Fine-scale Segmentation and Spatiotemporal Variability of the 2010 Mw 8.8 Maule Aftershock Sequence Revealed by a Deep-Learning-Based Earthquake Catalog

Rodrigo Flores-Allende , Léonard Seydoux , Éric Beaucé, Luis Fabian Bonilla , Philippe Gueguen, Claudio Satriano 

We re-examine the aftershock sequence of the Mw 8.8 Maule earthquake in south-central Chile to understand how seismicity, magnitude-frequency distribution, and fault structure vary along the rupture zone. Using the International Maule Aftershock Deployment (IMAD) dataset, we analyze ten months of continuous data from approximately 156 temporary stations and build a high-resolution aftershock catalog for the Maule rupture zone. We apply the BackProjection and Matched-Filtering (BPMF) workflow, which integrates a deep-learning phase picker with backprojection-based association, relative relocation, and template matching. We initially detect and relocate 130,575 earthquakes, then use a subset of high-quality events as templates to identify smaller earthquakes missed by initial detection. The final catalog contains 537,387 earthquakes, nearly 13 times more events than in previous studies, with a completeness magnitude of approximately Mw 1.8 and magnitudes ranging from Mw 0.2 to Mw 6.2. A local magnitude (ML) calibration provides a homogeneous magnitude scale across the network. The dense catalog reveals detailed seismotectonic features along the rupture. In the Pichilemu region, aftershocks delineate a shallow normal fault system with L-shaped geometry, whereas the Concepción area contains aseismic patches. Using the classical maximum likelihood and b-more-incomplete methods, we find that temporal b-values range between 1.2 and 1.6 early in the sequence and converge toward approximately 1.0. Meanwhile, b-values vary strongly along strike, with higher values in the north and lower values in the south. These contrasts are consistent with along-strike variations in effective stress and pore fluid pressure on the plate interface, in line with previous studies.