IGGCAS OpenIR  > 地球与行星物理院重点实验室
Progressive denoising of seismic data via robust noise estimation in dual domains
Lin, Yi1,2,3; Zhang, Jinhai1,2
2020
Source PublicationGEOPHYSICS
ISSN0016-8033
Volume85Issue:1Pages:V99-V118
AbstractRandom 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.
DOI10.1190/GEO2019-0010.1
Funding OrganizationNational 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
WOS KeywordEMPIRICAL-MODE DECOMPOSITION ; DATA RECONSTRUCTION ; SIGNAL ENHANCEMENT ; SEISLET TRANSFORM ; LOW-RANK ; T-X ; ATTENUATION ; PREDICTION ; INTERPOLATION ; SUPPRESSION
Language英语
Funding ProjectNational Major Project of China[2017ZX05008-007] ; National Natural Science Foundation of China[41941002]
Funding OrganizationNational 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
WOS Research AreaGeochemistry & Geophysics
WOS SubjectGeochemistry & Geophysics
WOS IDWOS:000506219100057
PublisherSOC EXPLORATION GEOPHYSICISTS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/95852
Collection地球与行星物理院重点实验室
Corresponding AuthorZhang, Jinhai
Affiliation1.Chinese Acad Sci, Key Lab Earth & Planetary Phys, Inst Geol & Geophys, Beijing, Peoples R China
2.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing, Peoples R China
3.Unvers Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
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.
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