Paper Info
Title
Subsurface Elastic Parameter Reconstruction Based on Seismic Data From the High-Speed Trains Using Full Waveform Inversion
Abstract
In this study, we attempt to use the high-speed train (HST)-induced seismic data for subsurface elastic parameter reconstruction by the full waveform inversion (FWI) method. The HSTs provide a new kind of seismic source as the superposition of a series of moving subsources. We consider the situation of HST running on the viaduct and use a finite difference method to simulate the seismic wave excitation. The result shows that the HST-induced seismic data are highly complex in the time domain but appear as a series of discrete peaks in the frequency domain. Elastic FWI is used to retrieve the P- and S-wave velocities of the subsurface based on this new kind of seismic data. The alternative iteration strategy and multiscale inversion are used to improve the inversion results. Numerical examples with the Marmousi2 model show the feasibility and the great potential of using this new kind of seismic data in seismic imaging.
Year
DOI
Venue
2022
10.1109/TGRS.2022.3151352
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Keywords
DocType
Volume
Wheels, Vibrations, Imaging, Data models, Seismic waves, Loading, Receivers, Elastic full waveform inversion (FWI), ground vibration, high-speed trains (HSTs), moving combination source
Journal
60
ISSN
Citations 
PageRank 
0196-2892
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Jingrui Luo100.68
Xiaokai Wang201.35
Wenchao Chen3109.51