Predictive assessment of metallogenic signatures using the DataBase Querying (DBQ) method: A European application

As part of the European-Peruvian ION4RAW project (Horizon 2020 framework programme of the European
Commission), which aims at developing mineral-processing technology to recover selected by-products (e.g., Te,
Bi, Co, Re, Mo, Pt, Sb, Ge, Se, In) from primary Cu-Ag-Au deposits, we assessed a geographical inventory of
selected elements. However, not all elements of economic interest today have been systematically assayed and/or
studied in the past, and the existing European databases commonly are incomplete from a 2022 viewpoint. The
DataBase Querying (DBQ) geostatistical mineral prospectivity method helps address this gap between potential
mineral occurrences and ‘piecemeal’ historical inventories. In addition to a ‘classical’ application of the DBQ
method, we developed a new approach. This is based on the assessment of more global predictive metallogenicsignature
aspects (e.g., VMS, orogenic, epithermal), by clustering studied elements known to occur in various
metallogenic families, using ArcGIS software. Development of this method at a continental scale allowed identifying
several areas of great interest in Europe for exploration of the targeted by-products. It also helps in
assessing the favourability for the occurrence of commodities that are ‘by-products’ in their parageneses and that
were, until recently, rarely reported in geochemical studies.