This thesis advances the understanding of the high-enthalpy geothermal system of the Domo de San Pedro (DSP) volcanic complex in western Mexico. Located in the Trans-Mexican Volcanic Belt, DSP has been exploited for power generation since 2015. The study focuses on improving the conceptual model of DSP by identifying fluid-rich permeable zones within the geothermal reservoir and analyzing its seismic behavior in response to geothermal operations. Additionally, it explores precursory signals of large earthquakes in strike-slip fault systems using seismic ambient noise interferometry.
A dedicated broadband seismic network of 20 stations recorded continuous data from March 2021 to January 2022. Ambient noise seismology techniques were employed to retrieve surface waves sensitive to fluid presence, enabling the investigation of DSP’s subsurface structure. The new 3-D shear-wave velocity model, derived from Ambient Noise Tomography (ANT), resolves features down to 3.5 km depth, revealing a low-velocity region interpreted as the geothermal reservoir and a fractured, fluid-rich zone extending westward, suggesting potential for geothermal expansion.
Geothermal activity monitoring at DSP involved computing apparent velocity variations (dv/v) from ambient noise interferometry in the 0.1–1.5 Hz frequency band. These variations were compared with records of geothermal operations, revealing how fluid extraction and reinjection affect the seismic wavefield. Maps of dv/v were generated using noise-based imaging techniques, and a catalog of 217 local earthquakes was compiled and refined using a 1-D velocity model. Three distinct seismic activity periods along with seismic velocity transients were linked to changes in fluid reinjection and production rates and are attributed to pore pressure fluctuations.
Beyond ambient noise, the thesis also examines human-made tremor-like signals at DSP, similar to those found in volcanic and tectonic settings. These signals, occurring at 1–22 Hz with durations from hours to months, were tied to geothermal operations such as fluid extraction, wellbore maintenance, and pressure changes. Using a novel implementation of a network coherence method from volcanology, four distinct tremor families were classified and correlated with operational records, leading to conceptual models explaining their origins.
At a broader scale, the study investigates precursory signals of large earthquakes in regional strike-slip fault systems using seismic interferometry. Analysis of public datasets from seismic stations near major faults in California, Türkiye, and the Aegean Sea shows a consistent decrease in waveform coherence (up to 20%) several days before recent M > 6.5 earthquakes. This waveform decoherence is interpreted as a response to mechanical changes in the propagation medium, highlighting the potential of noise-based monitoring to complement existing seismic surveillance systems.
The concluding chapter remarks the significance of these findings for geothermal monitoring and broader seismological applications. The study establishes a framework for using seismic ambient noise to track geothermal field responses to industrial operations while also demonstrating its potential in detecting precursory signals of large earthquakes. These insights contribute to both geothermal resource management and seismic hazard assessment.
