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Unsupervised FISTA-Net-Based Adaptive Subtraction for Seismic Multiple Removal

文献类型：期刊论文

作者Li, Zhongxiao2; Sun, Keyi2; Zeng, Tongsheng1; Ma, Jiahui2; Qi, Zhen2; Sun, Ningna2; Wang, Yibo3
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2023
卷号61页码:9
关键词Adaptive subtraction fast iterative shrinkage thresholding algorithm (FISTA)-Net multiple removals unsupervised
ISSN号0196-2892
DOI10.1109/TGRS.2023.3306511
英文摘要Adaptive subtraction plays a crucial role in the multiple removal method that involves modeling and subtraction steps. The linear regression (LR)-based method utilizes the fast iterative shrinkage thresholding algorithm (FISTA) to solve the optimization problem that contains the L1 norm minimization constraint of primaries. It selects the regularization factor and shrinkage thresholding value through trial and error. Under the non-LR framework, the U-net is used for adaptive subtraction of modeled multiples from the original recorded data. Since U-net has a large network capacity, it is prone to overfit to the original recorded data and lead to primary damage. In this article, we unfold the iterative steps of FISTA to construct FISTA-Net, which takes the original recorded data and modeled multiples as input data and outputs the estimated primaries. The FISTA-Net-based method does not require true primaries as labels and uses the L1 norm minimization constraint of primaries for unsupervised training. It can adaptively estimate the regularization factor and shrinkage thresholding value, which is replaced by U-net. FISTA-Net introduces the nonlinear mapping ability of U-net into its structure, which can be interpreted as the iterative steps of FISTA. As a result, the proposed FISTA-Net-based method can better attenuate residual multiples, avoid overfitting, and preserve primaries compared to the LR-based and U-net-based methods.
WOS关键词SHRINKAGE-THRESHOLDING ALGORITHM ; ITERATIVE INVERSION ; SCATTERING ; NETWORK
资助项目China Post-doctoral Science Foundation[2022M723127] ; National Natural Science Foundation of China[41804110] ; Shandong Provincial Education Department through the Youth Innovation Team Project[2022KJ141]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001064403200007
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构China Post-doctoral Science Foundation ; China Post-doctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Shandong Provincial Education Department through the Youth Innovation Team Project ; Shandong Provincial Education Department through the Youth Innovation Team Project ; China Post-doctoral Science Foundation ; China Post-doctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Shandong Provincial Education Department through the Youth Innovation Team Project ; Shandong Provincial Education Department through the Youth Innovation Team Project ; China Post-doctoral Science Foundation ; China Post-doctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Shandong Provincial Education Department through the Youth Innovation Team Project ; Shandong Provincial Education Department through the Youth Innovation Team Project ; China Post-doctoral Science Foundation ; China Post-doctoral Science Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Shandong Provincial Education Department through the Youth Innovation Team Project ; Shandong Provincial Education Department through the Youth Innovation Team Project
源URL[http://ir.iggcas.ac.cn/handle/132A11/110784]  
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Li, Zhongxiao
作者单位1.Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
2.Qingdao Univ, Sch Elect Informat, Dept Elect Engn, Qingdao 266071, Peoples R China
3.Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 Li, Zhongxiao,Sun, Keyi,Zeng, Tongsheng,et al. Unsupervised FISTA-Net-Based Adaptive Subtraction for Seismic Multiple Removal[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2023,61:9.
APA Li, Zhongxiao.,Sun, Keyi.,Zeng, Tongsheng.,Ma, Jiahui.,Qi, Zhen.,...&Wang, Yibo.(2023).Unsupervised FISTA-Net-Based Adaptive Subtraction for Seismic Multiple Removal.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,61,9.
MLA Li, Zhongxiao,et al."Unsupervised FISTA-Net-Based Adaptive Subtraction for Seismic Multiple Removal".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 61(2023):9.

入库方式： OAI收割

来源：地质与地球物理研究所

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