Abstract

AbstractDespite the fact that earthquake occurrence can be strongly influenced by the architecture of pre‐existing faults, it remains challenging to obtain information about the detailed subsurface geometries of active fault systems. Current geophysical methods for studying such systems often fail to resolve geometrical complexities at sufficiently high spatial resolutions. In this work, we present a novel method for imaging the detailed 3D architectures of seismically active faults based on high‐precision hypocenter catalogs, using nearest neighbor learning and principal component analysis. The proposed approach enables to assess variations in fault instabilities and kinematics. We apply the method to the relatively relocated St. Léonard (max.ML = 3.2) and Anzère (max.ML = 3.3) microearthquake sequences in the Southwestern Swiss Alps, revealing strike‐slip fault systems with interconnecting stepovers at depths of 3–7 km and lengths ranging from 0.5 to 2 km. In combination with additional information about fault instabilities and kinematics, we observe significantly reduced earthquake migration velocities and fault locking processes within the stepovers. Understanding such processes and their role in the propagation of strain across stepovers is of great relevance, as these structures can potentially limit earthquake ruptures but also represent possible locations for the nucleation of larger ruptures. Our proposed method is expected to be broadly useful for further applications such as monitoring hydraulic fracture stimulations or geothermal exploration of natural, fluid‐bearing faults. Conducting similar high‐resolution spatiotemporal analyses of microseismic sequences has the potential to greatly enhance our comprehension of how the 3D fault architecture impacts seismogenic fault reactivation.

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