Geothermal Reservoir Characterization Using Seismic Moment Tensor Solutions from Distributed Fiber Optic Sensing

Abstract Seismic moment tensors provide important information to understand the origin and nature of seismic sources. They have been used to elucidate the dynamics of plate tectonics, the state of active volcanoes, and to characterize subsurface reservoirs. Distributed fiber optic sensing (DFOS) provides unrivaled sampling of the seismic source radiation pattern, which is necessary to estimate moment tensors (MTs). In this study, we demonstrate a significant step toward tapping the potential of moment tensor inversion with DFOS. For that purpose, we analyze more than 14.5 million seismic arrivals to automatically estimate the full MT of thousands of seismic events. The benefits of accessing large numbers of MTs are demonstrated with the characterization of the geothermal reservoir at the Utah Frontier Observatory for Research in Geothermal Energy underground laboratory. The interpretation reveals the important role of the interaction between induced and natural fractures in providing hydraulic connectivity for the enhanced geothermal system at the site. Furthermore, the estimated MTs complement previous studies by providing otherwise inaccessible information about the spatial variability and hydraulic relevance of natural fractures.