Joint Inversion of Rayleigh Wave Phase Velocity, Particle Motion, and Teleseismic Body Wave Data for Sedimentary Structures

Mapping seismic structures of sedimentary basins is of great importance to better evaluate energy resources and seismic hazards. In this study, we develop a joint Bayesian Monte Carlo nonlinear inversion method that utilizes the complementary nature of Rayleigh wave phase velocity, Rayleigh wave par...

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Veröffentlicht in:Geophysical research letters 2019-06, Vol.46 (12), p.6469-6478
Hauptverfasser: Li, Guoliang, Niu, Fenglin, Yang, Yingjie, Tao, Kai
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Sprache:eng
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Zusammenfassung:Mapping seismic structures of sedimentary basins is of great importance to better evaluate energy resources and seismic hazards. In this study, we develop a joint Bayesian Monte Carlo nonlinear inversion method that utilizes the complementary nature of Rayleigh wave phase velocity, Rayleigh wave particle motion, and teleseismic P wave in responding to sedimentary structures. Synthetic tests demonstrate that our joint inversion can retrieve the input sedimentary models better than inversions with surface or body wave data alone. We apply our method to waveform data of two broadband stations inside the Songliao Basin in northeast China to invert for sedimentary structures beneath the two stations. We verify our results by successfully isolating the Moho P‐to‐S conversion from sediment reverberations in surface receiver functions with a wavefield‐downward‐continuation technique. We further demonstrate that we can extend our method to single‐station inversions by excluding the Rayleigh wave phase velocity in the inversion. Key Points Rayleigh wave phase velocity, particle motion, and teleseismic body wave data are jointly inverted for high‐resolution sedimentary models The high‐resolution sedimentary models are used to effectively extract deep structural signals by removing sediment reverberations The method can be extended to single‐station recordings by excluding the Rayleigh wave phase velocity
ISSN:0094-8276
1944-8007
DOI:10.1029/2019GL082746