TL;DR
A machine learning-assisted geophysical–geotechnical framework that integrates Electrical Resistivity Tomography, Seismic Refraction Tomography, and borehole-derived Standard Penetration Test data to improve subsurface characterization and engineering site assessment is presented.
The presence of near-surface cavities poses a significant geohazard due to potential ground subsidence and structural collapse. To mitigate threats to urban stability, this study presents an integrated geophysical framework to locate and characterize abandoned mining galleries and exploitation voids near Linares (Jaén,...
Accurate delineation of gold mineralization in deeply weathered tropical terrains requires the integration of indirect geophysical data with direct subsurface observations. Electrical resistivity imaging (ERI) and induced polarization (IP) are widely used in mineral exploration; however, interpretation is often limited...
Accurate prediction of reservoir properties such as porosity, permeability, and lithofacies distribution is essential for reliable hydrocarbon reserve estimation, well placement, and field development planning. Conventional deterministic methods for relating seismic response to reservoir properties are limited by the n...
Earthquake-induced landslides and liquefaction often occur within the same seismic event but may be controlled by different combinations of ground shaking, topography, hydrology, site conditions, and tectonic setting. This study develops an interpretable remote-sensing framework to map and compare these secondary hazar...
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