多点地质统计学研究进展与展望
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摘要
在简要回顾多点地质统计学起源后,介绍了多点地质统计学的3种方法,并总结了多点地质统计学的研究进展。在应用领域,已经从河流相建模发展到扇环境建模,从储集层结构建模发展到储集层物性分布模拟,从宏观地质体预测发展到微观孔喉分布建模,从地质研究发展到地质统计反演。在整合信息建模方面,给出了3种综合地震属性的方法;在算法方面,提出了PRTT实时处理方法,完善了多点地质统计学建模,并开发了新的多点统计生长算法(Growthsim)。对多点地质统计学未来发展进行了展望,指出在训练图像、数据综合以及建模方法耦合方面还需要进一步深入研究。
The paper summarizes the progress of multiple point geostatistics.First the origin of multiple point geostatistics is introduced and the theories of three main multiple-point geostatistic methods are analyzed.Then,the development status is concluded in three aspects.Firstly,in real reservoir modeling domain,the modeling environment is from fluvial to fan facies;the modeling content is from reservoir architecture to reservoir petrophysical property;the modeling scale is from large geologic deposits to micro pores and throats;the modeling region is from geological modeling to geological statistic inversion.Secondly,in integrating multi-disciplines modeling domain,there are three methods for integrating seismic data.Thirdly,in modeling methods domain,there are some improvements and new methods such as PRTT and the Growthsim.Based on the analysis of the development of multiple point geostatistics,the paper points out that the training image,data integration and modeling coupration are the main aims in further studies.
The paper summarizes the progress of multiple point geostatistics.First the origin of multiple point geostatistics is introduced and the theories of three main multiple-point geostatistic methods are analyzed.Then,the development status is concluded in three aspects.Firstly,in real reservoir modeling domain,the modeling environment is from fluvial to fan facies;the modeling content is from reservoir architecture to reservoir petrophysical property;the modeling scale is from large geologic deposits to micro pores and throats;the modeling region is from geological modeling to geological statistic inversion.Secondly,in integrating multi-disciplines modeling domain,there are three methods for integrating seismic data.Thirdly,in modeling methods domain,there are some improvements and new methods such as PRTT and the Growthsim.Based on the analysis of the development of multiple point geostatistics,the paper points out that the training image,data integration and modeling coupration are the main aims in further studies.
引文
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Chugunova T,Hu L Y,Lerat O.2007.Conditioning a Process-Based Flu-vial Model Using a Non-Stationary Multiple-Point Statistics Approach[C].Petroleum Geostatistics Cascais,Portugal.
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Eskandari K,Srinivasan S.2007.Growthsim-A Multiple Point Framework forPattern Simulation:Petroleum Geostatistics Cascais[C].Portugal.
Ezequiel F,Gonzlez.2008.Seismic inversion combining rock physics andmultiple-point geostatistics[J].Geophysics,73(1):11-21.
Farmer,Deutsch C V.1992.Numerical Rocks[M].In:King P(eds).The Mathematical Generation of Reservoir Geology.Oxford,Claren-don Press.
Guardiano F,Srivastava R M.1993.Multivariate Geostatistics:Beyond Bi-variate Moments[C].In:Soares A(ed).Geostatistics-Troia,KluwerAcademic Publications,Dordrecht,1:113-114.
Journel A G.2002.Combining knowledge from diverse sources:An alter-native to traditional data independence hypotheses[J].MathematicalGeology,34(5):573-596.
Li H,Christopher D,White.2003.Geostatistical models for shales in dis-tributary channel point bars(Ferron Sandstone,Utah):Fromground-penetrating radar data to three-dimensional flow modeling[J].AAPG Bulletin,87(12):1851-1868.
Liu.2007.Multi-scale Spatial Simulation of Rock Pores by Geostatisticswith a Scaling Law[C].12th Conference of Int.Association forMathematical Geology.Beijing,China,569-572.
Liu Y,Journel A G.2004.Improving sequential simulation with a struc-tured path guided by information content[J].Mathematical Geology,36(8):945-964.
Liu Y,Harding A,Abriel W,Strebelle S.2004.Multiple-point simulationintegrating wells,three dimensional seismic data,and geology[J].AAPG Bulletin,88(10):905-921.
Luis M,Jesus C.2009.Application of Multiple Point Geostatistics to Non-stationary Images[J].Math.Geosci.,41:29-42.
Neil F,Zhang T.2009.Method to generate fullbore images using boreholeimages and multi-point statistics[J].SPE:120671.
Pyrcz M J,Boisvert J B,Deutsch C V.2009.A library of training imagesfor fluvial and deepwater reservoirs and associated code[J].Comput-er&Geosciences,34:542-560.
Roy P,Strebelle S.2008.Capturing Depositional Processes Using MPSSimulation with Multiple Training Images[C].AAPG ConventionSan Antonio,TX.
Srivastava.1992.Iterative Methods for Spatial Simulation[C].In:Report5.Stanford Centre for Reservoir Forecasting,Stanford,America.
Strebelle S.2000.Sequential simulation drawing structures from trainingimages[D].Strebelle,Stanford University,America.
Strebelle S,Journel A G.2001.Reservoir modeling using multiple-pointstatistics[J].SPE:71324.
Stien M,Abrahamsen P,Hauge R,et al.2007.Modification of the Algo-rithm[C].Petroleum Geostatistics Cascais,Portugal.
Suzuki S,Strebelle S.2007.Real-time Post-Processing Method to EnhanceMultiple-Point Statistics Simulation[C].Petroleum GeostatisticsCascais,Portugal.
Wang L.1996.Modeling complex reservoir geometries with multiple-pointstatistics[J].Mathematical Geology,28(7):895-901.
Zhang T.2008.Incorporating geological conceptual models and interpreta-tions into reservoir modeling using multiple-point geostatistics[J].Earth Science Frontiers,1:16-23.
Zhang T,Bombard S,Strebelle S,et al.2006b.3D porosity modeling of acarbonate reservoir using continuous multiple-point statistics simula-tion[J].SPE:96308.
Zhang T,Switzer P,Journel A G.2006a.Filter-based classification oftraining image patterns for spatial simulation[J].Math.Geol.,38(1):63-80.
吴胜和,李文克.2005.多点地质统计学——理论、应用与展望[J].古地理学报,7(1):137-144.
尹艳树,吴胜和,张昌民,等.2006.多种随机建模方法综合预测储集层微相[J].石油学报,27(2):68-71.
尹艳树,吴胜和,张昌民,等.2008.基于储集层骨架的多点地质统计学方法[J].中国科学,38(增刊Π):157-164.
张春生,刘忠保,施冬.2000.三角洲分流河道及河口坝形成过程的物理模拟[J].地学前缘,7(3):168-176.
张挺,卢德唐,李道伦.2010.基于二维图像和多点统计方法的多孔介质三维重构研究[J].中国科学技术大学学报,40(3):271-277.
Arpat B G.2005.Sequential simulation with patterns[D].Stanford Uni-versity,America.
Caers J,Zhang T.2002.Multiple-point Geostatistics:A Quantitative Ve-hicle for Integrating Geologic Analogs into Multiple Reservoir Models[C].In:Grammer G M et al.(eds).AAPG Memoir:Integration ofOutcrop and Modern Analog Data in Reservoir Models.
Caers J,Srinivasan S,Journel A G.1999.Geostatistical identification ofgeological information in a north-sea reservoir[J].SPE:56655.
Chugunova T,Hu L Y,Lerat O.2007.Conditioning a Process-Based Flu-vial Model Using a Non-Stationary Multiple-Point Statistics Approach[C].Petroleum Geostatistics Cascais,Portugal.
Deutsch C V,Wang L.1996.Hierarchical object-based stochastic modeling offluvial reservoirs[J].Mathematical Geology,28(7):857-880.
Eskandari K,Srinivasan S.2007.Growthsim-A Multiple Point Framework forPattern Simulation:Petroleum Geostatistics Cascais[C].Portugal.
Ezequiel F,Gonzlez.2008.Seismic inversion combining rock physics andmultiple-point geostatistics[J].Geophysics,73(1):11-21.
Farmer,Deutsch C V.1992.Numerical Rocks[M].In:King P(eds).The Mathematical Generation of Reservoir Geology.Oxford,Claren-don Press.
Guardiano F,Srivastava R M.1993.Multivariate Geostatistics:Beyond Bi-variate Moments[C].In:Soares A(ed).Geostatistics-Troia,KluwerAcademic Publications,Dordrecht,1:113-114.
Journel A G.2002.Combining knowledge from diverse sources:An alter-native to traditional data independence hypotheses[J].MathematicalGeology,34(5):573-596.
Li H,Christopher D,White.2003.Geostatistical models for shales in dis-tributary channel point bars(Ferron Sandstone,Utah):Fromground-penetrating radar data to three-dimensional flow modeling[J].AAPG Bulletin,87(12):1851-1868.
Liu.2007.Multi-scale Spatial Simulation of Rock Pores by Geostatisticswith a Scaling Law[C].12th Conference of Int.Association forMathematical Geology.Beijing,China,569-572.
Liu Y,Journel A G.2004.Improving sequential simulation with a struc-tured path guided by information content[J].Mathematical Geology,36(8):945-964.
Liu Y,Harding A,Abriel W,Strebelle S.2004.Multiple-point simulationintegrating wells,three dimensional seismic data,and geology[J].AAPG Bulletin,88(10):905-921.
Luis M,Jesus C.2009.Application of Multiple Point Geostatistics to Non-stationary Images[J].Math.Geosci.,41:29-42.
Neil F,Zhang T.2009.Method to generate fullbore images using boreholeimages and multi-point statistics[J].SPE:120671.
Pyrcz M J,Boisvert J B,Deutsch C V.2009.A library of training imagesfor fluvial and deepwater reservoirs and associated code[J].Comput-er&Geosciences,34:542-560.
Roy P,Strebelle S.2008.Capturing Depositional Processes Using MPSSimulation with Multiple Training Images[C].AAPG ConventionSan Antonio,TX.
Srivastava.1992.Iterative Methods for Spatial Simulation[C].In:Report5.Stanford Centre for Reservoir Forecasting,Stanford,America.
Strebelle S.2000.Sequential simulation drawing structures from trainingimages[D].Strebelle,Stanford University,America.
Strebelle S,Journel A G.2001.Reservoir modeling using multiple-pointstatistics[J].SPE:71324.
Stien M,Abrahamsen P,Hauge R,et al.2007.Modification of the Algo-rithm[C].Petroleum Geostatistics Cascais,Portugal.
Suzuki S,Strebelle S.2007.Real-time Post-Processing Method to EnhanceMultiple-Point Statistics Simulation[C].Petroleum GeostatisticsCascais,Portugal.
Wang L.1996.Modeling complex reservoir geometries with multiple-pointstatistics[J].Mathematical Geology,28(7):895-901.
Zhang T.2008.Incorporating geological conceptual models and interpreta-tions into reservoir modeling using multiple-point geostatistics[J].Earth Science Frontiers,1:16-23.
Zhang T,Bombard S,Strebelle S,et al.2006b.3D porosity modeling of acarbonate reservoir using continuous multiple-point statistics simula-tion[J].SPE:96308.
Zhang T,Switzer P,Journel A G.2006a.Filter-based classification oftraining image patterns for spatial simulation[J].Math.Geol.,38(1):63-80.
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