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  • <div>Heavy minerals (HMs) are those with a specific gravity greater than 2.9 g/cc (e.g., anatase, zircon). They have been used successfully in mineral exploration programs outside Australia for decades [1 and refs therein]. Individual HMs and combinations, or co-occurrence, of HMs can be characteristic of lithology, degree of metamorphism, alteration, weathering or even mineralisation. These are termed indicator minerals, and have been used in exploration for gold, diamonds, mineral sands, nickel-copper, platinum group elements, volcanogenic massive sulfides, non-sulfide zinc, porphyry copper-molybdenum, uranium, tin-tungsten, and rare earth elements mineralization. Although there are proprietary HM sample assets held by industry in Australia, no extensive public-domain dataset of the natural distribution of HMs across the continent currently exists.</div><div> We describe a vision for a national-scale heavy mineral (HM) map generated through automated mineralogical identification and quantification of HMs contained in floodplain sediments from large catchments covering most of Australia [1]. These samples were collected as part of the National Geochemical Survey of Australia (NGSA; www.ga.gov.au/ngsa) and are archived in Geoscience Australia’s rock store. The composition of the sediments can be assumed to reflect the dominant rock and soil types within each catchment (and potentially those upstream), with the generally resistant HMs largely preserving the mineralogical fingerprint of their host protoliths through the weathering-transport-deposition cycle. </div><div> Underpinning this vision is a pilot project, focusing on a subset of NGSA to demonstrate the feasibility of the larger, national-scale project. Ten NGSA sediment samples were selected and both bulk and HM fractions were analysed for quantitative mineralogy using a Tescan® Integrated Mineral Analyzer (TIMA) at the John de Laeter Centre, Curtin University (Figure 1). Given the large and complex nature of the resultant HM dataset, we built a bespoke, cloud-based mineral network analysis (MNA) tool to visualise, explore and discover relationships between HMs, as well as between them and geological setting or mineral deposits. The pilot project affirmed our expectations that a rich and diverse mineralogical ecosystem will be revealed by expanding HM mapping to the continental scale. </div><div> A first partial data release in 2022 was the first milestone of the Heavy Mineral Map of Australia (HMMA) project. The area concerned is the Darling-Curnamona-Delamerian region of southeastern Australia, where the richly endowed Broken Hill mineral province lies. Here, we identified over 140 heavy minerals from 29 million individual mineral observations in 223 sediment samples. Using the MNA tool, one can quickly identify interesting base metal mineral associations and their spatial distributions (Figure 2).</div><div> We envisage that the Heavy Mineral Map of Australia and the MNA tool will contribute significantly to mineral prospectivity analysis and modelling in Australia, particularly for technology critical elements and their host minerals, which are central to the global economy transitioning to a more sustainable, decarbonised paradigm.</div><div><br></div>Figure 1. Distribution map of ten selected heavy minerals in the heavy mineral fractions of the ten NGSA pilot samples (pie charts), overlain on Australia’s geological regions (variable colors) [2]). Map projection: Albers equal area.</div><div><br></div><div>Figure 2. Graphical user interface for the Geoscience Australia MNA cloud-based visualization tool for the DCD project (https://geoscienceaustralia.shinyapps.io/HMMA-MNA/) showing the network for Zn minerals with the gahnite subnetwork highlighted (left) and the map of gahnite distribution (right).</div><div> <strong>References</strong></div><div>[1] Caritat et al., 2022, Minerals, 12(8), 961. https://doi.org/10.3390/min12080961 </div><div>[2] Blake &amp; Kilgour, 1998, Geosci Aust. https://pid.geoscience.gov.au/dataset/ga/32366 </div><div><br></div>This Abstract was submitted/presented to the 2022 Mineral Prospectivity and Exploration Targeting (MinProXT 2022) webinar, Freiburg, Germany, 01 - 03 November (www.minproxt.com)

  • <div>The Heavy Mineral Map of Australia (HMMA) project1, part of Geoscience Australia’s Exploring for the Future program, determined the abundance and distribution of heavy minerals (HMs; specific gravity >2.9 g/cm3) in 1315 floodplain sediment samples obtained from Geoscience Australia’s National Geochemical Survey of Australia (NGSA) project2. Archived NGSA samples from floodplain landforms were sub-sampled with the 75-430 µm fraction subjected to dense media separation and automated mineralogy assay using a TESCAN Integrated Mineral Analysis (TIMA) instrument at Curtin University.</div><div><br></div><div>Interpretation of the massive number of mineral observations generated during the project (~150&nbsp;million mineral observations; 166 unique mineral species) required the development of a novel workflow to allow end users to discover, visualise and interpret mineral co-occurrence and spatial relationships. Mineral Network Analysis (MNA) has been shown to be a dynamic and quantitative tool capable of revealing and visualizing complex patterns of abundance, diversity and distribution in large mineralogical data sets3. To facilitate the application of MNA for the interpretation of the HMMA dataset and efficient communication of the project results, we have developed a Mineral Network Analysis for Heavy Minerals (MNA4HM) web application utilising the ‘Shiny’ platform and R package. The MNA4HM application is used to reveal (1) the abundance and co-occurrences of heavy minerals, (2) their spatial distributions, and (3) their relations to first-order geological and geomorphological features. The latter include geological provinces, mineral deposits, topography and major river basins. Visualisation of the mineral network guides parsimonious yet meaningful mapping of minerals typomorphic of particular geological environments or mineral systems. The mineralogical dataset can be filtered or styled based on mineral attributes (e.g., simplified mineralogical classes) and properties (e.g., chemical composition).</div><div><br></div><div>In this talk we will demonstrate an optimised MNA4HM workflow (identification à mapping à interpretation) for exploration targeting selected critical minerals important for the transition to a lower carbon global economy. </div><div><br></div><div>The MNA4HM application is hosted at https://geoscienceaustralia.shinyapps.io/mna4hm and is available for use by the geological community and general public.</div> This Abstract was submitted and presented to the 2023 Goldschmidt Conference Lyon, France (https://conf.goldschmidt.info/goldschmidt/2023/meetingapp.cgi)