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  4. 中国科学院地球与行星物理重点实验室
Progressive denoising of seismic data via robust noise estimation in dual domains

文献类型：期刊论文

作者Lin, Yi1,2,3; Zhang, Jinhai1,3
刊名GEOPHYSICS
出版日期2020
卷号85期号:1页码:V99-V118
ISSN号0016-8033
DOI10.1190/GEO2019-0010.1
英文摘要Random noise attenuation plays an important role in seismic data processing. Most traditional methods suppress random noise either in the time-space domain or in the transformed domain, which may encounter difficulty in retaining the detailed structures. We have introduced the progressive denoising method to suppress random noise in seismic data. This method estimates random noise at each sample independently by imposing proper constraints on local windowed data in the time-space domain and then in the transformed domain, and the denoised results of the whole data set are gradually improved by many iterations. First, we apply an unnormalized bilateral kernel in time-space domain to reject large-amplitude signals; then, we apply a range kernel in the frequency-wavenumber domain to reject medium-amplitude signals; finally, we can obtain a total estimate of random noise by repeating these steps approximately 30 times. Numerical examples indicate that the progressive denoising method can achieve a better denoising result, compared with the two typical single-domain methods: the f-x deconvolution method and the curvelet domain thresholding method. As an edge-preserving method, the progressive denoising method can greatly reduce the random noise without harming the useful signals, especially to those high-frequency components, which would be crucial for high-resolution imaging and interpretations in the following stages.
WOS关键词EMPIRICAL-MODE DECOMPOSITION ; DATA RECONSTRUCTION ; SIGNAL ENHANCEMENT ; SEISLET TRANSFORM ; LOW-RANK ; T-X ; ATTENUATION ; PREDICTION ; INTERPOLATION ; SUPPRESSION
资助项目National Major Project of China[2017ZX05008-007] ; National Natural Science Foundation of China[41941002]
WOS研究方向Geochemistry & Geophysics
语种英语
WOS记录号WOS:000506219100057
出版者SOC EXPLORATION GEOPHYSICISTS
资助机构National Major Project of China ; National Major Project of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Major Project of China ; National Major Project of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Major Project of China ; National Major Project of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Major Project of China ; National Major Project of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://ir.iggcas.ac.cn/handle/132A11/95852]  
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.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing, Peoples R China
2.Unvers Chinese Acad Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Key Lab Earth & Planetary Phys, Inst Geol & Geophys, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Lin, Yi,Zhang, Jinhai. Progressive denoising of seismic data via robust noise estimation in dual domains[J]. GEOPHYSICS,2020,85(1):V99-V118.
APA Lin, Yi,&Zhang, Jinhai.(2020).Progressive denoising of seismic data via robust noise estimation in dual domains.GEOPHYSICS,85(1),V99-V118.
MLA Lin, Yi,et al."Progressive denoising of seismic data via robust noise estimation in dual domains".GEOPHYSICS 85.1(2020):V99-V118.

入库方式： OAI收割

来源：地质与地球物理研究所

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