Abstract:Fault interpretation is crucial in reservoir prediction and geological modeling. Currently, fault interpretation is mostly conducted manually, with a large workload and low efficiency, which fails to meet the precise requirements of oilfield exploration and development. Therefore, based on the analysis and optimization of the traditional coherent attributes or intelligent fault prediction data volumes, this paper proposes an automatic fault extraction method based on α-shape and polygon offset. Firstly, it determines the location of the target fault through human-computer interaction. Secondly, it develops an α-shape breakpoint edge extraction algorithm and an inclination constrained polygon offset algorithm to accurately depict the spatial boundary of faults. Finally, by using the spatial boundary as a constraint condition and setting a target fault coincidence threshold, the extension range of the region growth algorithm is constrained to complete the automatic extraction of 3D faults. The application of the proposed method has achieved great results in many areas of Shengli Oilfield. The spatial distribution pattern of faults is depicted in Zheng 6 area, and the fault integrity and accuracy are significantly better than a certain commercial software. The automatic extraction of faults has greatly improved work efficiency in Xin 50 area.
BAHORICH M,FARMER S.3-D seismic disconti-nuity for faults and stratigraphic features: the coherence cube[J].The Leading Edge,1995,14(10): 1053-1058.
[2]
MARFURT K J,KIRLIN L R,FARMER S L,et al. 3-D seismic attributes using a semblance-based coherency algorithm[J].Geophysics,1998,63(4): 1150-1165.
[3]
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.
[4]
COHEN I,COIFMAN R R.Local discontinuity measures for 3-D seismic data[J].Geophysics,2002,67(6): 1933-1945.
[5]
王西文,苏明军,刘军迎,等.基于小波变换的地震相干体算法及其应用[J].石油物探,2002,41(3): 334-338.WANG Xiwen,SU Mingjun,LIU Junying,et al.Computation of seismic coherence cube based on wavelet transform and its application[J].Geophysical Prospecting for Petroleum,2002,41(3): 334-338.
[6]
宋建国,王海昆,穆星.基于DOA的相干算法研究与应用[J].地球物理学进展,2010,25(5): 1662-1669.SONG Jianguo,WANG Haikun,MU Xing.Research and implementation of cohere algorithm based on DOA[J].Progress in Geophysics,2010,25(5): 1662-1669.
[7]
LU W,LI Y,ZHANG S,et al.Higher-order-statistics and supertrace-based coherence-estimation algorithm[J].Geophysics,2005,70(3): 13-18.
[8]
段春节,吴汉宁,马承杰,等.基于高阶统计量的相干体算法在地震中深层构造解释中应用[J].地球物理学进展,2009,24(2): 640-643.DUAN Chunjie,WU Hanning,MA Chengjie,et al.The application of higher-order statistics coherency algorithm in seismic data interpretation[J].Progress in Geophysics,2009,24(2): 640-643.
[9]
马瑾环,陈国俊,吴志高,等.改进的第三代相干算法及应用[J].勘探地球物理进展,2007,30(4):286-291.MA Jinhuan,CHEN Guojun,WU Zhigao,et al.Modified coherency cube of the third generation and its applications[J].Progress in Exploration Geophysics,2007,30(4):286-291.
[10]
崔正伟,程冰洁,徐天吉,等.基于构造导向滤波与梯度结构张量相干属性的储层裂缝预测方法及应用[J].石油地球物理勘探,2021,56(3): 555-563.CUI Zhengwei,CHENG Bingjie,XU Tianji,et al.Reservoir fracture prediction method and application based on structure-oriented filtering and coherent attributes of gradient structure tensor[J].Oil Geophysical Prospecting,2021,56(3): 555-563.
[11]
WU X,LIANG L,SHI Y,et al.FaultSeg3D: using synthetic data sets to train an end-to-end convolutional neural network for 3D seismic fault segmentation[J].Geophysics,2019,84(3): IM35-IM45.
[12]
蔡宇飞.三维地震断层智能识别与重建[D].四川成都: 电子科技大学,2020.
[13]
张政,严哲,顾汉明.基于残差网络与迁移学习的断层自动识别[J].石油地球物理勘探,2020,55(5): 950-956.ZHANG Zheng,YAN Zhe,GU Hanming.Automatic fault recognition with residual network and transfer learning[J].Oil Geophysical Prospecting,2020,55(5): 950-956.
[14]
路鹏飞,杜文龙,李丽,等.基于VNet深度学习架构的低序级断层智能识别方法[J].石油地球物理勘探,2022,57(6): 1276-1286.LU Pengfei,DU Wenlong,LI Li,et al.Intelligent recognition method of low-grade faults based on VNet deep learning architecture[J].Oil Geophysical Prospecting,2022,57(6): 1276-1286.
[15]
陈俊安,陈海东,龚伟,等.深度学习与边缘增强相结合的断裂综合检测技术——顺北地区超深走滑断裂检测应用实例[J].石油地球物理勘探,2022,57(6): 1304-1316.CHEN Junan,CHEN Haidong,GONG Wei,et al.Application of comprehensive fault detection technology combining deep learning with edge enhancement in detecting ultra-deep strike-slip faults in Shunbei block[J].Oil Geophysical Prospecting,2022,57(6): 1304-1316.
[16]
刘乃豪,李时桢,黄腾,等.改进的整体嵌套边缘检测地震断层识别技术[J].石油地球物理勘探,2022,57(3): 499-509.LIU Naihao,LI Shizhen,HUANG Teng,et al.Seismic fault interpretation based on improved holistically-nested edge detection[J].Oil Geophysical Prospecting,2022,57(3): 499-509.
[17]
严哲.三维地震断层自动识别与智能解释[D].湖北武汉: 中国地质大学(武汉),2010.
[18]
张进超.基于地震数据的三维断层的自动识别[D].陕西西安: 西安科技大学,2014..
[19]
陈雷,肖创柏,禹晶,等.基于相似性传播聚类与主成分分析的断层识别方法[J].石油地球物理勘探,2017,52(4): 826-833.CHEN Lei,XIAO Chuangbai,YU Jing,et al.Fault recognition based on affinity propagation clustering and principal component analysis[J].Oil Geophysical Prospecting,2017,52(4): 826-833.
[20]
EDELSBRUNNER H,KIRKPATRICK D,SEIDEL R.On the shape of a set of points in the plane[J].IEEE Transactions on Information Theory,1983,29(4): 551-559.
[21]
CHEN X,MCMAINS S.Polygon offsetting by computing winding numbers[C].ASME 2005 Interna-tional Design Engineering Technical Conferences and Computers and Information in Engineering Confe-rence,Long Beach,California,USA,2005,565-575.