Date of Award
2026-08-01
Degree Name
Doctor of Philosophy
Department
Geological Sciences
Advisor(s)
Aaron A. Velasco
Abstract
Modern seismic monitoring has been transformed by machine-learning methods that detect and locate earthquakes at scales manual analysis cannot reach. This dissertation develops, validates, and applies such workflows across three settings that span the range of modern monitoring problems: a major subduction-zone aftershock sequence, the tectonic questions that sequence can answer, and an urban region without any local monitoring at all. First, I construct a high-resolution catalog for the aftershock sequence of the September 8, 2017, Mw 8.2 Tehuantepec, Mexico earthquake, by integrating deep-learning phase detection with established location and relocation methods. The resulting catalog of 11,374 relocated earthquakes is the most complete for this sequence and the first to exploit the full rapid-response deployment. Second, I use that catalog, moment tensors, and a local tomographic study to analyze the sequence itself. The earthquake activated a three-level system: segmented extensional failure within the subducting slab, thrust faulting at the plate-interface zone whose slip parallels plate convergence, and a delayed, cluster-by-cluster activation of the overriding crust along an inherited basement contact. Third, I transfer the same detection framework to El Paso, Texas, building a community-hosted seismic network and automated pipeline that produced the region's first local earthquake catalog. Eight months of monitoring show that the region's detectable seismicity is almost entirely quarry blasting and establish a baseline for the East Franklin Mountains Fault before anticipated energy development alters the region. Together, these studies demonstrate that machine-learning monitoring workflows, carefully validated, yield reproducible catalogs whose resolution turns aftershock sequences into tectonic instruments and extends earthquake monitoring to communities that previously had none.
Language
en
Provenance
Received from ProQuest
Copyright Date
2026-08
File Size
170 p.
File Format
application/pdf
Rights Holder
Marc Adrian Garcia
Recommended Citation
Garcia, Marc Adrian, "Advancements In Modern Seismic Monitoring: Integrating Novel and Traditional Methods for Earthquake Detection, Characterization, and Structural Imaging" (2026). Open Access Theses & Dissertations. 4679.
https://scholarworks.utep.edu/open_etd/4679