Anita Asgharnezhad
Unsupervised Clustering of Seismic Scattering Features for Microseismic Event Classification in the Bossea Cave (NW Italy).
Rel. Chiara Colombero, Lorena Di Toro. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Per L'Ambiente E Il Territorio, 2025
Abstract
Geophysical and geological explorations are critical for traditional resource extraction, geothermal energy production, carbon capture and storage, hydrogen storage, natural catastrophe forecasting and assessment, and research of the shallow Earth. Geophysical technologies enable scientists to investigate beneath the surface of the Earth without the need for excavation. Microseismicity is one of the most practical geophysical monitoring methods which provides information of various subsurface phenomena in high space resolution in real time. In this work, we first explore applications of these microseismic studies in different fields. These methods can be applied at different scales, from local to global and show widespread potential in climate change evaluation and monitoring, adaptation, and mitigation tasks.
Traditional microseismic analysis methods have limitations, and the dramatic increase in seismic data volume makes manual analysis increasingly challenging
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