A Consistent High-Resolution Catalog of Induced Seismicity in Basel Based on Matched Filter Detection and Tailored Post-Processing

Abstract

Seismic monitoring of the Basel Enhanced Geothermal System (EGS) has been running for more than a decade. Yet, the details of the long-term behavior of its induced seismicity remained unexplored because a seismic event catalog with consistent detection sensitivity and magnitudes did not exist. This knowledge is essential for developing guidelines and mitigation procedures on how to safely operate and terminate injection activities. Only few observational data exist that cover all phases of such projects in a consistent manner. Here, we describe a method that overcomes these deficiencies based on sensitive matched filter detection and a machine learning approach to remove false detections. With an emphasis on consistency, we create a catalog that contains more than 280 000 events down to Mw−1.5. The much higher temporal resolution allows us to analyze induced microearthquakes in great detail and to gain new insights. We resolved temporal variations of seismicity parameters and, in the post-operational phase, a preferential temporal clustering of events. We find a breakdown in the Gutenberg--Richter scaling during reservoir stimulation, which may have physical reasons or could be caused by a method-independent detection limit during high event rates. The scaling breakdown has implications for the design of Adaptive Traffic Light Systems and may limit the potential of real-time mitigation strategies in future EGS projects. Nevertheless, our catalog gives the opportunity to study the temporal evolution of the sequence in unprecedented detail, which will help to better understand the physical processes in a geothermal reservoir, potentially not only in the Basel case.