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Preparing the initial model for iterative deblending by median filtering

WEI CHEN1,2 ,  JIANG YUAN3 ,  YANGKANG CHEN4 ,  SHUWEI GAN3
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1 Key Laboratory of Exploration Technology for Oil and Gas Resources of the Ministry of Education, Yangtze University, Wuhan, Hubei 430100, P. R. China.,
2 Hubei Cooperative Innovation Center of Unconventional Oil and Gas, Wuhan, Hubei 430100, P.R. China.,
3 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Fuxue Road 18, Beijing 102200, P. R. China.,
4 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, U.S.A.,
JSE 2017, 26(1), 25–47;
Submitted: 27 April 2016 | Accepted: 20 November 2016 | Published: 1 February 2017
© 2017 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

Chen, W., Yuan, J., Chen, Y. and Gan, §., 2017. Preparing the initial model for iterative deblending by median filtering. Journal of Seismic Exploration, 26: 25-47. Simultaneous-source acquisition can obtain much faster acquisition with higher spatial sampling at the cost of obtaining highly noisy seismic records. While researchers are seeking specific direct imaging algorithms for attenuating the simultaneous-source interference during the migration process, deblending is still a preferable way to deal with simultaneous-source seismic data at the current stage. Removing blending noise while preserving as much useful signal as possible is thought to be the key in the deblending process. Previous study has shown that the median filtering (MF) can be used to effectively and efficiently separate the simultaneous-source seismic data in the common midpoint domain based on one-step filtering. In this paper, we investigate the application of MF in preparing the initial model in an inversion-based deblending framework. Our results show that the application of MF in a shaping regularized iterative deblending framework can effectively accelerate the convergence rate and improve the deblending performance in a limited number of iterations. We use three different synthetic examples and one field data example to demonstrate our proposed methodology.

Keywords
simultaneous source
deblending
shaping regularized iterative inversion
median filtering (MF)
initial model of deblending
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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