Application of multichannel analysis of passive surface waves method for fault investigation

Research on faulting is of fundamental significance to the exploration of geothermal resources since faulting is an important factor in the formation of traps for water accumulation. The high-frequency passive surface waves methods using ambient noise data become more popular because of its low-cost, environment-friendly, non-destructive and efficient advantages. We have conducted a field work in Hetian town of Zhejiang Province to evaluate the feasibility of high-frequency passive surface wave survey for fault investigation. We adopted the multichannel analysis of passive surface waves (MAPS) to process the high-frequency (>1 Hz) ambient noise for retrieving surface waves. Spectral analysis indicated that the dominant energy of ambient noise is focused on the frequency band from 1 to 12 Hz. We utilized the beamforming technique to show the distribution of ambient noise energy and the stable phase-velocity range of plane wave and reveal the location of interior sources in the receiver array. We selected these segments with less interior-source contamination from noise data collected at night to obtain clear and continuous surface-wave dispersion energy. The cross-correlation functions are obtained from ambient noise to acquire accurate phase velocity of surface waves. The dispersion curves of surface waves are inverted for shear (S)-wave velocity profiles. The faults revealed in the inversion profiles match well with the previous geological references. The inverted S-wave velocity profiles are consistent with the results of controlled source audio-magnetotelluric in terms of the characteristics of the layered structures. Our synthetic and real-world tests demonstrated that the waveforms of virtual shot gathers and dispersion images of surface waves are affected by interior sources of a receiver array. Results indicated that the survey arrays should be distributed along roads instead of crossing them. The success of this case study showed that MAPS has the great potential for fault investigation using ambient noise in town environment.