207 6. The use of passive seismic methods for Geothermal exploration and monitoring As in many geophysical exploration strategies, it is rarely one method that brings in the open useful information, but rather a multi-physics approach where complementary data and models are compared or even inferred simultaneously, so that different information converge toward the most logical interpretation. From that perspective, passive seismic methods are a relevant tool within the geothermal exploration toolbox. In general, the most utilized strategies to detect and characterize geothermal targets are based on electromagnetic methods (Muñoz, 2014) as geothermal reservoirs display clear conductive signature. Nevertheless, seismic properties can also highlight similar geological features (Toledo et al., 2022) driven by the presence of water- filled fractures which tend to decrease seismic velocity and increase seismic attenuation. Joint interpretation of passive seismic with other geophysical methods is usually highly valuable. Several approaches can be adopted, we provide below a non-exhaustive list of those methodologies along with a few literature examples: • Workflow integration: Exploration workflows can benefit from dedicated multiphysics workflow such as “Play and Fairway analysis” (Craig et al., 2021) where ANSI-based Vs tomography brings insight on the elastic structures of the investigated area allowing to characterize complex geothermal context. • Statistical integration: Models obtained from multiphysics imaging methods are always the resulting complex combination of geophysical responses of the heterogeneous subsurface (e.g. faults, layers, fluids, petrophysics, lithology etc.). Statistical integration approaches aim to highlight and isolate specific geological targets that can affect differently the geophysical responses of various geophysical methods (e.g. Ars et al., 2024; Muñoz et al., 2010; Bauer et al., 2012). • Constrained inversion: Going beyond the “simple” co-interpretation of Vs velocity models in parallel to other geophysical models, one can also use a constrained inversion approach where ambient noise tomography is proceeded under the constrain of a 3D resolved pre-obtained model describing the distribution of other physical parameters such as resistivity (Ars et al., 2024). • Joint inversion: In this case, the geophysical inversion process itself is parametrized to find the best fitting models under the constraint of a given relationship coupling the physical model properties. A typical example in geothermal exploration context of such an approach is the joint inversion of ANSI-based surface wave dataset with gravimetric dataset. Both physical fields are sensitive to elastic properties of the underground, and the joint inversion process results in an improved resolution of both geophysical models (e.g. Carillo et al., 2024; Ars et al. 2024). • Perspectives: So far, ANSI based tomography methods have been focused on deriving Vs models of the subsurface. However, recent developments have highlighted to possibility to also derive 3D seismic attenuation models from the ambient seismic signal (e.g. Soergel et al., 2020; Cabrera-Perez et al., 2024). Such evolution may lead to future co-processing of seismic and resistivity datasets for better imaging of attenuation and conductive structures, since they both exhibit high sensitivity to the presence of fluids.
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