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AI-Powered Seismic Tomography Reveals Two Magma Reservoirs Beneath Popocatépetl

Using six years of CENAPRED seismic records, UNAM scientists trained machine-learning models to build higher-resolution images of Popocatépetl’s interior.

Overview

  • The images locate two reservoirs to roughly 10 km depth and indicate about 70% crystallized rock that can intermittently reheat and mobilize, and the model spans depths equivalent to about 30 km below sea level.
  • The deepest proposed chamber was not resolved, with researchers pursuing wave-attenuation analyses and complementary monitoring to probe it.
  • The tomography leveraged CENAPRED seismic records from January 2019 through December 2024, delivering higher resolution than earlier models.
  • A machine-learning workflow automatically detected and classified volcanic tremor to improve phase picking and event catalogs, according to Karina Bernal Manzanilla and Marco Calò.
  • Results are documented in the Journal of Volcanology and Geothermal Research, with a related paper under review at the Journal of South American Earth Sciences.