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Iterative deblending based on the modified singular spectrum analysis

JUAN WU,  MIN BAI
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Key Laboratory of Exploration Technology for Oil and Gas Resources of the Ministry of Education, Yangtze University, Wuhan 430100, P.R. China,
JSE 2019, 28(1), 1–20;
Submitted: 18 February 2018 | Accepted: 7 October 2018 | Published: 1 February 2019
© 2019 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Wu, J. and Bai, M., 2019. Iterative deblending based on the modified singular spectrum analysis. Journal of Seismic Exploration, 28: 1-20. Deblending of simultaneous-source seismic data aims at separating the blended records caused by simultaneous shooting as if the data are acquired traditionally. In this paper, we propose a novel modified singular spectrum analysis (SSA) approach to remove blending noise in an iterative inversion manner. Compared with the traditional SSA approach, the modified SSA approach applies a modified truncated singular value decomposition (TSVD) onto the Hankel matrix in the frequency domain, and can attenuate more blending noise than the traditional SSA method. We use both synthetic and field data examples to demonstrate that the proposed modified SSA method has a stronger signal-and-noise separability.

Keywords
deblending
singular value decomposition
noise
singular spectrum analysis
iterative solver
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