From predictive mapping of mineral prospectivity to quantitative estimation of number of undiscovered prospects

Carranza, Emmanuel J.M. (2010) From predictive mapping of mineral prospectivity to quantitative estimation of number of undiscovered prospects. Resource Geology, 61 (1). pp. 30-51.

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Abstract

This paper proposes that the spatial pattern of known prospects of the deposit-type sought is the key to link predictive mapping of mineral prospectivity (PMMP) and quantitative mineral resource assessment (QMRA). This proposition is demonstrated by PMMP for hydrothermal Au-Cu deposits (HACD) and by estimating the number of undiscovered prospects for HACD in Catanduanes Island (Philippines). The results of analyses of the spatial pattern of known prospects of HACD and their spatial associations with geological features are consistent with existing knowledge of geological controls on hydrothermal Au-Cu mineralization in the island and elsewhere, and are used to define spatial recognition criteria of regional-scale prospectivity for HACD. Integration of layers of evidence representing the spatial recognition criteria of prospectivity via application of data-driven evidential belief functions results in a map of prospective areas occupying 20% of the island with fitting- and prediction-rates of 76% and 70%, respectively. The predictive map of prospective areas and a proxy measure for degrees of exploration based on the spatial pattern of known prospects of HACD were used in one-level prediction of undiscovered mineral endowment, which yielded estimates of 79 to 112 undiscovered prospects of HACD. Application of radial-density fractal analysis of the spatial pattern of known prospects of HACD results in an estimate of 113 undiscovered prospects of HACD. Thus, the results of the study support the proposition that PMMP can be a part of QMRA if the spatial pattern of discovered prospects of the deposit-type sought is considered in both PMMP and QMRA.

Item ID: 27348
Item Type: Article (Research - C1)
ISSN: 1751-3928
Keywords: evidential belief functions; fractal analysis; Fry analysis; GIS; hydrothermal Au-Cu; mineralization controls; spatial association analysis
Date Deposited: 07 Jun 2013 02:16
FoR Codes: 04 EARTH SCIENCES > 0403 Geology > 040399 Geology not elsewhere classified @ 50%
01 MATHEMATICAL SCIENCES > 0103 Numerical and Computational Mathematics > 010399 Numerical and Computational Mathematics not elsewhere classified @ 50%
SEO Codes: 84 MINERAL RESOURCES (excl. Energy Resources) > 8401 Mineral Exploration > 840199 Mineral Exploration not elsewhere classified @ 100%
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