Group A, Poster #011, Seismology
Machine-Learning catalog for the California-Baja California, Mexico, border region
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Poster Presentation
2022 SCEC Annual Meeting, Poster #011, SCEC Contribution #12045 VIEW PDF
a to the Southern California Seismic Network (SCSN). The yearly-based analysis consisted of applying the deep learning techniques of the PhaseLink system to identify P- and S-arrivals and their association to the combined database. The location was done with Non-Linear Location and relocated with HypoDD. Due to large crustal velocity and thickness variations, the relocation process was separated into two areas: the Mexicali Valley and the Peninsular Rages of Baja California (PRBC), using the appropriate velocity model for each region. Our catalog generally has 2-3 times more events than those reported by RESNOM. For the Mexicali Valley region, profiles of seismic alignments show more constrained seismicity (between ~5 to ~10 km depth) when comparing them with the SCSN and RESNOM catalogs. This is especially notable in the Indiviso, Dixieland, and Laguna Salada-Indiviso faults. Three seismicity profiles for the PRBC region also show better constraints than the RESNOM catalog (the SCEC catalog is unavailable for this region). Having a precise-hypocenter complete catalog and the analyzed seismicity profiles for the California's border region will allow us to improve and expand the active fault geometries to be included in the Community Fault Model.
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