IGGCAS OpenIR  > 油气资源研究院重点实验室
Automatic Fresnel zone picking in the dip-angle domain using deep neural networks
Sun, Hui1,2,3; Zhang, Hao1,2,4; Song, Mingpeng1,2,3; Li, Shengrong1,2,3; Lu, Yongming5
2019-02-01
Source PublicationJOURNAL OF GEOPHYSICS AND ENGINEERING
ISSN1742-2132
Volume16Issue:1Pages:136-145
AbstractAlthough successful applications of deep neural networks (DNNs) have been shown in many research fields, their application to Fresnel zone picking for Kirchhoff-type migration has not been explored. We investigate the application of DNNs for identifying the left and right boundaries of the Fresnel zone in the dip-angle domain automatically, which leads to an optimal summation for imaging. We use a pair of 1D dip-angle gathers in both inline and crossline directions as the input data to train the DNNs in a supervised way. The goal is to minimize the cost as a function of weights and biases. The trained DNNs can be utilized to automatically extract a set of marks regarding different dip-angle values from a large number of sub-images in dip-angle gathers. Through experiment, we show that a four-layer DNN is enough to extract the features of our training data and meanwhile avoid overfitting in estimating the Fresnel zone range. Finally, we adopt two field data examples, Dashen and Xudong oil field in China, to demonstrate the effectiveness and the generalization ability of the DNNs-based Fresnel zone picking on dip-angle gathers. The results illustrate that the proposed DNN is an efficient automatic data-driven picker needing little human participation.
KeywordFresnel zone picking deep neural networks (DNNs) seismic data high resolution imaging
DOI10.1093/jge/gxy012
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation
WOS KeywordMIGRATION ; RESOLUTION
Language英语
Funding ProjectNational Natural Science Foundation of China[41804129] ; China Postdoctoral Science Foundation[2018T110137]
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; China Postdoctoral Science Foundation
WOS Research AreaGeochemistry & Geophysics
WOS SubjectGeochemistry & Geophysics
WOS IDWOS:000466715700012
PublisherOXFORD UNIV PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/91484
Collection油气资源研究院重点实验室
Corresponding AuthorZhang, Hao
Affiliation1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resources Res, Beijing 100029, Peoples R China
2.Chinese Acad Sci, Inst Earth Sci, Beijing 100029, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Geol Sci, Inst Geomech, Beijing 100081, Peoples R China
5.Southern Univ Sci & Technol, Dept Earth & Space Sci, Shenzhen 518055, Peoples R China
Recommended Citation
GB/T 7714
Sun, Hui,Zhang, Hao,Song, Mingpeng,et al. Automatic Fresnel zone picking in the dip-angle domain using deep neural networks[J]. JOURNAL OF GEOPHYSICS AND ENGINEERING,2019,16(1):136-145.
APA Sun, Hui,Zhang, Hao,Song, Mingpeng,Li, Shengrong,&Lu, Yongming.(2019).Automatic Fresnel zone picking in the dip-angle domain using deep neural networks.JOURNAL OF GEOPHYSICS AND ENGINEERING,16(1),136-145.
MLA Sun, Hui,et al."Automatic Fresnel zone picking in the dip-angle domain using deep neural networks".JOURNAL OF GEOPHYSICS AND ENGINEERING 16.1(2019):136-145.
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