<div>This video gives an overview of the $225 million Exploring for the Future program (2016-2024), the Australian Government’s flagship precompetitive geoscience initiative. It uses cutting-edge technologies and approaches to deliver world-leading information about the geological structure, systems and evolution of the Australian continent.</div>

<div>The study utilised Geoscience Australia’s vast data collection of mineral occurrences to identify the range of historical discoveries within the Officer-Musgrave, Darling-Curnamona - Delameian and Barkly - Isa - Georgetown Deep Dive areas. A literature review shed light on exploration discovery methods, commodity grades, exploration histories and deposit types. Many critical mineral occurrences were overlooked or ignored in the past, as the commodity discovered was not of interest or value at the time, or grades were regarded as sub-economic. However, with modern methods of mining, ore treatment techniques and increased demand, reassessment could now provide new opportunities.</div>

<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>

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

Critical minerals are pivotal to human society in industrialised and developing economies. Many critical minerals are irreplaceable inputs for technological and industrial advancements, especially renewable energy systems, electric vehicles, rechargeable batteries, consumer electronics, telecommunications, specialty alloys, and defence technologies. Critical minerals are metals, non-metals and mineral compounds that are economically important and are also subject to high risks of supply. “Criticality” is a subjective concept; countries develop their own lists of critical minerals based on the relative importance of particular minerals to their industrial needs and strategic assessment of supply risks. Lists are reviewed and changed over time. Commonly appearing on lists of high criticality are: antimony, barite, beryllium, bismuth, cesium, chromium, cobalt, germanium, indium, lithium, manganese, niobium, platinum-group elements (PGE), potash, rare earth elements (REE), rhenium, rubidium, scandium, strontium, tantalum, tellurium, rhenium, tungsten, and vanadium. The supply of critical minerals is an area of great growth potential, based on increasing technological demands and uses at a global level. Australia is one of the world’s principal producers of several key major mineral commodities (e.g. bauxite, coal, copper, lead, gold, ilmenite, iron ore, nickel, rutile, zircon, and zinc). Although some critical minerals are mined as primary products (e.g. REE, lithium, potash), many critical minerals are extracted as companion products from base or precious metal production (e.g. PGE from nickel sulfide ores, or indium from zinc concentrate). Considering that Australia has leading expertise in mining and metallurgical processing as well as extensive mineral resources likely to contain critical minerals, there is a clear opportunity for Australia to develop into a major, transparent and reliable supplier of critical minerals for the global economy. Based on a conservative estimate, Australia could add approximately $9.4 billion of value to the nation's mineral and metal production (currently valued at $112.2 billion, or an increase of about 8%) through the production of four critical commodities (hafnium, niobium, rare earth elements and scandium) from existing mines and favourable deposits. Full realisation of this and potentially even greater production is significantly affected by other factors, including: insufficient knowledge of critical minerals in Australian deposits and their behaviour during metallurgical processing due to limited reporting by industry; few geological studies dedicated to assessing and facilitating the discovery of critical mineral resources in Australia; the need for new mining technology and services to economically extract critical minerals; gaps in capabilities of domestic smelters/refineries to process critical minerals. These issues require further research and investigation in order for Australia to maximise its position in global critical minerals markets. This study was commissioned by Geoscience Australia in collaboration with RMIT and Monash University to summarise key aspects of the current state of critical minerals in Australia. The report covers: global demand and supply; Australia’s resource potential; an overview of ‘criticality’ assessment methods; estimates of potential economic value; and future research needs for critical minerals in Australia.

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>Maps showing the potential for carbonatite-related rare earth element (REE) mineral systems in Australia. Each of the mineral potential maps is a synthesis of three or four component layers. Model 1 integrates three components: sources of metals, energy drivers, and lithospheric architecture. Model 2 integrates four components: sources of metals, energy drivers, lithospheric architecture, and ore deposition. Both models use 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 map for Model 2 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. An assessment criteria table is provided and contains information on the map creation.</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.

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 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.