Derivation of Predictive Layers Using Regional Till Geochemistry Data for Mineral Potential Mapping of the REE Line of Bergslagen, Central Sweden

With the increasing need for rare-earth elements (REEs) to reach the goals of the ongoing green energy transition, new and innovative methods are needed to identify new primary resources of these critical metals. This study explores the potential to use a non-biased, uniform till dataset to generate evidentiary layers that describe these critical factors and geochemical anomalies to aid mineral potential mapping (MPM) for REEs using machine-assisted methods. The till samples used in this study were collected from the “REE Line”, a sub-region within the Bergslagen lithotectonic province, Sweden, where numerous REE mineralizations occur. Multiple approaches were used in this study to isolate geochemical anomalies using multivariate methods, namely principal component analysis (PCA) and K-means clustering. Additional factors for classifying till samples were also tested, including alteration indices. Using known REE occurrences in Bergslagen as validation points, the results demonstrated the usefulness of multivariate methods applied to till geochemistry for predictive bedrock mapping, and to identify potential areas of REE mineralization within the REE line. The results of the alteration indices showed that the till geochemistry demonstrated similar levels of alteration when compared to the underlying bedrock, allowing for a regional alteration map to be generated. These results show that regional-scale till sampling can provide low-cost data for mineral exploration at the regional scale and generate usable evidentiary layers for GIS-based MPM.