Deep Learning-Based Microseismic Detection and Location Reveal the Seismic Characteristics and Causes in the Xiluodu Reservoir, China

Abstract

ABSTRACT The Xiluodu reservoir, as the third reservoir developed in the lower Jinsha River, is the fourth largest reservoir in the world in terms of power generation. It is located in an area of historically high seismic intensity. A large amount of seismic activity has occurred in the reservoir area because the reservoir was impounded in 2013, but the mechanism of seismogenesis is still not clear. In this study, we collected continuous seismic records from July 2020 to October 2022 in the Xiluodu reservoir area, built a high-precision microseismic catalog for this region based on a deep learning seismic detection and location workflow called LOC-FLOW, and eventually obtained high-precision locations of 4924 earthquakes (five times more than the routine catalog). We sketched the main seismogenic structures based on the spatial and temporal distribution of the earthquakes in the catalog. According to the relationship between periodic variation of water level and seismic activity, seismicity in the reservoir area is active at the stage when the water level is filling to the highest point and starts to draw down. Especially, the sudden change in the rate of water level variation can easily trigger seismic activity. Combined with the spatiotemporal distribution of seismicity in each region and the previous results of numerical simulation, we concluded that the seismic activity in the reservoir head area and around the Manao fault is likely induced by the increase of normal stress and pore pressure diffusion caused by reservoir impoundment, whereas the ML 4.6 earthquake that occurred at the intersection of the Lianfeng fault and the Zhongcun fault was likely tectonic activity occurring on a concealed fault.