Predicting gold-rich epithermal and porphyry systems in the central Andes with a continental-scale metallogenic GIS

BRGM's GIS Andes, a comprehensive continental-scale metallogenic information system for the entire Andes Cordillera, is based on original syntheses structured into thematic layers. The aim of developing the GIS was to produce an integrated tool to understand ore deposit localization in the Andes. A fundamental question arising at the outset was whether the tool would be suitable for producing predictive mineral-resource maps at the continental scale, considering that previous predictive studies focus only on the regional scale. The continental-scale synthesis implied working with heterogeneous data in terms of distribution, quantity, quality, and in particular, accuracy. The benefit is the ability to include uncommon parameters linked to the geodynamic evolution of the active margin and significant only at the continental scale. In view of the particularities of the GIS dataset, an "expert-guided data-driven" approach was adopted for the multicriteria processing; an approach that combined expert knowledge and the use of elementary statistics, allowing to provide a link between the tectonic development of the whole Andean margin and the spatial and temporal distribution of individual mining districts. This study was purposely restricted to assessing the distribution of Neogene gold in the central Andes between lat. 3degrees and 33degreesS, thus (a) incorporating well constrained data on the present morphology of the convergent margin, and (b) avoiding ambiguities in the less well constrained older history of the complex evolution of the Andean margin. Five regional parameters were selected and were considered to have a significant influence on the Neogene magmatic-hydrothermal ore formation at continental scale. The five parameters: (i) host-rock lithostratigraphy, (ii) lithostratigraphic contacts, (iii) structural discontinuities, and (iv) depth and (v) dip of the Wadati-Benioff zone modeled from seismic data, had assigned favorability scores, from 0 to 2, based on their associated metal content with respect to a set of identified Neogene gold deposits. The next step was to calculate favorability maps for each criterion that were combined to create an overall (cumulative) favorability map or predictive gold map. Verifying the predictive map against known gold deposits, it was found that the cumulative favorability score of greater than or equal to4 (out of 10 maximum) located about two-thirds of the known gold-bearing epithermal and porphyry deposits and 95% of the metal content; a cumulative favorability score of greater than or equal to5 reduced these figures to 50% of the deposits and 71% of the metal content, and that of greater than or equal to6 relocated 24% of the deposits and 51% of the metal content. In addition to verifying the method, the predictive map outlines new potentially favorable gold areas and even indicates that some known districts could well host yet undiscovered mineralization. (C) 2004 Published by Elsevier B.V.