低孔渗砂岩孔隙结构分类方法研究
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摘要
低孔渗砂岩储层孔隙结构复杂,在二维与三维空间中具有较强非均质性,对储集空间的测井响应有极大影响。而压汞曲线、核磁T_2谱、铸体薄片3种资料在一定程度上各自反映了孔隙结构的不同特征,本文分别提取3种资料的微观孔隙结构参数进行相关性分析,最终分别利用主成分分析-模糊均值聚类方法实现孔隙结构分类,其分类结果压汞曲线分形法所得一致。
The pore structure of the low permeability sandstone reservoir is complex and has strong heterogeneity in two-dimensional and three-dimensional space, and it has a dramatic effect on logging response of reservoir. However, the mercury intrusion curves, NMR T_2 spectrum and thin section three kinds of data each reflects the different characteristics of the pore structure in some way. In this paper, the microscopic pore structure parameters of three kinds of data were extracted for correlation analysis, finally, pore structure classification was achieved respectively by PCA-FCM, and the classification result is consistent with the mercury intrusion curve fractal method.
The pore structure of the low permeability sandstone reservoir is complex and has strong heterogeneity in two-dimensional and three-dimensional space, and it has a dramatic effect on logging response of reservoir. However, the mercury intrusion curves, NMR T_2 spectrum and thin section three kinds of data each reflects the different characteristics of the pore structure in some way. In this paper, the microscopic pore structure parameters of three kinds of data were extracted for correlation analysis, finally, pore structure classification was achieved respectively by PCA-FCM, and the classification result is consistent with the mercury intrusion curve fractal method.
引文
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[14]葛新民,范宜仁,唐利民,等.基于信息熵-模糊谱聚类的非均质碎屑岩储层孔隙结构分类[J].中南大学学报:自然科学版, 2015,(6):2227-2235.Ge XM, Fan YR, Tang LM, et al. Pore structure typing of heterogeneous clastic reservoir using information entropy-fuzzy spectral clustering algorithm[J]. Journal of South University:Science and Technology, 2015,(6):2227-2235.(in Chinese).
[2]徐雪峰.基于三水导电模型的裂缝性致密砂岩测井解释方法与应用[J]. CT理论与应用研究, 2012,21(2):221-229.Xu XF. Logging interpretation and application based on three-water model in fractured tight sand reservoirs[J]. CT Theory and Applications, 2012, 21(2):221-229.(in Chinese).
[3]郎东江,伦增珉,吕成远,等.致密砂岩储层流体参数核磁共振实验研究[J]. CT理论与应用研究,2015, 24(2):251-259. doi:10.15953/j.1004-4140.2015.24.02.05.Lang DJ, Lun ZM, Lv CY, et al. Study of tight sandstone reservoir core fluidparameters by NMR[J]. CT Theory and Applications, 2015, 24(2):251-259. doi:10.15953/j.1004-4140.2015.24.02.05.(in Chinese).
[4]YanJP,HeX,GengB,etal.NuclearmagneticresonanceT2spectrum:Multifractal characteristics and pore structure evaluation[J]. Applied geophysics, 2017, 14(2):205-215.
[5]任晓娟.低渗砂岩储层孔隙结构与流体微观渗流特征研究[D].西安:西北大学, 2006.Ren XJ. Pore structure of low permeability sand rock and fluid flowing characteristics[D].Xi’an:Northwest University, 2006.(in Chinese).
[6]Marc Fleury. NMR surface relaxivity determination using NMR apparent diffusion curves and BET measurement[C]//SCA2007-35.(in Chinese).
[7]陈华,潘克家,谭永基.核磁共振弛豫信号多指数反演新方法[J].测井技术, 2009, 33(1):37-41.Chen H, Pan KJ, Tan YJ. A new method for multi-exponential inversion of NMR relaxation signal[J]. Well Logging Technology, 2009, 33(1):37-41.(in Chinese).
[8]Grove C, Jerram DA. jPOR:An imageJ macro to quantify total optical porosity from blue-stained thin sections[J]. Pergamon Press, Inc, 2011, 37:1850-1859.
[9]王勇,鲍志东,刘虎.低孔低渗储层评价中数学方法的应用研究[J].西南石油大学学报, 2007,29(5):8-12.Wang Y, Bao ZD, Liu H. Application of mathematical methods in evaluation of low porosity and low permeability reservoir[J]. Journal of Southwest Petroleum University, 2007, 29(5):8-12.(in Chinese).
[10]李海燕,徐樟有.新立油田低渗透储层微观孔隙结构特征及分类评价[J].油气地质与采收率, 2009,16(1):21-25+116.Li HY, Xu ZY. Microscopic pore structure and classification evaluation of low permeability reservoirs in Xinli oilfield[J]. Petrolum Geology and Recovery Efficiency, 2009, 16(1):21-25+116.(in Chinese).
[11]王文博,陈秀芝.多指标综合评价中主成分分析和因子分析方法的比较[J].统计与信息论坛, 2006,21(5):19-22.Wang WB, Chen XZ. Comparison of principal component analysis with factor analysis in comprehensive multi-indicators scoring[J]. Satics&Information Forum, 2006, 21(5):19-22.(in Chinese).
[12]Bezedek JC. A convergence theorem for the fuzzy ISODATA clustering algorithms[J]. IEEE Transactions on Pattern Analysis&Machine Intelligence, 1980, 2(1):1-8.
[13]Bezdek JC, Hathaway RJ, Sabin MJ, et al. Convergence theory for fuzzy c-means:Counter examples and repairs[J]. IEEE Trans on Systems, Man, and Cybernetics-part B:Cybernetics,1987, 17(5):873-877.
[14]葛新民,范宜仁,唐利民,等.基于信息熵-模糊谱聚类的非均质碎屑岩储层孔隙结构分类[J].中南大学学报:自然科学版, 2015,(6):2227-2235.Ge XM, Fan YR, Tang LM, et al. Pore structure typing of heterogeneous clastic reservoir using information entropy-fuzzy spectral clustering algorithm[J]. Journal of South University:Science and Technology, 2015,(6):2227-2235.(in Chinese).