Advanced Geostatistical and AI Workflows for Data-Driven Critical Mineral Prospectivity Mapping in Alberta

The project proposes to use AI-driven geostatistical models to help identify areas that may contain key minerals for future sampling and verification efforts.

Researchers at the University of Alberta aim to develop an integrated, artificial intelligence-driven geostatistical framework using advanced machine learning to model complex spatial patterns, combine diverse Earth datasets, transfer knowledge to data poor regions, and quantify prediction uncertainty to develop probably critical mineral maps for Alberta. The project will use existing geophysical, geochemical, hyperspectral, and remote-sensing datasets to inform the model and will be cross-validated against existing data and maps provided by the Alberta Geological Survey. Deliverables include reproducible workflows, probabilistic 2D and 3D maps, and interactive web-based layers.