Multi-objective particle swarm optimization for Rayleigh wave full waveform inversion
Conventional full waveform inversion (FWI) of Rayleigh wave updates the earth model iteratively by minimizing the difference between measured and synthetic data using single-objective function. However, FWI of Rayleigh wave is challenging due to its high nonlinearity and multimodality. Thus, single-objective inversion may lead to incorrect results, and multi-objective inversion is attractive to obtain global optimal solution. In this paper, we propose a multi-objective particle swarm optimization (MOPSO) scheme for FWI of Rayleigh wave. During the MOPSO inversion, the model is optimized iteratively by using multiple criteria simultaneously. We adopt four objective functions in our proposed MOPSO strategy to characterize the observed data: waveform, peak time, waveform envelope and phase velocity spectrum. The concept of Pareto optimal solution set is introduced in the MOPSO strategy to avoid the contradiction of multi-objective functions. Each non-dominated solution is recorded on the Pareto optimal set for model iteration. Both synthetic data and real field data demonstrate the effectiveness and practicability of the MOPSO strategy.
National Natural Science Foundation of China;National Natural Science Foundation of China;National Natural Science Foundation of China;
|WOS Research Area|
Geology ; Mining & Mineral Processing
Geosciences, Multidisciplinary ; Mining & Mineral Processing
|WOS Accession No|
|ESI Research Field|
Cited Times [WOS]:0
|Document Type||Journal Article|
|Department||Department of Earth and Space Sciences|
1.School of Geophysics and Geomatics,China University of Geosciences,Wuhan,Hubei,China
2.College of Metrology & Measurement Engineering,China Jiliang University,Zhejiang,Hangzhou,China
3.Department of Earth and Space Sciences,Southern University of Science and Technology,Shenzhen,Guangdong,China
Le，Zhao,Song，Xianhai,Zhang，Xueqiang,et al. Multi-objective particle swarm optimization for Rayleigh wave full waveform inversion[J]. Journal of Applied Geophysics,2023,215.
Le，Zhao.,Song，Xianhai.,Zhang，Xueqiang.,Shen，Chao.,Shi，Xueming.,...&Yuan，Shichuan.(2023).Multi-objective particle swarm optimization for Rayleigh wave full waveform inversion.Journal of Applied Geophysics,215.
Le，Zhao,et al."Multi-objective particle swarm optimization for Rayleigh wave full waveform inversion".Journal of Applied Geophysics 215(2023).
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