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Separating Scholte Wave and Body Wave in OBN Data Using Wave-Equation Migration

文献类型：期刊论文

作者Li, Chao2,3; Wang, Yuan2,3; Zhang, Jinhai2,3; Geng, Jianhua1; You, Qingyu2,3; Hu, Yaoxing2,3; Liu, Yuzhu1; Hao, Tianyao2,3; Yao, Zhenxing2,3
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2022
卷号60页码:13
关键词Surface waves Sea surface Filtering Imaging Cutoff frequency Background noise Underwater vehicles Body wave demigration migration ocean bottom node (OBN) Scholte wave wavefield separation
ISSN号0196-2892
DOI10.1109/TGRS.2022.3169427
英文摘要The ocean bottom nodes (OBNs) acquire seismic data at a challenging depth to explore the subsurface structures. The recorded body wave and Scholte wave are highly mixed and are difficult to be separated. The strong body wave would influence the high-order modes extraction using the Scholte wave, while the Scholte wave would degrade the imaging of sedimentary structures using body wave. The lacking of effective methods for separating both waves prevents their application. We developed a migration-based method to accurately separate the Scholte wave and body wave in the OBN data. First, we use high-pass filtering to divide the original OBN data into three parts: background noise, high-frequency body wave, and the mixture of Scholte wave and low-frequency body wave. Then, we separate the Scholte wave and low-frequency body wave using migration and demigration based on the fact that they have different limits of reversible-migration velocity. Finally, we generate the separated body wave by subtracting the Scholte wave from the denoised OBN data. For the off-line data, the local orthogonalization method is required to retrieve the weak leakage of Scholte wave around the apices. Theoretical analyses and numerical experiments show that the proposed method can accurately separate Scholte wave and body wave without any visible artifacts while retaining most of their inherent properties. The separated body wave provides a high-quality input for imaging sedimentary structures, and the separated Scholte wave enables the extraction of high-order modes of dispersion curve that are crucial for high-resolution surface-wave inversion.
WOS关键词FREQUENCY SURFACE-WAVES ; DISPERSION-CURVES ; OCEAN ; INVERSION ; SEDIMENTS ; DIFFRACTIONS ; TOMOGRAPHY ; TRANSFORM
资助项目National Key Research and Development Program of the Ministry of Science and Technology of China[2020YFA0713400] ; Key Research Program of the Chinese Academy of Sciences[ZDBS-SSW-TLC001] ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016)
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000793964300001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; National Key Research and Development Program of the Ministry of Science and Technology of China ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Key Research Program of the Chinese Academy of Sciences ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016) ; Foundation for Excellent Member of the Youth Innovation Promotion Association, Chinese Academy of Sciences (2016)
源URL[http://ir.iggcas.ac.cn/handle/132A11/105943]  
专题地质与地球物理研究所_中国科学院地球与行星物理重点实验室
通讯作者Zhang, Jinhai
作者单位1.Tongji Univ, State Key Lab Marine Geol, Shanghai 200092, Peoples R China
2.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing 100864, Peoples R China
3.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Earth & Planetary Phys, Beijing 100864, Peoples R China
推荐引用方式
GB/T 7714		 Li, Chao,Wang, Yuan,Zhang, Jinhai,et al. Separating Scholte Wave and Body Wave in OBN Data Using Wave-Equation Migration[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:13.
APA Li, Chao.,Wang, Yuan.,Zhang, Jinhai.,Geng, Jianhua.,You, Qingyu.,...&Yao, Zhenxing.(2022).Separating Scholte Wave and Body Wave in OBN Data Using Wave-Equation Migration.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,13.
MLA Li, Chao,et al."Separating Scholte Wave and Body Wave in OBN Data Using Wave-Equation Migration".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):13.

入库方式： OAI收割

来源：地质与地球物理研究所

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