Upgrading the Rock Geochemical Database of Finland and overview of the metallogenic provinces

Abstract. The Rock Geochemical Database (RGDB) compiled by the Geological Survey of Finland includes a wide range of metallic, non-metallic and geologically significant elements for 6544 rock samples taken from the bedrock throughout the whole Finland. Individual samples in the database are associated with one of the map units illustrated on the 1:1 000 000 scale bedrock map, also known as the DigiKP map. Based on the concentrations of different metallic elements and associated deposit types, several metallogenic areas were proposed. The main objectives of this thesis project were: 1) to find ambiguities in the assignment of the Rock Geochemical Database samples to the rock associations in the DigiKP map with the help of common geochemical classification diagrams, 2) to conduct statistical analysis of selected metallogenically important elements associated with different mineral deposit types, such as precious metal deposits (Au, Te, Pd), base metal deposits (Cu, Zn, Pb, Ni, Co), high-tech metals (Li, Nb, Sc, Ta, REE), ferrous metal (Fe, Cr, Ti, V), and energy-related metal deposits (Th, U), and finally 3) to prepare geochemical anomaly maps by ArcGIS utilising the statistical analysis and comparison of the geochemical anomaly maps with the current metallogenic areas. Correction of the rock association classification was applied to 166 samples in the database. The statistical analysis resulted in summary geochemical statistics for 120 rock associations, consisting mainly of mean, median, and standard deviation values of the selected elements, with the estimated median concentrations representing the background concentrations for all 120 rock associations. However, using the median values were unable to produce proper geochemical anomaly maps but this required normalisation of the background values with the raw concentrations. Several types of anomaly maps (single element and multi-element) were generated and tested against the current metallogenic areas. They reveal that many highly anomalous zones exist outside of the current metallogenic provinces for the studied elements. The statistical data originated during this project is a very potential tool. As different deposit types contain a common set of metals. The geochemical anomaly may represent not only a single type of deposit, but can also be linked to other deposit types to outline target areas. The prepared maps presented in this thesis are an example of the main mineralisation types of the selected elements. Preparing geochemical anomaly maps, including all potential deposit types within Finnish bedrock by utilising the generated database can provide new insights into using the normalised statistical dataset in search of metal deposits