Rapid, efficient, and accurate prediction of mineral occurrence that takes uncertainty into 20 account is essential to optimise defining exploration targets. Traditional approaches to mineral 21 potential mapping often fail to fully appreciate spatial uncertainties of input predictors and their 22 spatial cross-correlation. In this study a stochastic technique based on multivariate 23 geostatistical simulations and ensemble tree-based learners is introduced for predicting and 24 uncertainty quantification of mineral exploration targets. The technique is tested on a synthetic 25 case inspired by the characteristics of a hydrothermal mineral system model and a real-world 26 dataset from the Yilgarn Craton in Western Australia. Results from the two cases proved the 27 superior performance and robustness of the proposed stochastic technique, especially when 28 dealing with high dimensional and large data sets. <b>Citation:</b> Talebi, H., Mueller, U., Peeters, L.J.M. et al. Stochastic Modelling of Mineral Exploration Targets. <i>Math Geosci </i>54, 593–621 (2022). https://doi.org/10.1007/s11004-021-09989-z

This web service provides access to datasets produced by the mineral potential assement of iron oxide-copper-gold (IOCG) mineral systems in the Tennant Creek – Mt Isa region. The mineral potential assessment uses a 2D, GIS-based workflow to qualitatively map four key mineral system components: (1) Sources of metals, fluids and ligands, (2) Energy to drive fluid flow, (3) Fluid flow pathways and architecture, and (4) Deposition mechanisms, such as redox or chemical gradients. For each of these key mineral system components theoretical criteria, representing important ore-forming processes, were identified and translated into mappable proxies using a wide range of input datasets. Each of these criteria are weighted and combined using an established workflow to produce the final map of IOCG potential.

The Exploring for the Future program Showcase 2024 was held on 13-16 August 2024. Day 4 - 16th August talks included: <b>Session 1 – Deep Dives into the Delamerian</b> <a href="https://youtu.be/09knAwPnD7s?si=acdu6pQgIj7DNlnj">Scaffold to success: An overview of the Delamerian Orogen, and its crustal and lithospheric architecture</a> - Chris Lewis <a href="https://youtu.be/5GQC5f5IkWc?si=rLPqxoZFkxGAEPEf">Only time will tell: Crustal development of the Delamerian Orogen in space and time</a> - David Mole <a href="https://youtu.be/PhdIYE49eqU?si=d7acyv5rbTW_wTiO">Is it a big deal? New mineral potential insights of the Delamerian Orogen</a> - Dr Yanbo Cheng <b>Session 2 – Deep dives into Birrindudu, West Musgrave and South Nicholson–Georgina regions</b> <a href="https://youtu.be/DEbkcgqwLE8?si=sBKGaMTq_mheURib">Northwest Northern Territory Seismic Survey: Resource studies and results</a> - Paul Henson <a href="https://youtu.be/k9vwBa1fM9E?si=VOG19nBC1DAk-jGH">Tracing Ancient Rivers: A hydrogeological investigation of the West Musgrave Region</a> - Joshua Lester <a href="https://youtu.be/Du1JANovz8M?si=1XEOF87gxhSP9UF3">Water's journey: Understanding groundwater dynamics in the South Nicholson and Georgina basins, NT and QLD </a>- Dr Prachi Dixon-Jain <b>Session 3 – Groundwater systems of the Curnamona and upper Darling-Baaka River</b> <a href="https://youtu.be/nU8dpekmEHQ?si=WygIzefKNzsU4gUA">Groundwater systems of the upper Darling-Baaka floodplain: An integrated assessment</a> - Dr Sarah Buckerfield <a href="https://youtu.be/AKOhuDEPxIA?si=ebradAT6EBwHhPQ_">Potential for a Managed Aquifer Recharge Scheme in the upper Darling-Baaka floodplain: Wilcannia region</a> - Dr Kok Piang Tan <a href="https://youtu.be/epUdD8ax2FQ?si=_aMO_e_ZDZESgLOR">Aquifer alchemy: Decoding mineral clues in the Curnamona region</a> - Ivan Schroder Exploring for the Future: Final reflection – Karol Czarnota Resourcing Australia’s Prosperity – Andrew Heap View or download the <a href="https://dx.doi.org/10.26186/149800">Exploring for the Future - An overview of Australia’s transformational geoscience program</a> publication. View or download the <a href="https://dx.doi.org/10.26186/149743">Exploring for the Future - Australia's transformational geoscience program</a> publication. You can access full session and Q&A recordings from YouTube here: 2024 Showcase Day 4 - Session 1 - <a href="https://www.youtube.com/watch?v=4nuIQsl71cY">Deep Dives into the Delamerian</a> 2024 Showcase Day 4 - Session 2 - <a href="https://www.youtube.com/watch?v=9N3dIZRAcHk">Deep dives into Birrindudu, West Musgrave and South Nicholson–Georgina regions</a> 2024 Showcase Day 4 - Session 3 - <a href="https://www.youtube.com/watch?v=_ddvLAnUdOI">Groundwater systems of the Curnamona and upper Darling-Baaka River</a>

In the first half of 2019, a collaborative mineral potential mapping project was undertaken between the Geological Survey of New South Wales (GSNSW) and Kenex to examine the mineral potential in the eastern Lachlan Orogen (ELO; Ford et al., 2019b). This project was part of a broader state-wide study that utilised the high quality publicly available geoscience data provided by the GSNSW to generate data-driven mineral potential maps using the weights of evidence (WofE) technique for different mineral systems in key metallogenic districts within NSW (Ford et al., 2019a). The aim of this collaborative project was to deliver a product that could be used to provide justifiable land use planning advice to key government stakeholders, as well as to highlight the exploration potential for key mineral systems at a regional scale. One key mineral system that was included in the 2019 ELO study was the porphyry Cu-Au mineral system, which was constrained to the Macquarie Arc. The results of the WofE mineral potential mapping for this porphyry model were broadly successful in terms of predicting the location of both the training data used in the WofE model, as well as a separate set of validation porphyry Cu-Au occurrences. However, the model failed to predict the location of one of the training points, Kaiser, in the prospective area. This failure to predict Kaiser led to a re-evaluation of the data using a variety of different machine learning techniques, in particular random forests (RF; Ford, 2020) and neural networks (NN). No additional or updated data was incorporated, and the maps used in the machine learning were the same maps made as part of the initial WofE study in 2019. The results show that the use of input maps that have been pre-classified to determine optimal thresholds outperform input maps that have had no favourability criteria applied when typical benchmarks for exploration targeting are considered. In addition, the NN analysis shows strong evidence of overfitting to the training data when a large number of input maps are used. A moderate degree of success for targeting under cover was achieved when only geophysical maps were included in the models. Abstract presented at the 8th Mines & Wines Conference 2022 (https://www.aig.org.au/events/8th-mines-wines-conference-2022/)

<div>This study is part of the Mineral Potential Assessment (MPA) module of Geoscience Australia's Darling-Curnamona-Delamerian (DCD) project, a deep-dive project within the Exploring for the Future Program (EFTF) 2020-2024. An objective of the DCD project is to further the understanding of the geological architecture of the Delamerian Orogen into a cohesive framework enable a regional mineral potential assessment of this under-explored and mostly under cover Orogen. The MPA module is one of eight modules under the umbrella of the DCD project. To facilitate assessment of the mineral potential of the project area, the mineral potential assessment study has 3 key scientific objectives: (1) Defining the characteristics of the mineral systems / prospects. (2)&nbsp;&nbsp;Evaluating the temporal framework of the formation of mineral systems / prospects; and (3) Understanding the regional magma fertility. This study delivers Objective 1, i.e., outlining the principle geological and metallogenic characteristics of reported mineral prospects in the project area.&nbsp;</div><div><br></div><div>Legacy drill cores best demonstrating metallogenic features of different mineral system types at key prospects across the project area were selected for viewing and sampling following review of historical exploration reports and assay results. Four sets of data are included in the appendices of this report: (1)&nbsp;&nbsp;HyLogger spectral images of 20 drill holes of 8 prospects in New South Wales. (2)&nbsp;&nbsp;143 high-resolution scan files of legacy drill core samples across the project area. (3)&nbsp;&nbsp;16 microscopic images of thin sections for 4 prospects of the Loch Lilly-Kars Belt, New South Wales. (4)&nbsp;&nbsp;53 Backscattered Electron (BSE) images and 53 Advanced Mineral Identification and Characterization System (AMICS) high-resolution mineral maps of 53 samples from 18 prospects across the whole Delamerian Margin.&nbsp;</div><div><br></div><div>Metallogenic characteristics of samples from four different mineral deposit types were studied, along deposits of uncertain affiliation (referred here as undefined systems), including (1) Porphyry-epithermal mineral systems. (2)&nbsp;&nbsp;Volcanic hosted massive sulfide (VHMS) mineral systems. (3)&nbsp;&nbsp;Orogenic gold mineral systems. (4)&nbsp;&nbsp;Mafic-ultramafic Cu-Ni-PGE mineral systems. (5)&nbsp;&nbsp;Metallogenetically undefined systems. Detailed metallogenic characteristics of the samples from 22 key prospects in Delamerian Orogen are documented in this report.&nbsp;&nbsp;</div><div><br></div><div>This is the first systemic study on the essential metallogenic characteristics of the mineral systems in Delamerian. The characterisations outlined in this report are foundational for understanding the regional metallogenesis and assessing the potential of multiple types of mineral systems in the Delamerian Belt, which should be useful in both academic and the mineral exploration sector.</div><div><br></div><div>The high-resolution BSE and AMICS mineral maps are available at Geoscience Australia. Please reach out to the senior author of this GA Record, Dr. Yanbo Cheng (Yanbo.cheng@ga.gov.au). </div>

<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.

<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.

<div>The mineral potential toolkit (aka minpot-toolkit) provides tools to facilitate mineral potential analysis, from spatial associations to feature engineering and fully integrated mineral potential mapping.</div>

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.