期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 19, 期 -, 页码 -出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2022.3178915
关键词
Reflection; Deconvolution; Mathematical models; Couplings; Geoscience and remote sensing; Convolution; Approximation algorithms; Dual deconvolution (D-D); elastic full waveform inversion (EFWI); envelope-based sparse-constrained deconvolution; sparse-constrained deconvolution; wave mode decomposition
类别
资金
- National Natural Science Foundation of China [41904100]
- Oceanic Interdisciplinary Program of Shanghai Jiao Tong University [SL2020MS033]
- Scientific Research Fund of Second Institute of Oceanography [SL2020MS033]
- Talent Cultivation Project [SKX201901]
- High-Performance Computing Center of Zhejiang University
- Geophysical Computational Imaging and Instrumentation Group at Jilin University
This letter proposes solutions to the problem of local minima in elastic full waveform inversion (EFWI) from two aspects: low-frequency seismic data reconstruction and wave mode decomposition. The proposed methods, including envelope-based sparse-constrained deconvolution (E-SCD), dual deconvolution (D-D), and wave mode decomposition, effectively improve the resolution and accuracy of seismic data in the inversion process. Numerical experiments demonstrate the effectiveness of the proposed algorithm.
Affected by the low-frequency seismic data missing and multiple parameters coupling, elastic full waveform inversion (EFWI) is easy to fall into local minima. This letter attempts to solve the local minima problem from two aspects: low-frequency seismic data reconstruction and wave mode decomposition. First, by introducing the envelope into sparse-constrained deconvolution (SCD), an envelope-based SCD (E-SCD) method is proposed to overcome the problem caused by the phase shift and side lobes. However, the resolution of the envelope is insufficient to identify overlapping seismic events, which are generated by velocity models rich in thin layers. Therefore, SCD and E-SCD are combined, and a dual deconvolution (D-D) method is proposed: SCD is used to improve the resolution of the original seismic data, and then, E-SCD is used to reconstruct high-precision reflection sequence. Convolve the reconstructed reflection sequence with the full-band source wavelet to obtain the full-band seismic data. Second, for the multiparameter coupling problem, we use wave mode decomposition to obtain separated P- and S-waves. Finally, a multiscale EFWI method based on D-D and wave mode decomposition is proposed. Numerical experiment results demonstrate the algorithm proposed in this letter.
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