Near-surface Imaging Based on Cross-coherence Method with High-Speed-Train-Induced Vibrations

Abstract High-speed trains (HST) generate seismic waves that can serve as a powerful ambient noise source for near-surface imaging. To image the S-wave velocity of the near-surface using the HST seismic signals, we apply the seismic interferometry and compare the effects of two interferometry techniques: cross-correlation and cross-coherence. After processing the measured data, we recovered the Rayleigh wave data in the 1∼5Hz range from the original HST seismic data. The comparison shows that the cross-coherence technique produces surface wave data with a higher signal-to-noise ratio. We then process the obtained virtual shot gathers using the multi-channel surface wave analysis (MASW) method and invert them to obtain the S-wave velocity structure of the subsurface.