<div>This data package contains interpretations of airborne electromagnetic (AEM) conductivity sections in the Exploring for the Future (EFTF) program’s Eastern Resources Corridor (ERC) study area, in south eastern Australia. Conductivity sections from 3 AEM surveys were interpreted to provide a continuous interpretation across the study area – the EFTF AusAEM ERC (Ley-Cooper, 2021), the Frome Embayment TEMPEST (Costelloe et al., 2012) and the MinEx CRC Mundi (Brodie, 2021) AEM surveys. Selected lines from the Frome Embayment TEMPEST and MinEx CRC Mundi surveys were chosen for interpretation to align with the 20&nbsp;km line-spaced EFTF AusAEM ERC survey (Figure 1).</div><div>The aim of this study was to interpret the AEM conductivity sections to develop a regional understanding of the near-surface stratigraphy and structural architecture. To ensure that the interpretations took into account the local geological features, the AEM conductivity sections were integrated and interpreted with other geological and geophysical datasets, such as boreholes, potential fields, surface and basement geology maps, and seismic interpretations. This approach provides a near-surface fundamental regional geological framework to support more detailed investigations. </div><div>This study interpreted between the ground surface and 500&nbsp;m depth along almost 30,000 line kilometres of nominally 20&nbsp;km line-spaced AEM conductivity sections, across an area of approximately 550,000&nbsp;km2. These interpretations delineate the geo-electrical features that correspond to major chronostratigraphic boundaries, and capture detailed stratigraphic information associated with these boundaries. These interpretations produced approximately 170,000 depth estimate points or approximately 9,100 3D line segments, each attributed with high-quality geometric, stratigraphic, and ancillary data. The depth estimate points are formatted for compliance with Geoscience Australia’s (GA) Estimates of Geological and Geophysical Surfaces (EGGS) database, the national repository for standardised depth estimate points. </div><div>Results from these interpretations provided support to stratigraphic drillhole targeting, as part of the Delamerian Margins NSW National Drilling Initiative campaign, a collaboration between GA’s EFTF program, the MinEx CRC National Drilling Initiative and the Geological Survey of New South Wales. The interpretations have applications in a wide range of disciplines, such as mineral, energy and groundwater resource exploration, environmental management, subsurface mapping, tectonic evolution studies, and cover thickness, prospectivity, and economic modelling. It is anticipated that these interpretations will benefit government, industry and academia with interest in the geology of the ERC region.</div>

<div>The interpretation of AusAEM airborne electromagnetic (AEM) survey conductivity sections in the Canning Basin region delineates the geo-electrical features that correspond to major chronostratigraphic boundaries, and captures detailed stratigraphic information associated with these boundaries. This interpretation forms part of an assessment of the underground hydrogen storage potential of salt features in the Canning Basin region based on integration and interpretation of AEM and other geological and geophysical datasets. A main aim of this work was to interpret the AEM to develop a regional understanding of the near-surface stratigraphy and structural geology. This regional geological framework was complimented by the identification and assessment of possible near-surface salt-related structures, as underground salt bodies have been identified as potential underground hydrogen storage sites. This study interpreted over 20,000 line kilometres of 20&nbsp;km nominally line-spaced AusAEM conductivity sections, covering an area approximately 450,000 km2 to a depth of approximately 500&nbsp;m in northwest Western Australia. These conductivity sections were integrated and interpreted with other geological and geophysical datasets, such as boreholes, potential fields, surface and basement geology maps, and seismic interpretations. This interpretation produced approximately 110,000 depth estimate points or 4,000 3D line segments, each attributed with high-quality geometric, stratigraphic, and ancillary data. The depth estimate points are formatted for Geoscience Australia’s Estimates of Geological and Geophysical Surfaces database, the national repository for formatted depth estimate points. Despite these interpretations being collected to support exploration of salt features for hydrogen storage, they are also intended for use in a wide range of other disciplines, such as mineral, energy and groundwater resource exploration, environmental management, subsurface mapping, tectonic evolution studies, and cover thickness, prospectivity, and economic modelling. Therefore, these interpretations will benefit government, industry and academia interested in the geology of the Canning Basin region.</div>

Building on newly acquired airborne electromagnetic and seismic reflection data during the Exploring for the Future (EFTF) program, Geoscience Australia (GA) generated a cover model across the Northern Territory and Queensland, in the Tennant Creek – Mount Isa (TISA) area (Figure 1; between 13.5 and 24.5⁰ S of latitude and 131.5 and 145⁰ E of longitude) (Bonnardot et al., 2020). The cover model provides depth estimates to chronostratigraphic layers, including: Base Cenozoic, Base Mesozoic, Base Paleozoic and Base Neoproterozoic. The depth estimates are based on the interpretation, compilation and integration of borehole, solid geology, reflection seismic, and airborne electromagnetic data, as well as depth to magnetic source estimates. These depth estimates in metres below the surface (relative to the Australian Height Datum) are consistently stored as points in the Estimates of Geophysical and Geological Surfaces (EGGS) database (Matthews et al., 2020). The data points compiled in this data package were extracted from the EGGS database. Preferred depth estimates were selected to ensure regional data consistency and aid the gridding. Two sets of cover depth surfaces (Bonnardot et al., 2020) were generated using different approaches to map megasequence boundaries associated with the Era unconformities: 1) Standard interpolation using a minimum-curvature gridding algorithm that provides minimum misfit where data points exist, and 2) Machine learning approach (Uncover-ML, Wilford et al., 2020) that allows to learn about relationships between datasets and therefore can provide better depth estimates in areas of sparse data points distribution and assess uncertainties. This data package includes the depth estimates data points compiled and used for gridding each surface, for the Base Cenozoic, Base Mesozoic, Base Paleozoic and Base Neoproterozoic (Figure 1). To provide indicative trends between the depth data points, regional interpolated depth surface grids are also provided for the Base Cenozoic, Base Mesozoic, Base Paleozoic and Base Neoproterozoic. The grids were generated with a standard interpolation algorithm, i.e. minimum-curvature interpolation method. Refined gridding method will be necessary to take into account uncertainties between the various datasets and variable distances between the points. These surfaces provide a framework to assess the depth and possible spatial extent of resources, including basin-hosted mineral resources, basement-hosted mineral resources, hydrocarbons and groundwater, as well as an input to economic models of the viability of potential resource development.

To meet the increasing demand for natural resources globally, industry faces the challenge of exploring new frontier areas that lie deeper undercover. Here, we present an approach to, and initial results of, modelling the depth of four key chronostratigraphic packages that obscure or host mineral, energy and groundwater resources. Our models are underpinned by the compilation and integration of ~200 000 estimates of the depth of these interfaces. Estimates are derived from interpretations of newly acquired airborne electromagnetic and seismic reflection data, along with boreholes, surface and solid geology, and depth to magnetic source investigations. Our curated estimates are stored in a consistent subsurface data repository. We use interpolation and machine learning algorithms to predict the distribution of these four packages away from the control points. Specifically, we focus on modelling the distribution of the base of Cenozoic-, Mesozoic-, Paleozoic- and Neoproterozoic-age stratigraphic units across an area of ~1.5 million km2 spanning the Queensland and Northern Territory border. Our repeatable and updatable approach to mapping these surfaces, together with the underlying datasets and resulting models, provides a semi-national geometric framework for resource assessment and exploration. <b>Citation:</b> Bonnardot, M.-A., Wilford, J., Rollet, N., Moushall, B., Czarnota, K., Wong, S.C.T. and Nicoll, M.G., 2020. Mapping the cover in northern Australia: towards a unified national 3D geological model. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

The Exploring for the Future program Virtual Roadshow was held on 7 July and 14-17 July 2020. The Minerals session of the roadshow was held on 14 July 2020 and consisted of the following presentations: Introduction - Richard Blewett Preamble - Karol Kzarnota Surface & Basins or Cover - Marie-Aude Bonnardot Crust - Kathryn Waltenberg Mantle - Marcus Haynes Zinc on the edge: New insights into sediment-hosted base metals mineral system - David Huston Scale reduction targeting for Iron-Oxide-Copper-Gold in Tennant Creek and Mt Isa - Anthony Schofield and Andrew Clark Economic Fairways and Wrap-up - Karol Czarnota

This service provides Estimates of Geological and Geophysical Surfaces (EGGS). The data comes from cover thickness models based on magnetic, airborne electromagnetic and borehole measurements of the depth of stratigraphic and chronostratigraphic surfaces and boundaries.

Water, energy and mineral resources are vital for Australia’s economic prosperity and sustainable development. However, continued supply of these resources cannot be taken for granted. It is widely accepted that the frontier of exploration now lies beneath the Earth’s surface, making characterisation of the subsurface a unifying challenge. Between 2016 and 2020, the $100.5 million Exploring for the Future program focused on addressing this challenge across northern Australia in order to better define resource potential and boost investment. The program applied a multiscale systems approach to resource assessment based on characterisation of the Australian plate from the surface down to its base, underpinned by methodological advances. The unprecedented scale and diversity of new data collected have resulted in many world-first achievements and breakthrough insights through integrated systems science. Through this multi-agency effort, new continental-scale datasets are emerging to further enhance Australia’s world-leading coverage. The program has identified prospective regions for a wide range of resources and pioneered approaches to exploration undercover that can be applied elsewhere. The outcomes so far include extensive tenement uptake for minerals and energy exploration in covered terranes, and development of informed land-management policy. Here, we summarise the key scientific achievements of the program by reviewing the main themes and interrelationships of 62 contributions, which together constitute the Exploring for the Future: extended abstracts volume. <b>Citation:</b> Czarnota, K., Roach, I.C., Abbott, S.T., Haynes, M.W., Kositcin, N., Ray, A. and Slatter, E., 2020. Exploring for the Future: advancing the search for groundwater, energy and mineral resources. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

It is increasingly recognised that, to maintain a sustainable pipeline of mineral resources in Australia, future discoveries will need to be made in areas obscured by more recent cover sequences. A major challenge to mineral exploration in covered frontiers is identifying new prospective fairways, and understanding and mapping important metallogenic processes at a range of scales to enable more effective targeting of exploration. Here, we present evidence for a completely buried corridor of interpreted high prospectivity—the East Tennant region—based on synthesis and integration of a diverse range of geoscientific datasets. Key indicators of the region’s potential include lithospheric-scale architecture, elevated electrical conductivity in the crust and mantle, and modelled and demonstrated hydrothermal alteration in the near surface. Multiscale geophysical surveys show evidence for crustal-scale fluid flow along major structures, connecting the mantle with the surface. Although few geological constraints exist in this region, examination of legacy drillcore and geochronology results demonstrates a similar history to rocks known to host mineralisation across the North Australian Craton. These results provide tantalising indications that the under-explored East Tennant region has significant potential to host major mineral systems. <b>Citation: </b>Schofield, A., Clark, A., Doublier, M.P., Murr, J., Skirrow, R., Goodwin, J., Cross, A. J., Pitt, L., Duan, J., Jiang, W., Wynne, P., O’Rourke, A., Czarnota, K., and I. C. Roach., 2020. Data integration for greenfields exploration: an example from the East Tennant region, Northern Territory. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

The Murray Basin is a saucer-shaped basin with flat-lying Cenozoic sediments up to approximately 600 m thickness (Brown and Stephenson, 1991). Constraints on the thickness of the Murray Basin have been compiled from: drillholes, reflection seismic profile interpretations, refraction seismic profiles and depth to magnetic basement estimates (Target_type.pdf). Target depths were sourced from Geoscience Australia, the national Groundwater Information System database (Http://www.bom.gov.au/water/groundwater/ngis/), the Geological Survey of Victoria (http://earthresources.vic.gov.au/earth-resources/geology-of-victoria/geological-survey-of-victoria) and the Geological Survey of South Australia (http://www.minerals.statedevelopment.sa.gov.au/geoscience/geological_survey). In addition, some of the magnetic depth estimates used data from McLean (2010). To constrain the thickness of Cenozoic cover where sediments were either absent or very thin we generated shallow-depth values in areas with post-Cenozoic geology and high topographic relief. In all, 5436 depth estimates were compiled (Target_depths.xlsx). The input datasets have been used to generate two predictive models of the thickness of Cenozoic sediments within the Murray Basin. The first model uses kriging of the depth estimates to generate a gridded surface using a local-area linear variogram model as a means of interpolating between constraints (Murray_Basin_kriging_Cenozoic_thickness.pdf; Murray_Basin_krig.tif -floating value grid). The second model uses a machine-learning approach where correlations between 17 supplementary datasets and 5436 depth estimates are used to derive a predictive model. We used a supervised learning algorithm known as Gaussian Process (GP) to generate the integrated predictive model. Gaussian Process is a non-parametric probabilistic approach to learning. It uses kernel functions to measure the similarity between points and predict values not seen from the training data (see Read_Me_GP.rtf). The supplementary datasets used in the model are listed in Table 1 and model variable settings can be found in read_me.rtf (Murray_Basin_GP_Cenozoic_thickness.pdf; Murray_Basin_GP_model.tif -floating value grid). Both approaches delineate the overall structure, geometry and thickness of the Murray Basin. The advantage of the machine learning approach is that it learns relationships between the depth and supplementary datasets which allow predictions in areas with limited constraints. References Brown, C. M. and Stephenson, A. E., 1991, Geology of the Murray Basin, southeastern Australia, Canberra, Bureau of Mineral Resources Bulletin 235, 430 p. McLean, M.A., 2010. Depth to Palaeozoic basement of the Gold Undercover region from borehole and magnetic data. GeoScience Victoria Gold Undercover Report 21. Department of Primary Industries, Victoria. Table 1. Supplementary input datasets used in predictive estimation of Murray Basin thickness, utilising a machine learning method Covariates* Description 1 Latitude Gridded latitude values 2 Longitude Gridded longitude values 3 Elevation Terrain elevation – 90m shuttle DEM 4 Distance from bedrock Euclidean distance from outcrop geology units older than Cenozoic 5 Gravity Terrain and isostatic corrected Bouguer gravity 6 Gravity 1228 Upward continued gravity at 1228 metres 7 Gravity 2407 Upward continued gravity at 2407 metres 8 Gravity 6605 Upward continued gravity at 6605 metres 9 Gravity 18124 Upward continued gravity at 18124 metres 10 Gravity 35524 Upward continued gravity at 35524 metres 11 Gravity 49734 Upward continued gravity at 49734 metres 12 Gravity 97479 Upward continued gravity at 97479 metres 13 Gravity – 1k Isostatically corrected gravity subtracted from upward continued gravity at 1000 metres 14 Magnetics 5km Upward continued magnetic anomaly grid at 5 km 15 Magnetic 10km Upward continued magnetic anomaly grid at 10 km 16 Magnetic 5-10km Upward continued 5km magnetic anomaly grid subtracted from upward continued 10 km magnetic anomaly grid 17 Magnetic basement Depth to magnetic basement using the tilt method. *Primary datasets including gravity, magnetics and surface geology sourced from Geoscience Australia http://www.ga.gov.au/data-pubs/maps Elevation dataset used the 3 second (~90m) Shuttle Radar Topography Mission (SRTM) digital elevation model. https://pid.geoscience.gov.au/dataset/ga/72760.

<div>Geoscience Australia’s Exploring for the Future program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia’s geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia’s transition to net zero emissions, strong, sustainable resources and agriculture sectors, and economic opportunities and social benefits for Australia’s regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government. This work contributes to building a better understanding of the Australian continent, whilst giving the Australian public the tools they need to help them make informed decisions in their areas of interest.</div><div><br></div><div>As part of the Australia's Resources Framework Project, in the Exploring for the Future Program, Geoscience Australia and CSIRO undertook a magnetic source depth study across four areas, with the objectives of generating cover model constraints from magnetic modelling to expand national coverage, and to improve our subsurface understanding of these areas. During this study, 2005 magnetic estimates of depth to the top of magnetization were generated, with solutions derived using a consistent methodology (targeted magnetic inversion modelling, or TMIM; also known as ‘sweet-spot’ modelling). The methodology for these estimates are detailed in a summary report by Foss et al (2024), and is available for download through Geoscience Australia’s enterprise catalogue (https://pid.geoscience.gov.au/dataset/ga/149239). </div><div><br></div><div>The new points were generated over four areas: 1) the western part of Tasmania that is the southernmost extension of the Darling-Curnamona-Delamerian (DCD) project area; 2) northeastern Queensland; 3) the Officer Basin area of western South Australia and southeastern West Australia; and 4) the Eastern Resources Corridor (ERC), covering eastern South Australia, southwest Queensland, western New South Wales and western Victoria. These depth estimates have been released, together with a summary report detailing the data and methodology used to generate the results, through Geoscience Australia's product catalogue (ecat) at https://pid.geoscience.gov.au/dataset/ga/149239.</div><div><br></div><div>This supplementary data release contains the chronostratigraphic attribution of the new TMIM magnetic depth estimates, which range in depth from at surface to 13,294 m below ground. To ensure that the interpretations took into account the local geological features, the magnetic depth estimates were integrated and interpreted with other geological and geophysical datasets, including borehole stratigraphic logs, potential fields images, surface and solid geology maps, and airborne electromagnetic interpretations (where available). </div><div><br></div><div>Each depth-solution is interpretively ascribed to either a chronostratigraphic boundary with the stratigraphic units above and below the depth estimate, or the stratigraphic unit that the depth estimate occurs within, populated from the Australian Stratigraphic Units Database (ASUD). Stratigraphic attribution adds value and informs users of the depth to certain stratigraphic units in their areas of interest. Each solution is accompanied by confidence estimates. The depth estimate points are formatted for compliance with Geoscience Australia’s (GA) Estimates of Geological and Geophysical Surfaces (EGGS) database, the national repository for standardised depth estimate points. </div><div><br></div><div>Results from these interpretations provided some support to stratigraphic drillhole targeting, as part of the Delamerian Margins NSW National Drilling Initiative campaign, a collaboration between GA’s EFTF program, the MinEx CRC National Drilling Initiative and the Geological Survey of New South Wales. The magnetic depth-estimate solutions produced within this study provide important depth constraints in data-poor areas. These data help to construct a better understanding of the 3D geometry of the Australian continent and aid in cover thickness modelling activities. The availability of the depth-estimate solutions via the EGGS database through Geoscience Australia’s Portal creates enduring value to the public.</div>