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Adaptive iterative deblending of simultaneous-source seismic data based on sparse inversion

  • Research Article - Applied Geophysics
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Abstract

Deblending of simultaneous-source seismic data is becoming more popular in seismic exploration since it can greatly improve the efficiency of seismic acquisition and reduce acquisition cost. At present, the deblending methods of simultaneous-source seismic data are mainly divided into two types: filtering method and sparse inversion method. Compared with the filtering method, the sparse inversion method has higher precision, but the selection of its parameter value mainly depends on experience, which is not suitable for large-scale seismic data processing. In this paper, an adaptive iterative deblending method based on sparse inversion is proposed. By improving the original iterative solution method of regularization inversion model, the effective signal and blending noise are weakened simultaneously in the iterative process, so that the energy intensity of blending noise is consistent with that of the effective signal in each iterative, so as to ensure the consistency of the regular parameter calculation method of each iteration. By analyzing the distribution of coefficients in the curvelet domain of pseudo-deblending data and blending noise, it is concluded that the value of regular parameters is the maximum amplitude of residual pseudo-deblending data in the curvelet domain multiplied by a coefficient between 0 and 1. In the process of iterative deblending, the regularized parameters are obtained adaptively from the data itself. It not only ensures the accuracy of the calculation results, but also improves the calculation efficiency, which is suitable for large-scale seismic data processing.

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source includes 2 single sources. a Pseudo-deblending data. b Blending noise. c Amplitude value of coefficient in the curvelet domain

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source includes 5 single sources. a Pseudo-deblending data. b Blending noise. c Amplitude value of coefficient in the curvelet domain

Fig. 5

source includes 10 single sources. a Pseudo-deblending data. b Blending noise. c Amplitude value of coefficient in the curvelet domain

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Acknowledgments

This work is supported by National Natural Science Foundation of China (grant numbers 41974166, 41674114), Natural Science Foundation of Hebei Province (grant numbers D2019403063, D2019403082).

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Authors and Affiliations

  1. Hebei Key Laboratory of Strategic Critical Mineral Resources, Hebei GEO University, Shijiazhuang, 050031, China

    Yajie Wei, Jingjie Cao, Xue Chen & Zhicheng Cai

  2. CNOOC Research Institute Co., Ltd, Beijing, 100028, China

    Xiaogang Huang

Authors
  1. Yajie Wei
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  2. Jingjie Cao
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  3. Xiaogang Huang
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  4. Xue Chen
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  5. Zhicheng Cai
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Corresponding author

Correspondence to Jingjie Cao.

Additional information

Communicated by Michal Malinowski (CO-EDITOR-IN-CHIEF)/Sanyi Yuan (ASSOCIATE EDITOR).

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Wei, Y., Cao, J., Huang, X. et al. Adaptive iterative deblending of simultaneous-source seismic data based on sparse inversion. Acta Geophys. 69, 497–507 (2021). https://doi.org/10.1007/s11600-021-00561-1

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  • DOI: https://doi.org/10.1007/s11600-021-00561-1

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