Retrieval of surface waves from high-speed-train-induced vibrations using seismic interferometry

Abstract

Train traffic has recently been realized as a potential seismic source for imaging and monitoring shallow subsurface structures. High-speed trains usually move on viaducts and generate seismic wavefields through bridge piers. This kind of source is not randomly distributed in space and time and thus indicates the characteristic of self-correlation. We find that correlated sources of one high-speed train running over piers make time-delayed spurious signals in the crosscorrelation functions. The direct-wave interferometry with correlated sources is proposed and demonstrates that stacking the interferometric responses from high-speed trains with different speeds may reduce the spurious imprint of source self-correlations, but it cannot remediate the problem. The influence of the source wavelet can be eliminated by using cross coherence. Stationary-phase segment selection and stacking can reduce the bias generated by trains moving out of the stationary-phase zone of station pairs. The validity is demonstrated by using synthetic data with inline and out-of-line linear arrays. We apply the proposed scheme to field data with nine high-speed train events. Multimodal Rayleigh waves were retrieved and shallow shear-wave velocities were inverted from multimodal dispersion data in a range of 4–25 Hz. The results bring a novel approach for the imaging and monitoring of the shallow subsurface using high-speed-train-induced vibrations.