Geological Mapping
High-resolution mapping of lithology, faults, folds, and geological formations using AI-driven feature recognition and satellite imagery analysis. Advanced computer vision techniques and satellite embedding models enable precise interpretation of complex geological structures from multispectral and hyperspectral satellite data.
Geophysical Data Processing and Inversion
Automated processing of gravity, magnetic, and ambient noise data with advanced filtering techniques and 3D inversion modeling to detect subsurface anomalies and mineral deposits with enhanced sensitivity and accuracy.
Spatial Prospectivity Mapping
AI-powered identification and prioritization of prospective mineral zones integrating geophysical, geochemical, and remote sensing data. Uses Random Forest and positive-unlabeled learning to reduce exploration search space by up to 90%. Leverages Generative AI methods to handle sparse mineral exploration data for robust insights.
Spatiotemporal Mineral Prospectivity
Revolutionary deep-time mineral prospectivity analysis reconstructing geological processes over millions of years using plate tectonic models, paleotopography, and geodynamic simulations. Integrates Explainable AI for transparent, interpretable results that bridge technical innovation with practical field insights.