河道纹理属性分析中的灰度共生矩阵参数研究
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摘要
河道纹理是河流相沉积引起的地震振幅强弱变化的动力学表征。计算地震纹理属性时,灰度共生矩阵多个相互关联参数的不同选择组合对运算速度和应用效果有很大的影响。依据现代曲流河形态抽象出一个简化的三维曲流河道储层模型,通过三维高斯射线束方法数值模拟出一个无噪声的叠后地震数据体。选择不同组合的四个关键参数(灰度阶数、分析窗口尺度、灰度点对间的方向和步长),从正演地震数据中计算出四种常用的灰度共生矩阵的二次统计特征量(能量、熵、对比度和均质性)。从理论公式和水平切片的视觉效果两个角度评判,得出了一组适合描述河道纹理的灰度共生矩阵参数。其中能量和熵选择小灰度级,对比度和均质性选择高灰度级,分析窗口尺度最大为地质目标尺度的一半,灰度点对方向选择0°、45°、90°和135°四个方向,灰度点对步长都取为1。将该灰度共生矩阵参数方案应用于渤海湾盆地部分浅层河道储层的地震纹理计算,钻井证实其河道纹理形态识别的正确性。
Channel texture is an acoustic expression of a fluvial facies via seismic amplitude fluctuations.The Gray Level Co-occurrence Matrix(GLCM) attribute has been proved to be a promising method for seismic texture analysis.As we try to extract seismic texture attributes,however,it is a big uncertainty how to select the optimal GLCM parameters which will impact the final estimated seismic texture results and also affect the computing time.In this paper,we study the relationship between GLCM parameters and final seismic texture results to simplify the computation of GLCM.We build an ideal synthetic channel reservoir model which is derived from a modern meandering river.Then we simulate a noise-free post-stack seismic data using 3D Gaussian beam approach.With the synthetic channel model data,we will show how to select the four key GLCM parameters including the gray levels,the size of moving window,and the distance and direction of gray pairs.Selecting various combinations of these four key parameters,we extract four GLCM secondary statistical measurements(Energy,Entropy,Contrast,and Homogeneity).Based on theoretical equations and horizontal slices of texture,we ultimately get a proper co-occurrence matrix parameter for fluvial reservoir from our synthetic channel model.For energy and entropy,the number of gray levels is lower.For contrast and homogeneity,the number of gray levels is higher.The size of moving window is smaller than the half of the size of geological target.The distance of gray pairs is usually 1.And we usually represent repetitive patterns of gray pairs at angles of 0°,45°,90° and 135° to the axes.At last,we apply our method on the field data from Bohai Bay,China.This real seismic example shows that GLCM is an effective method for accurate and reliable channel texture measurements.
Channel texture is an acoustic expression of a fluvial facies via seismic amplitude fluctuations.The Gray Level Co-occurrence Matrix(GLCM) attribute has been proved to be a promising method for seismic texture analysis.As we try to extract seismic texture attributes,however,it is a big uncertainty how to select the optimal GLCM parameters which will impact the final estimated seismic texture results and also affect the computing time.In this paper,we study the relationship between GLCM parameters and final seismic texture results to simplify the computation of GLCM.We build an ideal synthetic channel reservoir model which is derived from a modern meandering river.Then we simulate a noise-free post-stack seismic data using 3D Gaussian beam approach.With the synthetic channel model data,we will show how to select the four key GLCM parameters including the gray levels,the size of moving window,and the distance and direction of gray pairs.Selecting various combinations of these four key parameters,we extract four GLCM secondary statistical measurements(Energy,Entropy,Contrast,and Homogeneity).Based on theoretical equations and horizontal slices of texture,we ultimately get a proper co-occurrence matrix parameter for fluvial reservoir from our synthetic channel model.For energy and entropy,the number of gray levels is lower.For contrast and homogeneity,the number of gray levels is higher.The size of moving window is smaller than the half of the size of geological target.The distance of gray pairs is usually 1.And we usually represent repetitive patterns of gray pairs at angles of 0°,45°,90° and 135° to the axes.At last,we apply our method on the field data from Bohai Bay,China.This real seismic example shows that GLCM is an effective method for accurate and reliable channel texture measurements.
引文
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[2]Love P L,Simaan M.Segmentation of stacked seis-mic data by the classification of image texture.SEGTechnical Program Expanded Abstracts,1984,3:480～482
[3]Gao D.The first-order and the second-order seismictextures.AAPG Abstracts with Programs,1999,8:A45
[4]Gao D.3DVCM seismic textures:A new technologyto quantify seismic interpretation.SEG TechnicalProgram Expanded Abstracts,1999,18:1037～1039
[5]Gao D.Volume texture extraction for 3Dseismic vi-sualization and interpretation.Geophysics,2003,68(4):1294～1302
[6]West B P,May S R,Eastwood J E et al.Interactiveseismic facies classification using textural attributesand neural networks.The Leading Edge,2002,21(10):1042～1049
[7]Angelo M S,Matos M C,Marfurt K J.Integratedseismic texture segmentation and clustering analysisto delineate reservoir heterogeneity.SEG TechnicalProgram Expanded Abstracts,2009,28:1107～1111
[8]Yenugu M,Marfurt K J,Matson S.Seismic textureanalysis for reservoir prediction and characterization.The Leading Edge,2010,29(9):1116～1121
[9]Haralick R M,Shanmugam K,Dinstein I.Texturalfeatures for image classification.IEEE Transactionson Systems,Man,and Cybernetics,1973,3(6):610～621
[10]薄华,马缚龙,焦李成.图像纹理的灰度共生矩阵计算问题的分析.电子学报,2006,34(1):155～158,134Bo Hua,Ma Fulong,Jiao Licheng.Research on com-putation of GLCM of image texture.Acta ElectronicaSinica,2006,34(1):155～158,134
[11]王伟.地震几何属性识别断层技术研究及应用[硕士学位论文].山东东营:中国石油大学(华东),2009
[12]崔世凌,张军华,王伟等.地震纹理属性在JJD工区断层识别中的应用.物探化探计算技术,2010,32(3):304～309Cui Shiling,Zhang Junhua,Wang Wei et al.The ex-traction of seismic texture attribute and its applicationin fault identification.Computing Techniques for Geo-physical and Geochemical Exploration,2010,32(3):304～309
[13]Chopra S,Alexeev V.Texture analysis aids interpre-tation.Hart’s E and P,2005,12(11):111～113
[14]Chopra S,Alexeev V.Applications of texture attrib-ute analysis to 3Dseismic data.The Leading Edge,2006,25(8):934～940
[15]Miall A D.Analysis of Fluvial Depositional Sys-tems.Tulsa:American Association of Petroleum Ge-ologists,1982
[16]Di B,Xu X,Wei J.A seismic modeling analysis ofwide and narrow 3Dobservation systems for channelsand bodies.Applied Geophysics,2008,5(3):294～300
[17]Schumm S A.The Fluvial System.New York:Wi-ley-Interscience,1977
[18]Wood L J.Quantitative seismic geomorphology ofPliocene and Miocene fluvial systems in the northernGulf of Mexico,USA.Journal of Sedimentary Re-search,2007,77(9):713～730
[19]Cerveny V,Popov M M,Psencik I.Computation ofwave fields in inhomogeneous media:Gaussian beamapproach.Geophysical Journal of the Royal Astro-nomical Society,1982,70(1):109～128
[20]邓飞,刘超颖.三维射线快速追踪及高斯射线束正演.石油地球物理勘探,2009,44(2):158～165Deng Fei,Liu Chao-ying.3-D rapid ray-tracing andGaussian ray-beam forward simulation.OGP,2009,44(2):158～165
[21]朱伟林,王国纯.渤海浅层油气成藏条件分析.中国海上油气(地质),2000,14(6):2～9Zhu Weilin,Wang Guochun.An analysis of condi-tions for shallow hydrocarbon accumulation in BohaiSea.China Offshore Oil and Gas(Geology),2000,14(6):2～9
[22]Gao D.Application of three-dimensional seismic tex-ture analysis with special reference to deep-marine fa-cies discrimination and interpretation:Offshore An-gola,West Africa.AAPG Bulletin,2007,91(12):1665～1683
[23]Wang Zhiguo,Yin Cheng,Ding Feng.MultiattributeRGBA color blending of principal components.CPS/SEG Beijing International Geophysical ConferenceExpanded Abstracts,2009
[2]Love P L,Simaan M.Segmentation of stacked seis-mic data by the classification of image texture.SEGTechnical Program Expanded Abstracts,1984,3:480～482
[3]Gao D.The first-order and the second-order seismictextures.AAPG Abstracts with Programs,1999,8:A45
[4]Gao D.3DVCM seismic textures:A new technologyto quantify seismic interpretation.SEG TechnicalProgram Expanded Abstracts,1999,18:1037～1039
[5]Gao D.Volume texture extraction for 3Dseismic vi-sualization and interpretation.Geophysics,2003,68(4):1294～1302
[6]West B P,May S R,Eastwood J E et al.Interactiveseismic facies classification using textural attributesand neural networks.The Leading Edge,2002,21(10):1042～1049
[7]Angelo M S,Matos M C,Marfurt K J.Integratedseismic texture segmentation and clustering analysisto delineate reservoir heterogeneity.SEG TechnicalProgram Expanded Abstracts,2009,28:1107～1111
[8]Yenugu M,Marfurt K J,Matson S.Seismic textureanalysis for reservoir prediction and characterization.The Leading Edge,2010,29(9):1116～1121
[9]Haralick R M,Shanmugam K,Dinstein I.Texturalfeatures for image classification.IEEE Transactionson Systems,Man,and Cybernetics,1973,3(6):610～621
[10]薄华,马缚龙,焦李成.图像纹理的灰度共生矩阵计算问题的分析.电子学报,2006,34(1):155～158,134Bo Hua,Ma Fulong,Jiao Licheng.Research on com-putation of GLCM of image texture.Acta ElectronicaSinica,2006,34(1):155～158,134
[11]王伟.地震几何属性识别断层技术研究及应用[硕士学位论文].山东东营:中国石油大学(华东),2009
[12]崔世凌,张军华,王伟等.地震纹理属性在JJD工区断层识别中的应用.物探化探计算技术,2010,32(3):304～309Cui Shiling,Zhang Junhua,Wang Wei et al.The ex-traction of seismic texture attribute and its applicationin fault identification.Computing Techniques for Geo-physical and Geochemical Exploration,2010,32(3):304～309
[13]Chopra S,Alexeev V.Texture analysis aids interpre-tation.Hart’s E and P,2005,12(11):111～113
[14]Chopra S,Alexeev V.Applications of texture attrib-ute analysis to 3Dseismic data.The Leading Edge,2006,25(8):934～940
[15]Miall A D.Analysis of Fluvial Depositional Sys-tems.Tulsa:American Association of Petroleum Ge-ologists,1982
[16]Di B,Xu X,Wei J.A seismic modeling analysis ofwide and narrow 3Dobservation systems for channelsand bodies.Applied Geophysics,2008,5(3):294～300
[17]Schumm S A.The Fluvial System.New York:Wi-ley-Interscience,1977
[18]Wood L J.Quantitative seismic geomorphology ofPliocene and Miocene fluvial systems in the northernGulf of Mexico,USA.Journal of Sedimentary Re-search,2007,77(9):713～730
[19]Cerveny V,Popov M M,Psencik I.Computation ofwave fields in inhomogeneous media:Gaussian beamapproach.Geophysical Journal of the Royal Astro-nomical Society,1982,70(1):109～128
[20]邓飞,刘超颖.三维射线快速追踪及高斯射线束正演.石油地球物理勘探,2009,44(2):158～165Deng Fei,Liu Chao-ying.3-D rapid ray-tracing andGaussian ray-beam forward simulation.OGP,2009,44(2):158～165
[21]朱伟林,王国纯.渤海浅层油气成藏条件分析.中国海上油气(地质),2000,14(6):2～9Zhu Weilin,Wang Guochun.An analysis of condi-tions for shallow hydrocarbon accumulation in BohaiSea.China Offshore Oil and Gas(Geology),2000,14(6):2～9
[22]Gao D.Application of three-dimensional seismic tex-ture analysis with special reference to deep-marine fa-cies discrimination and interpretation:Offshore An-gola,West Africa.AAPG Bulletin,2007,91(12):1665～1683
[23]Wang Zhiguo,Yin Cheng,Ding Feng.MultiattributeRGBA color blending of principal components.CPS/SEG Beijing International Geophysical ConferenceExpanded Abstracts,2009
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