中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地质与地球物理研究所
  3. 中国科学院地质与地球物理研究所
  4. 中国科学院油气资源研究重点实验室
A seismic fault recognition method based on ant colony optimization

文献类型：期刊论文

作者Chen, Lei1; Xiao, Chuangbai2; Li, Xueliang1; Wang, Zhenli1; Huo, Shoudong1
刊名JOURNAL OF APPLIED GEOPHYSICS
出版日期2018-05-01
卷号152页码:1-8
关键词Fault recognition Ant colony optimization Seismic section Horizon
ISSN号0926-9851
DOI10.1016/j.jappgeo.2018.02.009
文献子类Article
英文摘要Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results. (C) 2018 Elsevier B.V. All rights reserved.
WOS关键词ALGORITHM ; PATTERNS ; TRACKING
WOS研究方向Geology ; Mining & Mineral Processing
语种英语
WOS记录号WOS:000432501200001
出版者ELSEVIER SCIENCE BV
资助机构National Natural Science Foundation of China(41574134) ; National Natural Science Foundation of China(41574134) ; Beijing Natural Science Foundation(4162007) ; Beijing Natural Science Foundation(4162007) ; 100 Talents Program of the Chinese Academy of Science ; 100 Talents Program of the Chinese Academy of Science ; National Natural Science Foundation of China(41574134) ; National Natural Science Foundation of China(41574134) ; Beijing Natural Science Foundation(4162007) ; Beijing Natural Science Foundation(4162007) ; 100 Talents Program of the Chinese Academy of Science ; 100 Talents Program of the Chinese Academy of Science ; National Natural Science Foundation of China(41574134) ; National Natural Science Foundation of China(41574134) ; Beijing Natural Science Foundation(4162007) ; Beijing Natural Science Foundation(4162007) ; 100 Talents Program of the Chinese Academy of Science ; 100 Talents Program of the Chinese Academy of Science ; National Natural Science Foundation of China(41574134) ; National Natural Science Foundation of China(41574134) ; Beijing Natural Science Foundation(4162007) ; Beijing Natural Science Foundation(4162007) ; 100 Talents Program of the Chinese Academy of Science ; 100 Talents Program of the Chinese Academy of Science
源URL[http://ir.iggcas.ac.cn/handle/132A11/88260]  
专题地质与地球物理研究所_中国科学院油气资源研究重点实验室
通讯作者Huo, Shoudong
作者单位1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resources Res, Beijing 100029, Peoples R China
2.Beijing Univ Technol, Coll Comp Sci & Technol, Fac Informat Technol, Beijing 100724, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Lei,Xiao, Chuangbai,Li, Xueliang,et al. A seismic fault recognition method based on ant colony optimization[J]. JOURNAL OF APPLIED GEOPHYSICS,2018,152:1-8.
APA Chen, Lei,Xiao, Chuangbai,Li, Xueliang,Wang, Zhenli,&Huo, Shoudong.(2018).A seismic fault recognition method based on ant colony optimization.JOURNAL OF APPLIED GEOPHYSICS,152,1-8.
MLA Chen, Lei,et al."A seismic fault recognition method based on ant colony optimization".JOURNAL OF APPLIED GEOPHYSICS 152(2018):1-8.

入库方式： OAI收割

来源：地质与地球物理研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。