地震纹理属性在JJD工区断层识别中的应用

英文篇名：THE EXTRACTION OF SEISMIC TEXTURE ATTRIBUTE AND ITS APPLICATION IN FAULT IDENTIFICATION
中文刊名：物探化探计算技术
英文刊名：Computing Techniques for Geophysical and Geochemical Exploration
作者：崔世凌 ; 张军华 ; 王伟 ; 谭明友 ; 陈海云
英文作者：CUI Shi-ling1 ; 2 ; ZHANG Jun-hua3 ; WANG Wei4 ; et al.(1.Guangzhou Institute of Geochemistry ; Chinese Academy Sciences ; Guangzhou 510640 ; China ; 2.Geophysical Prospecting Research Institute of Shengli Oilfield ; Dongying 257022 ; China ; 3.College of Geo-Resources and Information ; China Petroleum University ; Dongying 257061 ; China ; 4.Research Institute of BGP ; Zhuozhou 072751 ; China)
中文关键词：纹理 ; 体素 ; 灰度共生矩阵 ; RGB技术 ; 断层
英文关键词：texture ; voxel ; gray level co-occurrence matrix ; RGB technology ; faults
出版日期：2010-05-15
机构：中国科学院广州地球化学研究所;中国石化胜利油田物探研究院;中国石油大学资源信息学院;东方地球物理公司研究院;
年：2010
期：03
出版单位：物探化探计算技术

摘要

纹理分析是图像处理中的一种常用技术,通过构建地震纹理基元和灰度共生矩阵,可以将此项技术推广到地球物理领域,并可在断层识别,边缘检测和沉积相划分等方面得到应用。这里通过算法研究和程序开发,结合JJD工区应用实例,得到了有一定理论意义和研究价值的结论:①基于灰度共生矩阵提取的纹理属性,是一种很好的凸显断层和裂缝信息的地震属性;②可以根据实际地质问题,提取不同方向的纹理属性,并用RGB技术进行多属性的融合;③地震纹理基元的窗大小取9×9×9为好;④要根据具体情况选取合理的灰度级别,对于常规三维地震数据,灰度级别取16或32比较理想。
Texture analysis is a common technology in image processing,which can be extended to the field of geophysical prospecting by constructing seismic texture primitive and gray level co-occurrence matrix.It can be used in fault identification,edge detection and sedimentary facies delineation.Through the algorithm research,programming and practical application,we get some conclusions which has theoretical meaning and valuable ①The texture attribute which based on gray level co-occurrence matrix is a good attribute in highlighting the information of faults and fractures,② According to actual geological problems,we can extract texture attributes of different directions,and use RGB technology for the integration of multi-attributes,③ The window of seismic texture element we should adopt is 9×9×9,④ We should select a reasonable level of gray of different conditions,and commonly selection is 16 or 32 for conventional three-dimensional seismic data.

引文

[1]刘晓民.纹理研究及其应用综述[J].测控技术.2008.27(5):4.
    [2]杨淑莹,胡军,曹作良.基于图像纹理分析的目标物体识别方法[J].天津理工学院学报,2001,17(4):31.
    [3]许存禄.图像纹理分析的新方法及其应用[M].上海:复旦大学,2005.
    [4]宋端智,柴振友,张爱敏.用虚拟现实建模语言实现地震层位三维可视化[J].物探化探计算技术,2000,22(3):299.
    [5]郭科,胥泽银,倪根生.用主曲率法研究裂缝性油气藏[J].物探化探计算技术,1998,20(4):335.
    [6]DENGLIANG GAO.Volume texture extraction for3D seismic visualization and interpretation[J].Geophysics.2003,68(4):1294.
    [7]DENGLIANG GAO.Texture model regression for effec-tive feature discrimination:Application to seismic facies visualization and interpretation[J].Geophysics,2004,69(4):958.
    [8]BAHORICH M,FARMER S.3-D Seismic coherency for faults and stratigraphic features[J].The Leading Edge,1995,14(10):1053.
    [9]MARFURT K J,KIRLIN R L,STEVEN S L.3-D seismic attributes using a semblance-based coherency algorithm[J].Geophysics,1998,63(4):1150.
    [10]GERSZTENKOMn A,MARFURT K J.Eigenstructure based coherence computations as an aid to3D structural and stratigraphic mapping[J].Geophysics,1999,64(5):1468.
    [11]DENGLIANG GAO.Structure-oriented texture model re-gression:Application to seismic structure visualizationand interpretation[J].SEG Expanded Abstracts,2006,25:1083.
    [12]DENGLIANG GAO.Application of seismic texture model regression to seismic facies characterization and inter-pretation[J].The Leading Edge,2008,27:394.
    [13]DENGLIANG GAO.3D seismic volume visualization and interpretation:An integrated workflow with case studies[J].Geophysics,2009,74(1):W1.
    [14]白雪冰,王克奇,王辉.基于灰度共生矩阵的木材纹理分类方法的研究[J].哈尔滨工业大学学报,2005,37(12):1667.
    [15]汪黎明,陈健敏,王锐,等.织物褶皱纹理灰度共生矩阵分析[J].青岛大学学报,2003,18(4):5.