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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Damped multichannel singular spectrum analysis for 3D random noise attenuation

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Huang, Weilin ; Wang, Runqiu ; Chen, Yangkang ; Li, Huijian ; Gan, Shuwei
Total Authors: 5
Document type: Journal article
Source: GEOPHYSICS; v. 81, n. 4, p. V261-V282, JUL-AUG 2016.
Web of Science Citations: 66

Multichannel singular spectrum analysis (MSSA) is an effective algorithm for random noise attenuation in seismic data, which decomposes the vector space of the Hankel matrix of the noisy signal into a signal subspace and a noise subspace by truncated singular value decomposition (TSVD). However, this signal subspace actually still contains residual noise. We have derived a new formula of low-rank reduction, which is more powerful in distinguishing between signal and noise compared with the traditional TSVD. By introducing a damping factor into traditional MSSA to dampen the singular values, we have developed a new algorithm for random noise attenuation. We have named our modified MSSA as damped MSSA. The denoising performance is controlled by the damping factor, and our approach reverts to the traditional MSSA approach when the damping factor is sufficiently large. Application of the damped MSSA algorithm on synthetic and field seismic data demonstrates superior performance compared with the conventional MSSA algorithm. (AU)

FAPESP's process: 13/08293-7 - CCES - Center for Computational Engineering and Sciences
Grantee:Munir Salomao Skaf
Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC