LI Hongwei, BAI Xuelian, CUI Jingbin, WAN Zhonghong, YUAN Shihong, CHU Wanchang. Fault identification technology of ant attribute optimization[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(6): 174-179. DOI: 10.3969/j.issn.1001-1986.2019.06.026
Citation: LI Hongwei, BAI Xuelian, CUI Jingbin, WAN Zhonghong, YUAN Shihong, CHU Wanchang. Fault identification technology of ant attribute optimization[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(6): 174-179. DOI: 10.3969/j.issn.1001-1986.2019.06.026

Fault identification technology of ant attribute optimization

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National Science and Technology Major Project(2017ZX05018-001)

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  • Received Date: March 10, 2019
  • Published Date: December 24, 2019
  • In the field of seismic geological exploration, the ant attributes is more and more widely used for rapid identification of fault system, and in the process of practical application, ant attributes based on 3D seismic data extraction are displayed either along strata slice(plan) or in section, the features of fault system and distribution characteristics of seismic events is not corresponding to the actual situation, the application effect is poorer, fault interpretation work is given priority to with manual interpretation backbone profile, unable to realize fault automatic tracking. In view of this widespread situation, this paper studies and analyzes the actual data and finds that simply extracting the attribute of ant body for fault interpretation cannot ensure the accuracy of fault identification. Therefore, a set of techniques for rapid fault identification of ant body was developed. First of all, according to the geological target optimization of ant attribute of termination criteria, application of the thin ant body of binarization technology makes the ant pheromone focus and converge, and then the fault surface and angle were analyzed by automatic fault separation, the rule of fault surface and the relationship between fault surfaces were effectively generated and defined, the final use of 3D visualization plane-solid simultaneous interpretation technology determined directly the rationality of the spatial distribution of fault system in the study area, sections were carefully edited and adjusted refiningly, fault edge was extracted automatically according to the needed intervals, so as to realize the automatic tracking of fault interpretation. Through the application of this series of techniques, good results have been achieved in the identification of fault systems in the study area, especially in the rapid automatic tracking of large-scale faults, and the framework for fault interpretation in the study area has been quickly and accurately established. The application of ant attributes to fault identification is a series of techniques. It is the key to test and optimize the calculation parameters using typical profiles. In order to obtain effective fault recognition results, the ant attributes in the whole area were calculated in accordance with this idea.
  • [1]
    DORIGO M,MANIEZZO V,COLORNI A. Positive feedback as a search strategy[R]. Milan:Milan Politecnico di Milano,1991:91-106.
    [2]
    DORIGO M,MANIEZZO V,COLORNI A. Ant System:optimization by a colony of cooperating agents[J]. IEEE Trans Syst Man Cybern B Cybern,1996,26(1):29-41.
    [3]
    PARMEE I C,VEKERIA H,BILCHEV G. Role of evo-lutionary and adaptive search during whole system,constrained and detailed design optimization[J]. Engineering Optimization,1997,29(1/2/3/4):151-176.
    [4]
    GAMBARDELLA L M,DORIGO M. Ant-Q:A rein-forcement learning approach to the traveling salesman prob-lem[C]//Proceedings of the Twelfth International Conference on Machine Learning. Palo Alto,California:Margan Kaufmann Publishers,1995:252-260.
    [5]
    STUTZLE T,HOOS H. MAX-MIN ant system and local search for the traveling salesman problem[C]//Proceedings of 1997 IEEE International Conference on Evolutionary Computation. New York:IEEE Press,1997:309-314.
    [6]
    BULLNHEIMER B,HARTL R F,STRAUSS C. A new rank based version of the ant system:A computational study[J]. Central European Journal for Operations Research and Economics,1999,7(1):25-38.
    [7]
    MIDDENDORF,MARTIN. Multi colony ant algorithms[J]. Journal of Heuristics,2002(5):305-320.
    [8]
    PEDERSEN S I,SKOV T. Automatic fault extraction using artificial ants[J]. SEG Technical Program Expanded Abstracts,2002,21:512-515.
    [9]
    SUN D S,LING Y. Application of spectral decomposition and ant tracking to fractured carbonate reservoirs[J]. EAGE Extended Abstacts,2011,B035:23-26.
    [10]
    AQRAWI A. Improved fault segmentation using a dip guided and modified 3D Sobel filter[J]. SEG Technical Program Expanded Abstracts,2011,30:999-1003.
    [11]
    乐群星,魏法杰. 蚂蚁算法的基本原理及其研究发展现状[J].北京航空航天大学学报(社会科学版),2005,18(4):5-8.

    YUE Qunxing,WEI Fajie. New stochastic optimization algorithm-ant system[J]. Journal of Beijing University of Aeronautics and Astronautics(Social Sciences Edition),2005,18(4):5-8.
    [12]
    赵伟. 基于蚁群算法的三维地震断层识别方法研究[D]. 南京:南京理工大学,2009.
    [13]
    王军,李艳东,甘利灯. 基于蚂蚁体各向异性的裂缝表征方法[J]. 石油地球物理勘探,2013,48(5):763-769.

    WANG Jun,LI Yandong,GAN Lideng. Fracture characterization based on azimuthal anisotropy of ant-tracking attribute bodys[J]. Oil Geophysical Prospecting,2013,48(5):763-769.
    [14]
    张瑞,文晓涛,李世凯,等. 分频蚂蚁追踪在识别深层小断层中的应用[J]. 地球物理学进展,2017,32(1):350-356.

    ZHANG Rui,WEN Xiaotao,LI Shikai,et al. Application of frequency division ant-tracking in identifying deep minor fault[J]. Progress in Geophysics,2017,32(1):350-356.
    [15]
    史刘秀,王静波,张如伟,等. 复值相干模量蚂蚁体技术[J].断块油气田,2015,22(5):545-549.

    SHI Liuxiu,WANG Jingbo,ZHANG Ruwei,et al. Ant tracking technology based on multichannel local complex-valued coherence[J]. Fault Block Oil & Gas Field,2015,22(5):545-549.
    [16]
    陈志刚,吴瑞坤,孙星,等. 基于反射强度交流分量滤波的蚂蚁追踪断层识别技术改进及应用[J]. 地球物理学进展,2017,32(5):1973-1977.

    CHEN Zhigang,WU Ruikun,SUN Xing,et al. Improvement and application effect of ant-tracking fault identification technique based on reflection strength AC component filtering[J]. Progress in Geophysics,2017,32(5):1973-1977.
    [17]
    张亚春,尹太举,周文. 在蚂蚁属性体约束下的裂缝建模方法研究[J]. 长江大学学报(自然科学版),2016,13(14):16-21.

    ZHANG Yachun,YIN Taiju,ZHOU Wen. The fracture modeling in the constraint of ant tracking attribute[J]. Journal of Yangtze University(Natural Science Edition),2016,13(14):16-21.
    [18]
    严哲,顾汉明,蔡成国,等. 利用方向约束蚂蚁群算法识别断层[J]. 石油地球物理勘探,2011,46(4):614-620.

    YAN Zhe,GU Hanming,CAI Chengguo,et al. Fault identification by orientation constraint ant colony algorithm[J]. Oil Geophysical Prospecting,2011,46(4):614-620.
    [19]
    隆雨辰,李俊,王志章,等. 综合蚂蚁体及曲率属性的断裂识别方法及应用[J]. 油气藏评价与开发,2017,7(4):6-15.

    LONG Yuchen,LI Jun,WANG Zhizhang,et al. Fracture identification methods and applications of integrated ant body and curvature attribute[J]. Reservoir Evaluation and Development,2017,7(4):6-15.
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