Authors / CoAuthors
Skirrow, R.G. | Murr, J. | Schofield, A. | Huston, D.L. | van der Wielen, S.E. | Czarnota, K | Coghlan, R.A. | Highet, L.M. | Connolly, D.P. | Doublier, M.P. | Duan, J.
Abstract
<p>Iron oxide copper-gold (IOCG) deposits are consequences of lithospheric- to deposit-scale earth processes, and form where there was a coincidence of ore-forming processes in space and time. Building on previous conceptualisations we view a ‘mineral system’ as an ore-forming geological system in which four components are required to have operated efficiently and coincidentally, namely: (1) available sources of ore metals (i.e., copper, gold, uranium, rareearth elements) and hydrothermal fluids; (2) energy sources to drive fluids in the ore-forming system; (3) active crustal and mantle lithospheric architecture, representing hydrothermal fluid and/or magma flow pathways; and (4) physico-chemical gradients along which ore metals were deposited to form ore bodies. <p>This holistic multi-scale mineral systems framework has been used to develop a practical, knowledge-based yet data-rich, prospectivity mapping method applicable at regional to continental scales for hydrothermal and orthomagmatic ore-forming systems. We demonstrate how the mineral system components can be translated into mappable criteria and show how maps of mineral potential are generated by integrating diverse and rich input data sets. The method enables prediction of mineral potential not only in brownfields areas but also in greenfields and covered terranes with no previously known mineralisation. Here we report the application of this methodology in regional-scale mapping of the potential for iron oxide Cu-Au (IOCG) deposits in Australia, using examples from five studies over the last decade in northern Queensland, eastern South Australia, and southern and central-eastern Northern Territory. Uncertainties in the results arising from assignment of weightings to input data layers were investigated by the application of Monte Carlo-type probabilistic simulations. The results of 500 iterations using randomly assigned weightings overall support the deterministic results but also show that modelled prospectivity is controlled mainly by variations in intrinsic values of the input geoscientific data sets (e.g. highs and lows of gravity values) rather than by the weightings. <p>The results of the knowledge-driven data-rich analyses of IOCG potential have been validated against known IOCG deposits (not used directly in the analysis). We find in all five studies (Queensland, South Australia and Northern Territory) a good spatial correspondence, with few exceptions. Statistical analysis of prospectivity mapping results from the Tennant Creek – Mt Isa study area demonstrate that 15 of 16 IOCG deposits occur in the highest modelled prospectivity areas within 4.2% of the study area, representing an area reduction of 95.8%. Moreover, several new discoveries of Cu-Au mineralisation have been made within areas previously highlighted as highly prospective. This success and validation support the utility of Geoscience Australia’s approach as a decision-support tool to assist exploration companies and governments in cratonto regional-scale area selection for discovery of IOCG and other mineral systems.
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document dataset
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130251
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Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
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- theme.ANZRC Fields of Research.rdf
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- EARTH SCIENCES
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- mineral deposits
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- iron oxide copper-gold deposits
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- mineral potential
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- mineral systems
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- australia
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- prospectivity mapping
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- Published_External
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2019-07-16T00:54:12
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