The Cenozoic alkaline and related igneous rocks of Australia web map service depicts the spatial representation of the alkaline and related rocks of Cenozoic age.

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.

<p>The Solid Geology of the North Australian Craton 1:1M scale dataset 1st edition (2020) is a seamless chronostratigraphic solid geology dataset of the North Australian Craton that covers north of Western Australia, Northern Territory and north-west Queensland. The data maps stratigraphic units concealed under cover by effectively removing the overlying cover (Liu et al., 2015). This dataset comprises five chronostratigraphic time slices, namely: Cenozoic, Mesozoic, Paleozoic, Neoproterozoic, and Pre-Neoproterozoic. As an example, the Mesozoic time slice (or layer) shows Mesozoic age geology that would be present if all Cenozoic units were removed. The Pre-Neoproterozoic time slice shows what would be visible if all Neoproterozoic, Paleozoic, Mesozoic, and Cenozoic units were removed. <p>Geological units are represented as polygon and line geometries and, are attributed with information regarding stratigraphic nomenclature and hierarchy, age, lithology, and primary data source. The datasets also contains geological contacts, structural features, such as faults and shears, and miscellaneous supporting lines like crater impacts or structural grain within stratigraphic units. <p>This is the second staged release of Geoscience Australia's national time based solid geology mapping program commenced under the Federal Government’s Exploring for the Future program. The Cenozoic time slice layer was extracted from Raymond, O.L., Liu, S., Gallagher, R., Highet, L.M., Zhang, W., 2012. Surface Geology of Australia, 1:1 000 000 scale, 2012 edition [Digital Dataset]. Geoscience Australia, Commonwealth of Australia, Canberra. http://www.ga.gov.au and retains the data schema of that dataset. For this layer’s metadata, refer to https://pid.geoscience.gov.au/dataset/ga/74619 <p>NOTE: Specialised Geographic Information System (GIS) software is required to view this data.

This service delivers the base of Cenozoic surface and Cenozoic thickness grids for the west Musgrave province. The gridded data are a product of 3D palaeovalley modelling based on airborne electromagnetic conductivity, borehole and geological outcrop data, carried out as part of Geoscience Australia's Exploring for the Future programme. The West Musgrave 3D palaeovalley model report and data files are available at https://dx.doi.org/10.26186/149152.

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.

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.

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.

<p>Geoscience Australia completed a regional assessment of the geological carbon dioxide (CO2) storage potential and petroleum prospectivity of the Browse Basin, offshore northwest Australia. This dual-purpose basin analysis study provided a new understanding of the basin’s Cretaceous succession based on new information regarding basin evolution, sequence stratigraphy, structural architecture and petroleum systems. The basin’s tectonostratigraphic framework was updated, and the integration of revised and recalibrated biostratigraphic data with well log and seismic interpretations has enabled an improved understanding of variations in depositional facies and the spatial distribution of reservoir, seal, and source rock sections. The outputs include models and maps of environments of deposition, play fairways, common risk element maps for regional-scale assessment of CO2 storage potential and petroleum systems model (Abbott et al., 2016; Edwards et al., 2015, 2016; Grosjean et al., 2015; Palu et al., 2017a and b; Rollet et al., 2016b, 2017a,b, 2018).<p> <p>This data pack includes 12 Cretaceous and Cenozoic horizons, and the regional fault maps produced from this study. This interpretation is based on data from 60 wells (Table 1) and 26 regional 2D and 3D seismic reflection surveys (Table 2) (Rollet et al., 2016a). Surfaces were converted from TWT to depth and integrated in a 3D geological model as input into a petroleum systems model (Palu et al., 2017a, b). <p>Data layers include: <p>12 regional depth surface grids and arcmap files generated for key Cretaceous and Cenozoic horizons (Figure 1; Table 3): K10.0_SB (late Tithonian), K20.0_SB (Valanginian), K30.0_SB (Late Hauterivian), K40.0_SB (Aptian), K50.0_SB (Late Cenomanian), K60.0_SB (Early Campanian), K65.0_SB (Maastrichtian), T10.0_SB (Base Cenozoic), T24.0_SB (Ypresian), T30.0_SB (Rupelian), T33.0_SB (Aquitanian) and water bottom based on bathymetry after Whiteway (2009), <p>2 fault population shapefiles (Figure 2): polygon envelop of shallow faults that formed during the Cenozoic collision between Australia and Asia, and horizon fault boundaries of deep regional faults that were formed through the Permian to Cretaceous.

<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>

<b>This data package is superseded by a second iteration presenting updates on 3D geological and hydrogeological surfaces across eastern Australia that can be accessed through </b><a href="https://dx.doi.org/10.26186/148552">https://dx.doi.org/10.26186/148552</a> The Australian Government, through the National Water Infrastructure Fund – Expansion, commissioned Geoscience Australia to undertake the project ‘Assessing the Status of Groundwater in the Great Artesian Basin’ (GAB). The project commenced in July 2019 and will finish in June 2022, with an aim to develop and evaluate new tools and techniques to assess the status of GAB groundwater systems in support of responsible management of basin water resources. While our hydrogeological conceptual understanding of the GAB continues to grow, in many places we are still reliant on legacy data and knowledge from the 1970s. Additional information provided by recent studies in various parts of the GAB highlights the level of complexity and spatial variability in hydrostratigraphic units across the basin. We now recognise the need to link these regional studies to map such geological complexity in a consistent, basin-wide hydrostratigraphic framework that can support effective long-term management of GAB water resources. Geological unit markers have been compiled and geological surfaces associated with lithostratigraphic units have been correlated across the GAB to update and refine the associated hydrogeological surfaces. Recent studies in the Surat Basin in Queensland and the Eromanga Basin in South Australia are integrated with investigations from other regions within the GAB. These bodies of work present an opportunity to link regional studies and develop a revised, internally consistent geological framework to map geological complexity across the GAB. Legacy borehole data from various sources, seismic and airborne electromagnetic (AEM) data were compiled, then combined and analysed in a common 3D domain. Correlation of interpreted geological units and stratigraphic markers from these various data sets are classified using a consistent nomenclature. This nomenclature uses geological unit subdivisions applied in the Surat Cumulative Management Area (OGIA (Office of Groundwater Impact Assessment), 2019) to correlate time equivalent regional hydrogeological units. Herein we provide an update of the surface extents and thicknesses for key hydrogeological units, reconciling geology across borders and providing the basis for a consistent hydrogeological framework at a basin-wide scale. The new surfaces can be used for facilitating an integrated basin systems assessment to improve our understanding of potential impacts from exploitation of sub-surface resources (e.g., extractive industries, agriculture and injection of large volumes of CO2 into the sub-surface) in the GAB and providing a basis for more robust water balance estimates. 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 2.1), • Twenty-one geological and hydrogeological unit thickness maps from the top crystalline basement to the surface (Figure 3.7 to Figure 3.27), • The formation picks and constraining data points (i.e., from boreholes, seismic, AEM and outcrops) compiled and used for gridding each surface (Table 3.8).