油藏流线模拟与表征方法研究进展

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中图分类号：TE319 文献标志码：A 文章编号：1000-7393（2025）-02-0131-13

Abstract：Aswaterfloodedmatureoilfieldsenterthestageofdeepandrefieddevelopment，thecomplexdynamicsofsubsurface oil-waterdistributionimposehigherdemandsonreservoirmanagement.Thispapersystematicallyreviews theresearchprogressof streamlinesimulationtechnologyforreservoirdevelopment，outliningitsdevelopmental trajectoryfromtwo-dimensionaltracing algorithmtotree-dimensionalmultiphasefowmodels，andfurthertotheintelligentstage.Thealgorithmicprincipleofenancing computationaleficiencythroughdimensionalityreduction（decomposingthree-dimensionalflowfieldsintoone-dimensional streamlines）iselucidated.Thestreamlinetechnologyiscategorizedintotwocomponents：streamlinesimulationandstreamline characterizationTheformerrevealsfluidflowpattmsinporous mediabysolvingpressreandsaturationfields，whilethelater accomplishesvisual modelingofflowtrajectoriesthroughvelocityfieldreconstruction，streamlinepathtracing，andmultipysical parameter transfer.The studycomprehensivelysummarizes aplications ofstreamline simulationin aiding history matchingand modeloptimization，reservoirmodelupscalingandcomputationalaceleration，characterizationofcomplexdisplacement mechanisms，svranagementandotimtion，waterinjectioadwellattoization，aswellasdyamicalyisnd uncertaintyquantification.However，curentstreaminesimulationtchologyfaceschallengesinmulti-physicalfieldcoupling modeling，acros-scale computational eficiency，and data dependency.Breakthroughsin machine learning，adaptivemesh optimization，and high-performancecomputing integration are urgently needed to support sustainable energy development

Key words：streamline simulation; streamline tracing; reservoir development; multiphysics field coupling; machine learning

0 引言

随着全球众多油田开发逐渐步入中后期阶段，常规水驱油田普遍面临含水率上升、剩余油分布高度复杂化等挑战，油藏管理的精细化与实时决策需求日益迫切。（剩余29180字）