Huai-shan Liu, Yu-zhao Lin*, Lei Xing, He-hao Tang, and Jing-hao Li
1. State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Eff ective Development, No. 197, Baisha Road,
Shahe Town, Changping District, 102206, Beijing, China,
2. Sinopec Key Laboratory of Seismic Elastic Wave Technology, No. 197, Baisha Road, Shahe Town, Changping District,
102206, Beijing, China and
3. College of Marine Geosciences, Ocean University of China, No.238, Miaoling Road, Laoshan District, 266100, Qingdao,
China
Abstract Full waveform inversion methods evaluate the properties of subsurface media by minimizing the misfit between synthetic and observed data. However, these methods omit measurement errors and physical assumptions in modeling, resulting in several problems in practical applications. In particular, full waveform inversion methods are very sensitive to erroneous observations (outliers) that violate the Gauss–Markov theorem. Herein, we propose a method for addressing spurious observations or outliers. Specifically, we remove outliers by inverting the synthetic data using the local convexity of the Gaussian distribution. To achieve this, we apply a waveform-like noise model based on a specific covariance matrix definition. Finally, we build an inversion problem based on the updated data, which is consistent with the wavefield reconstruction inversion method. Overall, we report an alternative optimization inversion problem for data containing outliers. The proposed method is robust because it uses uncertainties. This method enables accurate inversion, even when based on noisy models or a wrong wavelet.
Fund: This research project is supported in part by the National Natural Science Foundation of China under Grant 42276055; in part by the National Key Research and Development Program under Grant 2022YFC2803503; in part by the Fundamental Research Funds for the Central Universities under Grant 202262008.
Corresponding Authors: Yu-zhao Lin (Email: 798126072@qq.com).
E-mail: 798126072@qq.com
About author: Liu Huai-shan obtain an M.S. in Marine Geology in 1992 from the Ocean University of China, and a Ph.D. in Marine Geology in 1997 from the Ocean University of China. He currently works at the College of Marine Geosciences of Ocean University of China. His main research interests are geophysical prospecting, marine geophysics, gas hydrate exploration.
Cite this article:
. Bayesian-based Full Waveform Inversion[J]. APPLIED GEOPHYSICS, 2025, 22(1): 1-11.
2025, Vol. 22 
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