Application of the stratigraphy-controlled geochemical data analysis in mineral prospective mapping in glaciated terrain

Till is a preferred geochemical sampling medium for mineral exploration in glaciated terrains due to its good indication of local or regional bedrock composition and secondary, down-ice transportation. However, the influence of till stratigraphy on the detection of subsurface mineral deposits remains rarely investigated. This is particularly important in areas having thick glaciogenic sedimentary cover with several glaciation phases. We demonstrate this complexity in Finnish Lapland, where the glacial sediment cover is thick and composed of several till units which represent separate glaciations during the Quaternary. The average glacial sediment drape thickness in Lapland is 5.5 m, although in places it can be several tens of meters. Two approaches were applied to study till stratigraphy based on the till geochemistry: a) a fixed depth interval method, and b) a statistical approach method. The fixed, one-meter depth interval method was used to divide till layers based on geochemical composition from the ground surface to the bedrock surface, while the statistical approach analyses changes in elemental content with depth by identifying optimal depth intervals in till geochemistry. Fuzzy overlay maps were generated for two study areas concerning different depth intervals identified by the described methodologies. Results indicate that the optimal depth range for detecting gold mineralization in the selected sub area 1 in Kittilä is 1.7–3.6 m, whereas the optimal depth for detecting orthomagmatic deposits in the selected sub area 2 in Akanvaara is 2.8–5.2 m. The statistical till depth profiling improves the predicted maps for specific mineral deposits compared to the fixed depth intervals, and it can enhance the reliability of mineral deposit detection during exploration in glaciated terrains. • Analysing legacy geochemical data sets from different times requires data cleaning and levelling. • Identifying optimal till depth improves the detection of targeted mineral deposits. • A statistical approach to detecting different till depth intervals is preferable. • Sampling density plays an important role in generating fuzzy overlay predicted maps.