Turning Data into Discovery: A platform to support mineral exploration in Kazakhstan & beyond

By leveraging machine learning workflows to integrate geophysical, geochemical, geological, and structural data with known mineralization measurements the likelihood of mineralization within a project area can be predicted. Input features can be tailored to deposit type, incorporating relevant geological factors such as proximity to structures or lineaments. This demonstration of our SmartSuiteTM platform highlights how complex geoscientific data can be transformed into clear insights for faster, smarter decisions, for companies with early-stage exploration prospects. The platform automatically generates insightful maps of prospectivity, lithology, geophysical clusters, providing valuable layers for targeting exercises across Kazakhstan and beyond.
This case study will focus on a data stack of gravity, magnetics, FDEM and radiometrics. By distilling data into a single layer, patterns are more recognizable and therefore the knowledge on the distribution of intrusions in the project area can be improved. With a combination of geophysical domain mapping, predictive lithology and mineral prospectivity analysis alongside support from expert geoscience specialists, the early exploration pipeline can be improved through spatial data integration & targeting. The value of such a platform is its ability to highlight potential extensions of known deposits and identify prospective areas in unexplored regions, prioritizing field campaigns and reducing exploration costs