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>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>

This report, completed as part of Geoscience Australia’s Exploring for the Future Program National Groundwater Systems (NGS) Project, presents results of the second iteration of 3D geological and hydrogeological surfaces across eastern Australian basins. The NGS project is part of the Exploring for the Future (EFTF) program—an eight-year, $225 million Australian Government funded geoscience data and precompetitive information acquisition program. The program seeks to inform decision-making by government, community, and industry on the sustainable development of Australia's mineral, energy, and groundwater resources, including those to support the effective long-term management of GAB water resources. This work builds on the first iteration completed as part of the Great Artesian Basin Groundwater project. The datasets incorporate infills of data and knowledge gaps in the Great Artesian Basin (GAB), Lake Eyre Basin (LEB), Upper Darling Floodplain (UDF) and existing data in additional basins in eastern Australia. The study area extends from the offshore Gulf of Carpentaria in the north to the offshore Bight, Otway, and Gippsland basins in the South and from the western edge of the GAB in the west to the eastern Australian coastline to the east. The revisions are an update to the surface extents and thicknesses for 18 region-wide hydrogeological units produced by Vizy & Rollet, 2022. The second iteration of the 3D model surfaces further unifies geology across borders and provides the basis for a consistent hydrogeological framework at a basin-wide, and towards a national-wide, scale. The stratigraphic nomenclature used follows geological unit subdivisions applied: (1) in the Surat Cumulative Management Area (OGIA - Office of Groundwater Impact Assessment, 2019) to correlate time equivalent regional hydrogeological units in the GAB and other Jurassic and Cretaceous time equivalent basins in the study area and (2) in the LEB to correlate Cenozoic time equivalents in the study area. Triassic to Permian and older basins distribution and thicknesses are provided without any geological and hydrogeological unit sub-division. Such work helps to (1) reconcile legacy and contemporary regional studies under a common stratigraphic framework, (2) support the effective management of groundwater resources, and (3) provide a regional geological context for integrated resource assessments. The 18 hydrogeological units were constructed using legacy borehole data, 2D seismic and airborne electromagnetic (AEM) data that were compiled for the first iteration of the geological and hydrogeological surfaces under the GAB groundwater project (Vizy & Rollet, 2022a) with the addition of: • New data collected and QC’d from boreholes (including petroleum, CSG [Coal Seam Gas], stratigraphic, mineral and water boreholes) across Australia (Vizy & Rollet, 2023a) since the first iteration, including revised stratigraphic correlations filling data and knowledge gaps in the GAB, LEB, UDF region (Norton & Rollet, 2023) with revised palynological constraints (Hannaford & Rollet 2023), • Additional AEM interpretation since the first iteration in the GAB, particularly in the northern Surat (McPherson et al., 2022b), as well as in the LEB (Evans et al., in prep), in the southern Eromanga Basin (Wong et al., 2023) and in the UDF region (McPherson et al., 2022c), and • Additional 2D seismic interpretation in the Gulf of Carpentaria (Vizy & Rollet, 2023b) and in the western and central Eromanga Basin (Szczepaniak et al., 2023). These datasets were then analysed and interpreted in a common 3D domain using a consistent chronostratigraphic framework tied to the geological timescale of 2020, as defined by Hannaford et al. (2022). Confidence maps were also produced to highlight areas that need further investigation due to data gaps, in areas where better seismic depth conversion or improved well formation picks are required. New interpretations from the second iteration of the 18 surfaces include (1) new consistent and regionally continuous surfaces of Cenozoic down to Permian and older sediments beyond the extent of the GAB across eastern Australia, (2) revised extents and thicknesses of Jurassic and Cretaceous units in the GAB, including those based on distributed thickness, (3) revised extents and thicknesses of Cenozoic LEB units constrained by the underlying GAB 3D model surfaces geometry. These data constraints were not used in the model surfaces generated for the LEB detailed inventory (Evans et al., 2023), and (4) refinements of surfaces due to additional seismic and AEM interpretation used to infill data and knowledge gaps. Significant revisions include: • The use of additional seismic data to better constrain the base of the Poolowanna-Evergreen formations and equivalents and the top of Cadna-owie Formation and equivalents in the western and central Eromanga Basin, and the extent and thicknesses of the GAB units and Cenozoic Karumba Basin in the Gulf of Carpentaria, • The use of AEM interpretations to refine the geometry of outcropping units in the northern Surat Basin and the basement surface underneath the UDF region, and • A continuous 3D geological surface of base Cenozoic sediments across eastern Australia including additional constraints for the Lake Eyre Basin (borehole stratigraphy review), Murray Basin (AEM interpretation) and Karumba Basin (seismic interpretation). These revisions to the 18 geological and hydrogeological surfaces will help improve our understanding on the 3D spatial distribution of aquifers and aquitards across eastern Australia, from the groundwater recharge areas to the deep confined aquifers. These data compilations and information brought to a common national standard help improve hydrogeological conceptualisation of groundwater systems across multiple jurisdictions to assist water managers to support responsible groundwater management and secure groundwater into the future. These 3D geological and hydrogeological modelled surfaces also provide a tool for consistent data integration from multiple datasets. These modelled surfaces bring together variable data quality and coverage from different databases across state and territory jurisdictions. Data integration at various scale is important to assess potential impact of different water users and climate change. The 3D modelled surfaces can be used as a consistent framework to map current groundwater knowledge at a national scale and help highlight critical groundwater areas for long-term monitoring of potential impacts on local communities and Groundwater Dependant Ecosystems. The distribution and confidence on data points used in the current iteration of the modelled surfaces highlight where data poor areas may need further data acquisition or additional interpretation to increase confidence in the aquifers and aquitards geometry. The second iteration of surfaces highlights where further improvements can be made, notably for areas in the offshore Gulf of Carpentaria with further seismic interpretation to better constrain the base of the Aptian marine incursion (to better constrain the shape and offshore extent of the main aquifers). Inclusion of more recent studies in the offshore southern and eastern margins of Australia will improve the resolution and confidence of the surfaces, up to the edge of the Australian continental shelf. Revision of the borehole stratigraphy will need to continue where more recent data and understanding exist to improve confidence in the aquifer and aquitard geometry and provide better constraints for AEM and seismic interpretation, such as in the onshore Carpentaria, Clarence-Moreton, Sydney, Murray-Darling basins. Similarly adding new seismic and AEM interpretation recently acquired and reprocessed, such as in the eastern Eromanga Basin over the Galilee Basin, would improve confidence in the surfaces in this area. Also, additional age constraints in formations that span large periods of time would help provide greater confidence to formation sub-divisions that are time equivalent to known geological units that correlate to major aquifers and aquitards in adjacent basins, such as within the Late Jurassic‒Early Cretaceous in the Eromanga and Carpentaria basins. Finally, incorporating major faults and structures would provide greater definition of the geological and hydrogeological surfaces to inform with greater confidence fluid flow pathways in the study area. This report is associated with a data package including (Appendix A – Supplementary material): • Nineteen geological and hydrogeological surfaces from the Base Permo-Carboniferous, Top Permian, Base Jurassic, Base Cenozoic to the surface (Table 1.1), • Twenty-one geological and hydrogeological unit thickness maps from the top crystalline basement to the surface (Figure 3.1 to Figure 3.21), • The formation picks and constraining data points (i.e., from boreholes, seismic, AEM and outcrops) compiled and used for gridding each surface (Table 2.7). Detailed explanation of methodology and processing is described in the associated report (Vizy & Rollet, 2023).