基于井距分布的多类资料整合砂体建模
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摘要
为解决传统砂体建模方法资料利用不充分、模型精度较低、模型结果缺乏验证等缺点,提出了基于井距综合多类资料进行砂体建模的新方法.首先从井信息数学模拟结果、沉积微相分布、地震反演砂体预测成果与井距关系入手,建立了不同方位各类资料预测准确率与井距的关系曲线,然后在此基础上建立了不同类型信息在空间的权重场分布.最后应用权重场模型对各类信息整合得到了最终的砂体模型.将该方法应用于吉林扶余油田,通过新井验证,砂体预测符合率达80%以上,而仅用井数据模拟的砂体符合率仅为62%.结果证明,该方法原理正确,资料利用程度高,是进行砂体建模时的有效方法.
To improve conventional sand body model which utilized insufficiently data,had lower precision and required farther checking,a new method integrating various data based on different well spacing was proposed.Firstly,started with analysis of relation between well location and reliability of well modeling,facies,and seismic inversion,the relation curves were obtained at different azimuth.Secondly,based on these curves,the weight field distribution of various data was calculated.Finally,according to the weight field model different types of data were integrated and final sand body model was built.The method succeeded in application in Fuyu oil field. The predicted coincidence rate of sand by the method was up to 80%,while that by well data was 62%.The results show that the method is correct and effective to build a sand body model.
To improve conventional sand body model which utilized insufficiently data,had lower precision and required farther checking,a new method integrating various data based on different well spacing was proposed.Firstly,started with analysis of relation between well location and reliability of well modeling,facies,and seismic inversion,the relation curves were obtained at different azimuth.Secondly,based on these curves,the weight field distribution of various data was calculated.Finally,according to the weight field model different types of data were integrated and final sand body model was built.The method succeeded in application in Fuyu oil field. The predicted coincidence rate of sand by the method was up to 80%,while that by well data was 62%.The results show that the method is correct and effective to build a sand body model.
引文
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[2]HATLY A S.Numerical modeling combining deter-ministic and stochastic methods[C]//YARUS J M,CHAMBERS R L.Stochastic modeling and geosta-tistics.Tulsa:AAPG,1994:109-120.
[3]SOARES A.Sequential indicator simulation withcorrection for local probabilities[J].MathematicalGeology,1998,30(6):761-765
[4]JONES T A.Using flowpaths and vector fields inobject-based modeling[J].Computer&Geosciences,2001,27(1):133-138
[5]JONES T A.FP2VF:Fortran 90 program to generatea vector field from flowpaths[J].Computer&Geo-sciences,2003,29(1):209-214.
[6]BAHAR A,GHANI A,SILVA F P,et al.Seismicintegration for better modeling of rock type basedreservoir characterization:A field case example[J].SPE,2004,88793:2004,1-10.
[7]印兴耀,刘永社.储层建模中地质统计学整合地震数据的方法及研究进展[J].石油地球物理勘探,2002,37(4):423-426.YIN Xing-yao,LIU Yong-she.Methods and devel-opment of integrating seismic data in reservoir model-building[J].Oil Geophysical Prospeting,2002,37(4):423-426.
[8]吕晓光,潘懋,王家华,等.指示主成分模拟建立分流河道砂体相模型及意义[J].石油学报,2003,24(1):53-56.LV Xiao-guang,PAN Mao,WANG Jia-hua,et al.Microfacies modeling for distributary channel sand-body by using indicatorprincipal component simula-tion[J].Acta Petrolei Sinica,2003,24(1):53-56.
[9]吕晓光,张永庆,陈兵,等.深度开发油田确定性与随机建模结合的相控建模[J].石油学报,2004,25(5):60-64.LV Xiao-guang,ZHANG Yong-qing,CHEN Bing,et al.Facies controlled modeling formature developedoil field by integrating determinacy and stochasticmethod[J].Acta Petrolei Sinica,2004,25(5):60-64.
[10]廖新维,李少华,朱义清.地质条件约束下的储集层随机建模[J].石油勘探与开发,2004,31(B11):92-94.LIAO Xin-wei,LI Shao-hua,ZHU Yi-qing.Sto-chastic reservoir modeling restricted by geologicalconditions[J].Petroleum Exploration and Develop-ment,2004,31(B11):92-94.
[11]方杰,赵力民,赵太良,等.用层序地层学构建辫状河三角洲岩性油藏地质模型[J].石油学报,2004,25(5):29-33FANG Jie,ZHAO Li-min,ZHAO Tai-liang,et al.Construction of geologic model for lithologic oil res-ervoirs in braided river delta with sequence stratigra-phy[J].Acta Petrolei Sinica,2004,25(5):29-33.
[12]尹艳树,吴胜和,张昌民,等.用多种随机建模方法综合预测储层微相[J].石油学报,2006,27(2):68-71.YIN Yan-shu,WU Sheng-he,ZHANG Chang-min,et al.Integrative prediction of microfacies with mul-tiple stochastic modeling methods[J].Acta PetroleiSinica,2006,27(2):68-71.
[13]张淑品,于兴河.同位协同随机建模方法在储层预测中的应用[J].天然气地球科学,2006,17(3):378-383.ZHANG Shu-pin,YU Xing-he.The application ofcollocated co-kring stochastic modeling in reservoirdescription[J].Natural Gas Geoscience,2006,17(3):378-383.
[14]曹代勇,王占刚.三维地质模型可视化中直接三维交互的实现[J].中国矿业大学学报,2004,33(4):384-387.CAO Dai-yong,WANG Zhan-gang.Direct 3D-inter-action in 3D geological model visualization[J].Jour-nal of China University of Mining&Technology,2004,33(4):384-387.
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