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WITHDRAWN Building Non-planar 3D Fault Models From Earthquake Hypocenters

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WITHDRAWN Accurately characterizing three-dimensional (3D) fault geometry is vital for improving understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained due to limitations in observational data. We present an automated approach to constructing 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, allowing us to identify coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. Unlike traditional methods that rely on planar approximations, we employ surface fitting using support vector regression to balance surface accuracy with minimal deviations from planarity. To assess the quality of these models, we compute the spatial density of seismicity relative to the faults and evaluate how well it matches the documented tendency for hypocentral density to decrease with distance from the fault following a modified power-law. The verified fault models are output as triangular meshes at user-defined resolution.

As a proof of concept, we apply this approach to the San Andreas-Calaveras Fault junction region and the 2019 Ridgecrest earthquake sequence, both in California. These case studies demonstrate the method’s ability to delineate complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double-difference relocated catalogs. We find that our seismicity-based fault model results align with published 3D models that incorporate additional constraints and interpretations (Aagaard & Hirakawa, 2021; Plesch et al., 2020). This workflow provides a low-user-input solution for reconstructing fault geometries at depth from earthquake catalogs.

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