High‐Resolution Ambient Noise Imaging of Geothermal Reservoir Using 3C Dense Seismic Nodal Array and Ultra‐Short Observation

Abstract

AbstractTomographic imaging based on long‐term ambient seismic noise measurements, mainly the phase information from surface waves, has been shown to be a powerful tool for geothermal reservoir imaging and monitoring. In this study, we utilize seismic noise data from a dense nodal array (192 3C nodes within 20 ) over a ultra‐short observation period (4.7 days) to reconstruct surface waves and determine the high‐resolution (0.2 km) three‐dimensional (3‐D) S wave velocity structure beneath a rural town in Zhejiang, China. We report the advantage of cross‐coherence over cross‐correlation in suppressing pseudo‐arrivals caused by persistent sources. We use ambient noise interferometry to retrieve high quality Rayleigh waves and Love waves. Body waves are also observed on the R‐R component interferograms. We apply phase velocity dispersion measurements on both Rayleigh waves and Love waves and automatically pick more than 23,000 dispersion curves by using a Machine Learning technique. 3‐D surface wave tomographic results after depth inversion indicate low‐velocity anomalies (between −1% and −4%) from the surface to 2 km depth in the central area. Combined with the conductive characteristics observed on resistivity profile, the low‐velocity anomalies are inferred to be a fluid saturated zone of highly fractured rock. Joint interpretation based on horizontal‐to‐vertical spectral ratio (HVSR) measurements, and existing temperature and fluid resistivity records observed in a nearby well, suggests the existence of the high‐temperature geothermal field through the fracture channel. Strong correlation between HVSR measurements and the S wave velocity model highlights the potential of extraction of both amplitude and phase information from ambient noise.