Part I: A resource estimation based on mineral system modelling prospectivity approaches and analogical analysis: A case study of the MVT Pb-Zn deposits in Huayuan district, China
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Several techniques have been proposed to predict undiscovered mineral resources at the regional scale by integrating multiple spatial datasets and mineral deposit models using Geographical Information Systems (GIS). An unresolved issue, however, is that predictive proxies are two-dimensional GIS layers at a regional scale, whereas mineralising processes occur in four dimensions (i.e., space and time). In the past 10 years, mineral system modelling approaches have been proposed and developed for the critical doubt that are described in terms of two characteristics: spatial scales and relevant geochemical processes. This paper demonstrates the modelling and combination of multiple scales based on mineral system prospectivity analysis and then present a resource estimation method that involves the calculation of three variables. In applying a GIS-based approach to a mineral system, we compared the resource estimation in a trap on the district scale to the extrapolation of reserve estimations of representative deposits in the same mineral system. The procedure used for the implementation of this method includes: (i) the incorporation of a descriptive model based on the mineral deposit type; (ii) the digitalization of the favourable characteristics of the type of investigated deposit; (iii) the implementation of the mineral system theory (approach) to pinpoint the locations of potential structural or stratigraphic traps at the district scale using GIS-based two-dimensional prospectivity mapping; (iv) the calculation of similarities and ore-bearing ratios; (v) the restructuring of models of favourable features at multiple scales (i.e., district and ore deposit scales); and (vi) the assessment of undiscovered mineral resources in traps. This method was used to estimate MVT-type Pb-Zn mineralisation in a promising potential region in northwestern Hunan Province, China. In addition, this study is divided into two parts, and this paper mainly describes the methodology.
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