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Journal of Inverse and Ill-posed Problems

Editor-in-Chief: Kabanikhin, Sergey I.

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Volume 26, Issue 2


Full waveform inversion with sparse structure constrained regularization

Zichao Yan
  • Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, P. O. Box 9825, Beijing 100029, P. R. China; and University of Chinese Academy of Sciences, Beijing 100049, P. R. China
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/ Yanfei Wang
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  • Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, P. O. Box 9825, Beijing 100029, P. R. China; and University of Chinese Academy of Sciences, Beijing 100049, P. R. China
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Published Online: 2017-10-17 | DOI: https://doi.org/10.1515/jiip-2016-0076


Full waveform inversion is a large-scale nonlinear and ill-posed problem. We consider applying the regularization technique for full waveform inversion with structure constraints. The structure information was extracted with difference operators with respect to model parameters. And then we establish an lp-lq-norm constrained minimization model for different choices of parameters p and q. To solve this large-scale optimization problem, a fast gradient method with projection onto convex set and a multiscale inversion strategy are addressed. The regularization parameter is estimated adaptively with respect to the frequency range of the data. Numerical experiments on a layered model and a benchmark SEG/EAGE overthrust model are performed to testify the validity of this proposed regularization scheme.

Keywords: Acoustic wave equation; full waveform inversion; structure constraints; regularization

MSC 2010: 65J22; 86-08; 86A22


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About the article

Received: 2016-11-02

Revised: 2017-08-04

Accepted: 2017-08-24

Published Online: 2017-10-17

Published in Print: 2018-04-01

Funding Source: National Natural Science Foundation of China

Award identifier / Grant number: 41325016

Award identifier / Grant number: 91630202

The research is supported by National Natural Science Foundation of China under grant numbers 41325016 and 91630202.

Citation Information: Journal of Inverse and Ill-posed Problems, Volume 26, Issue 2, Pages 243–257, ISSN (Online) 1569-3945, ISSN (Print) 0928-0219, DOI: https://doi.org/10.1515/jiip-2016-0076.

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