Published as Geophysics, 81, V261-V270, (2016)

Damped multichannel singular spectrum analysis for 3D random noise attenuation

Weilin Huang% latex2html id marker 3414
\setcounter{footnote}{1}\fnsymbol{footnote}, Runqiu Wang% latex2html id marker 3415
\setcounter{footnote}{1}\fnsymbol{footnote}, Yangkang Chen% latex2html id marker 3416
\setcounter{footnote}{2}\fnsymbol{footnote}, Huijian Li% latex2html id marker 3417
\setcounter{footnote}{1}\fnsymbol{footnote}, and Shuwei Gan% latex2html id marker 3418
% latex2html id marker 3419
\setcounter{footnote}{1}\fnsymbol{footnote}State Key Laboratory of Petroleum Resources and Prospecting
China University of Petroleum
Fuxue Road 18th
Beijing, China, 102200 & & &
% latex2html id marker 3420
\setcounter{footnote}{2}\fnsymbol{footnote}Bureau of Economic Geology
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX 78713-8924


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 the truncated singular value decomposition (TSVD). However, this signal subspace actually still contains residual noise. We 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 the traditional MSSA for damping the singular values, we proposed a new algorithm for random noise attenuation. The proposed modified MSSA is named as the damped MSSA. The denoising performance is controlled by the damping factor and the proposed 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 a superior performance compared with the conventional MSSA algorithm.