The Mineral Potential web service provides access to digital datasets used in the assessment of mineral potential in Australia. The service includes maps showing the potential for sediment-hosted base metal mineral systems in Australia.

The Mineral Potential web service provides access to digital datasets used in the assessment of mineral potential in Australia. The service includes maps showing the potential for sediment-hosted base metal mineral systems in Australia.

Magnetotelluric (MT) data allow geoscientists to investigate the link between mineralisation and lithospheric-scale features and processes. In particular, the highly conductive structures imaged by MT data appear to map the pathways of large-scale palaeo-fluid migration, which is an important element of several mineral systems. New data were collected as part of the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) under Geoscience Australia Exploring for the Future (EFTF) program in northern Australian. We use this dataset to demonstrate that the MT method is a valuable tool for mapping lithospheric-scale features and for selecting prospective areas for mineral exploration. Our results image a number of major conductive structures at depths up to ~200 km or deeper in the survey region, for example, the Carpentaria Conductivity Anomaly in east of Mount Isa; and the Tanami Conductive Anomaly along the Willowra Suture Zone. These significant anomalies are lithospheric- scale highly conductive structures, and show spatial correlations with major suture zones and known mineral deposits. These results provide important first-order information for lithospheric architecture and possible large footprint of mineral systems. Large-scale crustal/mantle conductivity anomalies mapping fluid pathways associated with major sutures/faults may have implications for mineral potential. These results provide evidence that some mineralisation occurs at the gradient of or over highly conductive structures at lower crustal and lithospheric mantle depths. These observations provide a powerful means of highlighting greenfields for mineral exploration in under-explored and covered regions.

<div><strong>Output type:</strong> Exploring for the Future Extended Abstract</div><div><br></div><div><strong>Short abstract: </strong>Iron oxide copper-gold (IOCG) deposits are a significant source of copper and gold and can also contain critical minerals that are required for the transition to a low carbon economy and to increase Australia’s security of mineral supply. Given their strategic importance, a national-scale assessment of the mineral potential for IOCG mineral systems in Australia has been undertaken using a hybrid data- and knowledge-driven approach. The national-scale assessment includes the evaluation of the statistical importance of mappable criteria used in previously published regional-scale IOCG models, resulting in the removal of five criteria and the inclusion of four new or revised criteria derived from datasets developed through the Exploring for the Future program. The new mineral potential model successfully predicts the location of 91.7% of known IOCG deposits and occurrences in 8.3% of the area, reducing the exploration search space by 91.7% and highlighting new areas of elevated prospectivity in under-explored regions of Australia. When compared to existing regional-scale mineral potential assessments for IOCG mineral systems published by Geoscience Australia, the new national-scale model demonstrates higher prospectivity in areas with known IOCG deposits and occurrences, while also highlighting new prospective areas for IOCG mineral systems. Areas with assessed high prospectivity but lacking known IOCG mineralisation include parts of the Curnamona, Etheridge and Musgrave provinces, and the Delamerian, Halls Creek and Tanami orogens.</div> <div><strong>Citation</strong>: Cloutier J., et al., 2024. First national mineral system assessment of Australia's iron oxide copper-gold potential. In: Czarnota, K. (ed.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, https://doi.org/10.26186/149357</div>

<div>Mineral exploration and development involves the selection of potential projects which must be evaluated across disparate characteristics. However, the distinct metrics involved are typically difficult to reconcile (e.g. geological potential, environmental impact, jobs created, value generated, etc.). Separate stakeholders—with different goals and attitudes—will reasonably differ in their preferences as to which categories to prioritize and how much weight to give to each. These conflicting preferences can obscure optimal outcomes and confound project selection.</div><div><br></div><div>In this presentation, we will discuss how early-stage exploration decisions can be treated as multi-criteria optimization problems. We show how this approach can be used to effectively evaluate and communicate competing criteria, and locate regions that perform best under a range of different metrics. We then outline a mapping framework that identifies regions that perform best in terms of geological potential, economic value and environmental impact and demonstrate this approach in a real-word example that highlights new exploration targets in the Australian context. Abstract presented at the American Geophysical Union (AGU) Fall Meeting 2023 (AGU23) https://www.agu.org/fall-meeting

The Mineral Potential web service provides access to digital datasets used in the assessment of mineral potential in Australia. The service includes maps showing the potential for sediment-hosted base metal mineral systems in Australia.

<div>Maps showing the potential for iron oxide copper-gold (IOCG) mineral systems in Australia. Each of the mineral potential maps is a synthesis of four component layers (source of metals, fluids and ligands; energy sources and fluid flow drivers; fluid flow pathways and architecture; and ore depositional gradients). The model uses a hybrid data-driven and knowledge driven methodology to produce the final mineral potential map for the mineral system. An uncertainty map is provided in conjunction with the mineral potential maps that represents the availability of data coverage over Australia for the selected combination of input maps. Uncertainty values range between 0 and 1, with higher uncertainty values being located in areas where more input maps are missing data or have unknown values. The input maps and mineral deposits and occurrences used to generate the mineral potential map are provided along with an assessment criteria table which contains information on the map creation.</div>

Maps showing the potential for sediment-hosted base metal mineral systems in Australia. Each of the mineral potential maps is a synthesis of four component layers: sources of metals, energy drivers, lithospheric architecture, and depositional gradients, using a weighted sum to produce the final mineral potential map for the mineral system. Uncertainty maps are provided in conjunction with each of the mineral potential maps that represent the availability of data coverage over Australia for the selected combination of input maps. Uncertainty values range between 0 and 1, with higher uncertainty values being located in areas where more input maps are missing data or have unknown values. The set of input maps used to generate the mineral potential maps is provided along with an assessment criteria table that contains information on the map creation.

<div>Sediment-hosted copper (Cu) mineral systems are important sources of base metals and critical minerals such as cobalt that are vital to delivering Australia’s low-carbon economy. In Australia, sediment-hosted Cu resources account for ~11% of the total Cu resources. Given their significance to the Australian economy, national-scale mineral potential models for sediment-hosted Cu have been developed. In addition to the potential for sediment-hosted Cu mineralisation, the uncertainty related to data availability has been examined. Three mineral potential</div><div>models derived from the combination of two mineral systems have been derived from a large volume of precompetitive geoscience data combined with mineral systems expertise, each using a different combination of input maps to assess the influence of incomplete data on the results. The mineral potential models successfully predict the location of major sediment-hosted stratiform Cu and Mount Isa-type Cu deposits while highlighting new areas of elevated prospectivity in under-explored regions of Australia, reducing the exploration search space</div><div>by up to ~84%.</div>

<div>Mineral prospectivity studies seek to map evidence of mineral system activity, with the aim of informing mineral exploration decisions and guiding exploration in the face of uncertainty. These studies leverage the growing volumes of information that are available to characterise the lithosphere by compiling covariate (or feature) grids that represent key mineral system ingredients. Previous studies have been categorised as either “knowledge-driven” or “data-driven” approaches depending on whether these grids are integrated via expert elicitation or by the empirical relationship to known mineralisation, respectively. However, to our knowledge, the underlying modelling framework and assumptions have not been systematically reviewed to understand how choices in the approach to the problem influence modelling outcomes. Here we show the broad mathematical equivalence in these approaches and highlight the limitations inherent when optimising to minimise misfit in potentially under-determined problems. We argue that advances in mineral prospectivity are more likely to be driven by careful consideration of the model selection problem. Focusing effort on model selection will not only drive more robust mineral prospectivity predictions but may also simultaneously refine our understanding of key mineral system processes. To build on these results, we present the Mineral Potential Toolkit; a software repository to facilitate feature engineering, statistical appraisal, and quantitative prospectivity modelling. The toolkit enables a novel approach that combines the best aspects of previous methods. Abstract presented to the 26th World Mining Congress 2023 (https://wmc2023.org/)