%

TheoperatingmodeldefineshowfarAIcanscaleacross

theenterprise.

FIGURE7

Piloting

Rollingout

Fullyimplemented

AgenticAIadoptionacrossupstreamoperations

35%

20%

38%

11%

35%

12%

32%

23%

18%

21%

Autonomoussubsurface

interpretation/prospectranking

Closed-loopdrilling

optimization(withinguardrails)

Autonomousproductionoptimization

2%

Emissionsmonitoringtomitigationexecution

13%

Source:Q6A.Whatisyourorganization’scurrentstageofagenticAIimplementationineachofthefollowingupstreamareas?

UpstreamoilandgasintheAIera16

ForewordPartoneParttwoPartthreeActionguide

Thisgapbecomesvisibleinhow

organizationsareoperatingtoday

(seeFigure8).Standardsare

inconsistentacrossprojects,

limitingreuseofdata,models,and

decisionlogic.Governanceremains

localized,withdecisionrightsdefinedforpilotsratherthanenterprise-wideexecution.Authorityisconstrained,

withAIprimarilyrecommending

actionsratherthanexecutingwithindefinedguardrails.

Thesearenotisolatedissues.Theyaresymptomsofadeepermisalignment

betweenlegacyoperatingmodels

andtherequirementsforAI-enabledoperations.

FIGURE8

AIremainslocalizedwhengovernance,decisionlogic,andautonomyarenotscaled

Standards

Mostorganizationshavenot

standardizedthedata,rules,anddecisionlogicneededtoreuseAIacrossprojects.

Governance

MostorganizationsdefineAI

decisionrightsforpilots—butfewhaveformalizedenterprisegovernanceforscaled

productionuse.

Authority

AIremainsprimarilyadvisory,withlimitedauthorityto

executedecisions.

61%

areonlypartlyconsistentorlargelyinconsistent

40%

definedecisionrightsforpilotsonly

41%

useAItorecommend

actionswithhumanapproval

Only

5%

arefullyconsistent

Only

5%

haveenterprise-widedecisionrightswithescalationpaths

andauditability

Only

5%

allowAItoexecutehigh-

riskactionsunderguardrails

Source:Q13.Acrossyourorganization’smajorupstreamprojects,howconsistentarethedatadefinitions,rules,anddecisionlogicusedbyyourcurrentAIsystems?;Q14.WhichofthefollowingbestdescribeshowcurrentdecisionrightsaredefinedforAI-drivendecisionsinupstreamoperations?;Q15.WheredoesyourorganizationcurrentlydrawthelineregardingAIautonomy(thatis,agenticAI)inupstreamoperations?

UpstreamoilandgasintheAIera17

ForewordPartoneParttwoPartthreeActionguide

ScalingAIrequiresafundamentalchangeinhowupstreamoperationsarestructured(seeFigure9).Organizations

needtomovefromsiloeddataenvironmentstoaunified

operationaldatalayerthatconnectssubsurface,drilling,

andproduction;frompilot-baseddeploymentsto

embedded,continuousAIintegrateddirectlyintolive

workflows;andfromadvisoryanalyticstoexecution-linkedAI,withclearlydefineddecisionrightsandoperational

guardrailsthatenableconsistent,system-levelaction.

Thistransitionredefineshowvalueiscreated.

Performanceisnolongerdrivenbyisolatedoptimizationwithindisciplines,butbytheabilitytocoordinatedata,decisions,andexecutionacrossthesystem.

OrganizationsthatmakethishappencanextendAI

beyondlocalizedgainstoenterprise-scaleimpact.Thosethatdonotwillcontinuetogenerateinsightbutstruggletotranslateitintocoordinatedaction.

FIGURE9

TheoperatingmodelshiftrequiredtoscaleAI

AI-scaledmodel

Traditionalmodel

Cross-assetcoordination

Execution-Embedded

linkedAIoperationalAI

Asset-leveloptimization

Siloeddata

Pilot-basedAI

Advisoryanalytics

Integrateddatalayer

Source:IBMConsultinganalysis

UpstreamoilandgasintheAIera