The Australian Resource Reviews are periodic national assessments of individual mineral commodities. The reviews include evaluations of short-term and long-term trends for each mineral resource, world rankings, production data, significant exploration results and an overview of mining industry developments.

<div>High Purity Silica (HPS) is the principal raw material in the production of silicon used to manufacture high technology products including semiconductors and solar cells. Quartz (SiO2) is the most abundant silica mineral in the Earth’s crust; however, economic deposits of high purity quartz (HPQ; SiO2 >99.995%) are rare. Rapid acceleration towards reaching net zero emissions has seen a parallel increase in demand for the discovery of new HPQ deposits for downstream processing. As a part of the Australian Critical Minerals Research and Development Hub, Geoscience Australia is addressing this demand by generating the first mineral systems model and accompanying national scale mineral potential map to help explorers accelerate discovery. Two new mineral systems models are being developed for i) all pegmatite types and, ii) metamorphically-derived hydrothermal quartz veins. The two mineral systems are combined into key components, including geodynamic and geological setting, geodynamic drivers and fluid drivers. Each of the components have been subsequently converted into discrete mappable layers as part of the GIS-based process of generating a combined national mineral prospectivity map for deposit- scale accumulations of silica and quartz. A new, first generation, mineral prospectivity map has been developed for the combined pegmatite and hydrothermal quartz mineral system and, has already highlighted the massive potential in Australia for hosting both types of HPS occurrences at economically viable scales. The mineral potential map has already been used to define a suite of sample locations in which to help define the best source for HPS. Further, we are undertaking the first national scale sampling and analytical geochemistry campaign to examine the impact of mineral systems on quartz purity and develop the Explorers’ Toolbox - an industry applicable, best practice guideline for the characterisation of potential HPS deposits in Australia. Presented at the 2024 AusIMM Critical Minerals Conference

This web service delivers data from an aggregation of sources, including several Geoscience Australia databases (provinces (PROVS), mineral resources (OZMIN), energy systems (AERA, ENERGY_SYSTEMS) and water (HYDROGEOLOGY). Information is grouped based on a modified version of the Australian Bureau of Statistics (ABS) 2021 Indigenous Regions (IREG). Data covers population centres, top industries, a regional summary, groundwater resources and uses, energy production and potential across six sources and two energy storage options. Mineral production and potential covers 36 commodities that are grouped into 13 groups.

This database contains geochemical analyses of over 7000 samples collected from or near mineral deposits from 60 countries, compiled by the Critical Minerals Mapping Initiative (CMMI), a collaboration between Geoscience Australia (GA), the Geological Survey of Canada (GSC) and the United States Geological Survey (USGS). Data was compiled from a number of publicly-available sources, including federal and provincial government mineral deposit and geochemistry databases, and the ore samples normalised to average crustal abundance (OSNACA) database compiled by the Centre for Exploration Targeting at the University of Western Australia. Geochemical data cover the majority of the periodic table, with metadata on analytical methods and detection limits. Where available, sample descriptions include lithology, mineralogy, and host stratigraphic units. Mineral deposits are classified according to the CMMI mineral deposit classification scheme (Hofstra et al., 2021). Location information includes deposit or prospect name, and sampling location (i.e., mine, field site, or borehole collar). This dataset will be updated periodically as more data become available. Geoscience Australia: D Champion, O Raymond, D Huston, M Sexton, E Bastrakov, S van der Wielen, G Butcher, S Hawkins, J Lane, K Czarnota, I Schroder, S McAlpine, A Britt Geological Survey of Canada: K Lauzière, C Lawley, M Gadd, J-L Pilote, A Haji Egeh, F Létourneau United States Geological Survey: M Granitto, A Hofstra, D Kreiner, P Emsbo, K Kelley, B Wang, G Case, G Graham Geological Survey of Queensland: V Lisitsin

This web service delivers data from an aggregation of sources, including several Geoscience Australia databases (provinces (PROVS), mineral resources (OZMIN), energy systems (AERA, ENERGY_SYSTEMS) and water (HYDROGEOLOGY). Information is grouped based on a modified version of the Australian Bureau of Statistics (ABS) 2021 Indigenous Regions (IREG). Data covers population centres, top industries, a regional summary, groundwater resources and uses, energy production and potential across six sources and two energy storage options. Mineral production and potential covers 36 commodities that are grouped into 13 groups.

<div>Geological maps are powerful models for visualizing the complex distribution of rock types through space and time. However, the descriptive information that forms the basis for a preferred map interpretation is typically stored in geological map databases as unstructured text data that are difficult to use in practice. Herein we apply natural language processing (NLP) to geoscientific text data from Canada, the U.S., and Australia to address that knowledge gap. First, rock descriptions, geological ages, lithostratigraphic and lithodemic information, and other long-form text data are translated to numerical vectors, i.e., a word embedding, using a geoscience language model. Network analysis of word associations, nearest neighbors, and principal component analysis are then used to extract meaningful semantic relationships between rock types. We further demonstrate using simple Naive Bayes classifiers and the area under receiver operating characteristics plots (AUC) how word vectors can be used to: (1) predict the locations of “pegmatitic” (AUC = 0.962) and “alkalic” (AUC = 0.938) rocks; (2) predict mineral potential for Mississippi-Valley-type (AUC = 0.868) and clastic-dominated (AUC = 0.809) Zn-Pb deposits; and (3) search geoscientific text data for analogues of the giant Mount Isa clastic-dominated Zn-Pb deposit using the cosine similarities between word vectors. This form of semantic search is a promising NLP approach for assessing mineral potential with limited training data. Overall, the results highlight how geoscience language models and NLP can be used to extract new knowledge from unstructured text data and reduce the mineral exploration search space for critical raw materials.</div><div><br></div><div><strong>Citation: </strong>Lawley, C. J. M., Gadd, M. G., Parsa, M., Lederer, G. W., Graham, G. E., and Ford, A., 2023, Applications of Natural Language Processing to Geoscience Text Data and Prospectivity Modeling: Natural Resources Research. https://doi.org/10.1007/s11053-023-10216-1</div>

The importance of critical minerals and the need to expand and diversify critical mineral supply chains has been endorsed by the Federal governments of Australia, Canada, and the United States. The geoscience organizations of Geoscience Australia, the Geological Survey of Canada and the U.S. Geological Survey have created the Critical Minerals Mapping Initiative to build a diversified critical minerals industry in Australia, Canada, and the United States by developing a better understanding of known critical mineral resources, determining geologic controls on critical mineral distribution for deposits currently producing byproducts, identifying new sources of supply through critical mineral potential mapping and quantitative mineral assessments, and promoting critical mineral discovery in all three countries.

<div>Earth observation is a fast and cost-effective method for greenfields exploration of critical minerals at a continental to regional scale. A broad range of optical satellite sensors are now available to mineral explorers for collecting Earth observation information (EOI) at various spatial and spectral resolutions, with different capabilities for direct identification of mineral groups and/or species as well as selected chemical elements. The spectral resolution of many of the latest imaging spectroscopy satellite systems (e.g., PRISMA - https://www.asi.it/en/earth-science/prisma/; EnMap - https://www.enmap.org/; EMIT - https://earth.jpl.nasa.gov/emit/) allow the mapping of the relative mineral abundance and, in selected cases, even the chemical composition of hydrothermal alteration minerals and pegmatite indicator minerals, such as white mica, chlorite and tourmaline. More specialised hyperspectral satellite systems, such as DESIS (https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-13614/) feature a very high spectral resolution (235 bands at 2.55 nm sampling and 3.5 nm full width half maximum) across parts of the Visible to Near-Infrared (VNIR) wavelength range, opening up the possibility for direct mapping of rare earth elements, such as neodymium. The pixel size of the imaging spectroscopy satellite systems is commonly 30 m, which can be sufficient to map hydrothermal footprints of ore deposits or surface expressions of typical rare element host rocks, such as pegmatites and carbonatites. However, airborne hyperspectral surveys still provide a higher spatial resolution, which can be essential in a given mineral exploration campaign. Selected multispectral satellite systems, such as ASTER (https://terra.nasa.gov/data/aster-data) and WorldView3 (https://resources.maxar.com/data-sheets/worldview-3) do have bands at important wavelength ranges in the shortwave infrared, but not with high enough spectral resolution&nbsp;to clearly identify many indicator minerals for critical minerals deposits. Most publicly available satellite imagery comprises multispectral systems that are focussed on the VNIR, such as Landsat and Sentinel, but which allow the direct identification of only very few mineral groups (mainly iron oxides) and not hydroxylated vector minerals (e.g., white mica, chlorite, tourmaline). This work aims to provide a summary of currently available optical satellite sensors and high-level comparison of their applications for critical minerals exploration. In addition to the spatial and spectral resolution, the impact of, for example, signal-to-noise ratio, striping and band width on accurate mineral and element mapping is discussed. For this, case studies are presented that demonstrate the potential use of the respective sensors for different stages of an exploration campaign and also the opportunities for integration with other geoscience data across scales. This abstract was presented to the 13th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing (WHISPERS) November 2023 (https://www.ieee-whispers.com/)

<div>The production of rare earth elements is critical for the transition to a low carbon economy. Carbonatites (&gt;50% carbonate minerals) are one of the most significant sources of rare earth elements (REEs), both domestically within Australia, as well as globally. Given the strategic importance of critical minerals, including REEs, for the Australian national economy, a mineral potential assessment has been undertaken to evaluate the prospectivity for carbonatite-related REE (CREE) mineralisation in Australia. CREE deposits form as the result of lithospheric- to deposit-scale processes that are spatially and temporally coincident.</div><div><br></div><div>Building on previous research into the formation of carbonatites and their related REE mineralisation, a mineral system model has been developed that incorporates four components: (1) source of metals, fluids, and ligands, (2) energy sources and fluid flow drivers, (3) fluid flow pathways and lithospheric architecture, and (4) ore deposition. This study demonstrates how national-scale datasets and a mineral systems-based approach can be used to map the mineral potential for CREE mineral systems in Australia.</div><div><br></div><div>Using statistical analysis to guide the feature engineering and map weightings, a weighted index overlay method has been used to generate national-scale mineral potential maps that reduce the exploration search space for CREE mineral systems by up to ∼90%. In addition to highlighting regions with known carbonatites and CREE mineralisation, the mineral potential assessment also indicates high potential in parts of Australia that have no previously identified carbonatites or CREE deposits.</div><div><br></div><div><b>Citation: </b>Ford, A., Huston, D., Cloutier, J., Doublier, M., Schofield, A., Cheng, Y., and Beyer, E., 2023. A national-scale mineral potential assessment for carbonatite-related rare earth element mineral systems in Australia, <i>Ore Geology Reviews</i>, V. 161, 105658. https://doi.org/10.1016/j.oregeorev.2023.105658</div>

<div>The production of rare earth elements (REEs) is critical to the global transition to a low carbon economy. Carbonatites represent a significant source of REEs, both domestically within Australia, as well as globally. Given their strategic importance for the Australian economy, a national mineral potential assessment has been undertaken as part of the Exploring for the Future program at Geoscience Australia to evaluate the potential for carbonatite-related REE (CREE) mineral systems. Rather than aiming to identify individual carbonatites and/or CREE deposits, the focus of the mineral potential assessment is to delineate prospective belts or districts within Australia that indicate the presence of favourable criteria, particularly in terms of lithospheric architecture, that may lead to the formation of a CREE mineral system.</div><div><br></div><div>This study demonstrates how national-scale multidisciplinary precompetitive geoscience datasets can be integrated using a hybrid methodology that incorporates robust statistical analysis with mineral systems expertise to predictively map areas that have a higher geological potential for the formation of CREE mineral systems and effectively reduce the exploration search space. Statistical evaluation of the relationship between different mappable criteria that represent spatial proxies for mineral system processes and known carbonatites and CREE deposits has been undertaken to test previously published hypotheses on how to target CREE mineral systems at a broad-scale. The results confirm the relevance of most criteria in the Australian context, while several new criteria such as distance to large igneous province margins and distance to magnetic worms have also been shown to have a strong correlation with known carbonatites and CREE deposits. Using a hybrid knowledge- and data-driven mineral potential mapping approach, the mineral potential map predicts the location of known carbonatite and CREE deposits, while also demonstrating additional areas of high prospectivity in regions with no previously identified carbonatites or CREE mineralisation.</div> Presented at the AusIMM Critical Minerals Conference 2023.