Fault detection by reflected surface waves based on ambient noise interferometry

Abstract

Detecting subsurface fault structure is important for evaluating potential earthquake risks associated with active faults. In this study, we propose a new method to detect faults using reflected surface waves observed in ambient noise cross correlation functions. Ambient noise tomography using direct surface waves obtained from ambient noise interferometry has been widely used to characterize active fault zones. In cases where a strong velocity contrast exists across the fault interface, fault-reflected surface waves are expected. We test this idea using a linear array deployed in the Suqian segment of Tanlu fault zone in Eastern China. The fault-reflected surface waves can be clearly seen in the cross-correlation functions of the ambient noise data, and the spatial position of the fault on the surface is close to the stations where the reflected signals first appear. Potentially reflected surface waves could also be used to infer the dip angle, fault zone thickness and the degree of velocity contrast across the fault by comparing synthetic and observed waveforms.