首页|Predictive assessment of metallogenic signatures using the DataBase Querying (DBQ) method: A European application
Predictive assessment of metallogenic signatures using the DataBase Querying (DBQ) method: A European application
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
? 2022 The AuthorsAs 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 metallogenic-signature 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.
NSTL
Elsevier
