Multi-objective particle swarm optimization for Rayleigh wave full waveform inversion

Le，Zhao1; Song，Xianhai1; Zhang，Xueqiang1; Shen，Chao2; Shi，Xueming1; Wang，Yiming1; Yuan，Shichuan3

2023-08-01

10.1016/j.jappgeo.2023.105096

Journal of Applied Geophysics   Impact Factor & Quartile

0926-9851

1879-1859

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.

Full waveform inversion Multi-objective optimization Particle swarm optimization Rayleigh wave

SCI

English

Others

National Natural Science Foundation of China[41674142];National Natural Science Foundation of China[41874150];National Natural Science Foundation of China[42074164];

Geology ; Mining & Mineral Processing

Geosciences, Multidisciplinary ; Mining & Mineral Processing

WOS:001039886300001

ELSEVIER

GEOSCIENCES

2-s2.0-85164221549

Scopus

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).