吉林大学学报(地球科学版) ›› 2017, Vol. 47 ›› Issue (4): 1286-1294.doi: 10.13278/j.cnki.jjuese.201704304

• 地球探测与信息技术 • 上一篇    下一篇

基于Facet模型梯度算子一致性的地震数据不连续性识别方法

刘海燕1,2, 刘财1,2, 王典1,2, 刘洋1,2   

  1. 1. 吉林大学地球探测科学与技术学院, 长春 130026;
    2. 国土资源部应用地球物理重点实验室, 长春 130026
  • 收稿日期:2016-11-12 出版日期:2017-07-26 发布日期:2017-07-26
  • 通讯作者: 王典(1978一),女,副教授,主要从事地震数据处理方法研究工作,E-mail:dianwang@jlu.edu.cn E-mail:dianwang@jlu.edu.cn
  • 作者简介:刘海燕(1986),女,博士研究生,主要从事地震数据处理方法研究工作,E-mail:lhy509516@163.com
  • 基金资助:
    国家自然科学基金项目(41430322,41522404);国家重点基础研究发展计划("973"计划)项目(2013CB429805)

Seismic Data Discontinuity Identification Using Coherence Based on Facet Model Gradient Operator

Liu Haiyan1,2, Liu Cai1,2, Wang Dian1,2, Liu Yang1,2   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Key Laboratory of Applied Geophysics, Ministry of Land and Resources, Changchun 130026, China
  • Received:2016-11-12 Online:2017-07-26 Published:2017-07-26
  • Supported by:
    Supported by National Natural Science Foundation of China (41430322, 41522404) and State Key Development Program for Basic Research of China (2013CB429805)

摘要: 存在断层、角度不整合面等不连续结构的地质体的自动识别在地震构造解释中具有重要的意义,这些地质特征的地震响应为同相轴不连续。常规的地震数据不连续性识别方法应用范围有限,参数设置依赖于人为经验,易导致识别结果辨识度差。本文将一致性作为新的不连续性识别方法引入到地震数据处理中。首先利用定位精度高、易于扩展的Facet模型梯度算子计算一致性,其次对一致性数据作阈值化处理,最后利用数学形态学中的腐蚀、膨胀及细化算法作进一步处理,实现了对地震数据不连续性信息的自动识别。经过理论和实际资料测试,并与C3相干算法和方差算法对比分析,证实了本文所提方法在地震数据不连续性识别方面具有更高的稳定性和辨识度,可以作为地层不连续性识别的有力工具。

关键词: 一致性, Facet模型梯度算子, 不连续性识别, 地震数据

Abstract: Automatic identification of discontinuous geological bodies such as faults and angle unconformity is of significance in seismic structural interpretation, which in the seismic profile appears as the discontinuity of reflection events. The application scope of the conventional seismic data discontinuity identification method is limited due to the fact that its parameter setting relies on human experiences, which could easily results in an improper identification. Therefore, in this paper, coherence is introduced into seismic data processing as a new discontinuity identification parameter. Firstly, the coherence was calculated by the Facet model gradient operator, which is high positioning accurate and easy to be expanded. Secondly, we applied a threshold on the coherence data. Finally, the corrosion, expansion and thinning algorithm in mathematical morphology were used for further processing to realize the automatic identification of the seismic data discontinuity information. Through the synthetic and field seismic data tests, and the comparison with C3 coherent algorithms, as well as variance algorithm, we can demonstrate that the proposed method can be used as a powerful tool for the discontinuity identification in formations, with a higher stability and identification ability in seismic data discontinuity lineation.

Key words: coherence, Facet modelgradient operator, discontinuity identification, seismic data

中图分类号: 

  • P631.4
[1] 冯智慧,张文春,李向群,等. 高精度分频相干加强技术在微小断层识别中的应用[J].吉林大学学报(地球科学版),2016,46(5):1571-1579. Feng Zhihui,Zhang Wenchun,Li Xiangqun,et al. Application of High-Precision Frequency Division Coherency Enhancement Technique in Micro-Fault Identification[J]. Journal of Jilin University (Earth Science Edition),2016,46 (5):1571-1579.
[2] Bahorich M,Farmer S. 3-D Seismic Discontinuity for Faults and Stratigraphic Features:The Coherence Cube[J]. The Leading Edge,1995,14(10):1053-1058.
[3] Marfurt K J,Kirlin R L,Farmer S L,et al. 3-D Seismic Attributes Using a Semblance-Based Coherency Algorithm[J]. Geophysics,1998,63(4):1150-1165.
[4] Gersztenkorn A,Marfurt K J. Eigenstructure-Based Coherence Computations as an Aid to 3-D Structural and Stratigraphic Mapping[J]. Geophysics,1999,64(5):1468-1479.
[5] Van B P P,Pepper R E F. Seismic Signal Processing Method and Apparatus for Generating a Cube of Variance Values:United States,WOUS0005694 [P]. 2000-09-14.
[6] Randen T,Monsen E,Signer C,et al. Three-Dimensional Texture Attributes for Seismic Data Analysis[C]//Expanded Abstracts of the 70th Annual International SEG Meeting.Calgary:SEG,2000:668-671.
[7] 刘洋,王典,刘财,等.基于非平稳相似性系数的构造导向滤波及断层检测方法[J]. 地球物理学报,2014,57(4):1177-1187. Liu Yang,Wang Dian,Liu Cai,et al. Structure-Oriented Filtering and Fault Detection Based on Nonstationary Similarity[J]. Chinese Journal of Geophysics,2014,57(4):1177-1187.
[8] Kass M,Witkin A. Analyzing Orientated Pattern[J]. Computer Vision,Graphics and Image Processing,1987,37(3):362-385.
[9] Tian J,Yu W Y,Xie S L. An Ant Colony Optimization Algorithm for Image Edge Detection [C]//IEEE Congress on Evolutionary Computation.Hong Kong:IEEE,2008:751-756.
[10] Haralick,Robert M. Digital Step Edges from Zero Crossing of Second Directional Derivatives[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1984,PAMI-6 (1):58-68.
[11] 卢瑞涛,黄新生,徐婉莹.基于Contourlet变换和Facet模型的红外小目标检测方法[J]. 红外与激光工程,2013,42(8):2281-2287. Lu Ruitao,Huang Xinsheng,Xu Wanying. Method of Infrared Small Target Detection Based on Contourlet Transform and Facet Model[J]. Infrared and Laser Engineering,2013,42(8):2281-2287.
[12] 孙永壮.异常地质体地震边缘检测技术研究[D]. 青岛:中国石油大学(华东),2012. Sun Yongzhuang. The Research of Abnormal Geological Body Identification Based on Seismic Edge Detection[D]. Qingdao:China University of Petroleum (East China),2012.
[13] 姜杭毅,蔡元龙.采用正交多项式曲面拟合法的边缘检测[J]. 自动化学报,1990,16(3):202-210. Jiang Hangyi,Cai Yuanlong. Edge Detection from Surface Fitting by Orthogonal Polynomial[J]. Acta Automatica Sinica,1990,16(3):202-210.
[14] Claerbout J F. Basic Earth Imaging[Z]. Stanfod Exploration Project,2010,http://sepwww.stanford. edu/sep/prof/bei11.2010.pdf.
[15] 刘海燕.C3相干算法的改进及其在断层识别中的应用[D]. 长春:吉林大学,2013. Liu Haiyan. The Improvement of C3 Coherence Algorithm and the Application in Fault Identification [D]. Changchun:Jilin University,2013.
[16] Claerbout J F,Fomel S. Image Estimation by Example:Geophysical Soundings Image Construction[Z]. Stanford Exploration Project,2012,http://sepwww.stanford.edu/sep/prof/gee1-2012.pdf.
[17] Liu C,Chen C L,Wang D,et al. Seismic Dip Estimation Based on the Two-Dimensional Hilbert Transform and Its Application in Random Noise Attenuation[J]. Applied Geophysics,2015,12 (1):55-63.
[18] Liu Y,Fomel S,Liu G C.Nonlinear Structure-Enhancing Filtering Using Plane-Wave Predication[J]. Geophysical Prospecting,2010,58(3):415-427.
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