Near-Surface Characterization Using High-Speed Train Seismic Data Recorded by a Distributed Acoustic Sensing Array
Jie Shao, Yibo Wang, Ling Chen
Abstract
A high-speed train can be regarded as a moving seismic source when it travels along a railway. Seismic waves from such sources have strong energy and can be used for near-surface characterization, safety monitoring of high-speed railways, and detection of urban underground spaces. Distributed acoustic sensing (DAS) is a newly developed seismic acquisition technology. It has attracted widespread attention due to its advantages of low cost, high sensitivity, high efficiency, and dense sampling. This study investigated near-surface characterization using high-speed train seismic data recorded by DAS. The data were processed to obtain surface waves by seismic interferometry. Thereafter, the extracted surface waves were inverted to obtain the near-surface shear-wave velocity model using a multichannel analysis method. The inverted model is consistent with the subsurface geology of the study area. Our results demonstrate the effectiveness and reliability of DAS-based acquisition and data analysis in near-surface characterization using the high-speed train type of moving sources.