Towards hyperspectral exploration vectors in the Central European Kupferschiefer district

Europe holds significant potential for crucial metals essential for renewable energy and digital advancements. However, there is a need for a deeper understanding of the European subsurface, coupled with a requirement to reduce the environmental impact of exploration activities. We employ hyperspectral scanning of legacy drill cores to develop innovative indicators of mineralization in the Central European Kupferschiefer district, home to Europe's largest copper and silver resources. Hyperspectral imaging, capturing spectral reflectance and emission across numerous spectral bands, allows for non-invasive, high-resolution mineral mapping of drill cores. Initial findings showcased the technique's ability to identify critical redox boundaries and alteration minerals, aiding ore deposit characterization. In the framework of two research projects, we scanned 2400 meters of drill core from 87 boreholes across the Spremberg–Graustein Kupferschiefer deposit in Germany. For data acquisition, we deployed a drill-core scanner with a full suite of hyperspectral sensors covering the visible and near-infrared (400 to 970 nm), shortwave (970 to 2500 nm), mid-wave (2700 to 5300 nm), and longwave infrared (7700 to 12300 nm) ranges. The collected data were processed through a novel, open-source software pipeline, which enables i) real-time correction, processing, and analysis, ii) efficient data management and storage, and iii) comprehensive visualization and integrative interpretation of the hyperspectral drill core data. We upscaled mineral abundances across all of the scanned drill cores using a supervised learning model trained on quantitative mineralogical data from select samples. Initial analyses, particularly the visual alignment of hyperspectral derivatives at the base of the Kupferschiefer marker horizon, indicate geographical patterns in dolomite content and correlations between carbonate, clay, and mica compositions and copper grade. The hyperspectral data will eventually be integrated with geological, geophysical, and geochemical constraints to create accurate 3D subsurface and 4D mineral system models, aimed at enhancing our understanding of geological processes and resource management strategies in similar geological settings worldwide.

 

Acknowledgements: This research has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement nº 101058483 (VECTOR), and from the Geological Survey of Saxony (Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie, LfULG) under agreement nº 4-0912014LFULG01-88.