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.

This release comprises the 3D geological model of the Yilgarn-Officer-Musgrave (YOM) region, Western Australia, as Gocad voxets and surfaces. The YOM 3D geological model was built to highlight the broad-scale crustal architecture of the region and extends down to 60 km depth.

Radiogenic isotopes decay at known rates and can be used to interpret ages for minerals, rocks and geologic processes. Different isotopic systems provide information related to different time periods and geologic processes, systems include: U-Pb and Ar/Ar, Sm-Nd, Pb-Pb, Lu-Hf, Rb-Sr and Re-Os isotopes. The GEOCHRON database stores full analytical U-Pb age data from GA’s Sensitive High Resolution Ion Micro-Probe (SHRIMP) program. The ISOTOPE database is designed to expand GA’s ability to deliver isotopic datasets, and stores compiled age and isotopic data from a range of published and unpublished (GA and non-GA) sources. OZCHRON is a depreciated predecessor to GEOCHRON and ISOTOPE, the information once available in OZCHRON is in the process of migration to the two current databases. The ISOTOPE compilation includes sample and bibliographic links through the A, FGDM, and GEOREF databases. The data structure currently supports summary ages (e.g., U-Pb and Ar/Ar) through the INTERPRETED_AGES tables, as well as extended system-specific tables for Sm-Nd, Pb-Pb, Lu-Hf and O- isotopes. The data structure is designed to be extensible to adapt to evolving requirements for the storage of isotopic data. ISOTOPE and the data holdings were initially developed as part of the Exploring for the Future (EFTF) program – particularly to support the delivery of an Isotopic Atlas of Australia. During development of ISOTOPE, some key considerations in compiling and storing diverse, multi-purpose isotopic datasets were developed: 1) Improved sample characterisation and bibliographic links. Often, the usefulness of an isotopic dataset is limited by the metadata available for the parent sample. Better harvesting of fundamental sample data (and better integration with related national datasets such as Australian Geological Provinces and the Australian Stratigraphic Units Database) simplifies the process of filtering an isotopic data compilation using spatial, geological and bibliographic criteria, as well as facilitating ‘audits’ targeting missing isotopic data. 2) Generalised, extensible structures for isotopic data. The need for system-specific tables for isotopic analyses does not preclude the development of generalised data-structures that reflect universal relationships. GA has modelled relational tables linking system-specific Sessions, Analyses, and interpreted data-Groups, which has proven adequate for all of the Isotopic Atlas layers developed thus far. 3) Dual delivery of ‘derived’ isotopic data. In some systems, it is critical to capture the published data (i.e. isotopic measurements and derived values, as presented by the original author) and generate an additional set of derived values from the same measurements, calculated using a single set of reference parameters (e.g. decay constant, depleted-mantle values, etc.) that permit ‘normalised’ portrayal of the data compilation-wide. 4) Flexibility in data delivery mode. In radiogenic isotope geochronology (e.g. U-Pb, Ar-Ar), careful compilation and attribution of ‘interpreted ages’ can meet the needs of much of the user-base, even without an explicit link to the constituent analyses. In contrast, isotope geochemistry (especially microbeam-based methods such as Lu-Hf via laser ablation) is usually focused on the individual measurements, without which interpreted ‘sample-averages’ have limited value. Data delivery should reflect key differences of this kind. <b>Value: </b>Used to provide ages and isotope geochemistry data for minerals, rocks and geologic processes. <b>Scope: </b>Australian jurisdictions and international collaborative programs involving Geoscience Australia <b>To view the entire collection click on the keyword "HVC_144624" in the below Keyword listing</b>

The ISOTOPE database stores compiled age and isotopic data from a range of published and unpublished (GA and non-GA) sources. This internal database is only publicly accessible through the webservices given as links on this page. This data compilation includes sample and bibliographic links. The data structure currently supports summary ages (e.g., U-Pb and Ar/Ar) through the INTERPRETED_AGES tables, as well as extended system-specific tables for Sm-Nd, Pb-Pb, Lu-Hf and O- isotopes. The data structure is designed to be extensible to adapt to evolving requirements for the storage of isotopic data. ISOTOPE and the data holdings were initially developed as part of the Exploring for the Future (EFTF) program. During development of ISOTOPE, some key considerations in compiling and storing diverse, multi-purpose isotopic datasets were developed: 1) Improved sample characterisation and bibliographic links. Often, the usefulness of an isotopic dataset is limited by the metadata available for the parent sample. Better harvesting of fundamental sample data (and better integration with related national datasets such as Australian Geological Provinces and the Australian Stratigraphic Units Database) simplifies the process of filtering an isotopic data compilation using spatial, geological and bibliographic criteria, as well as facilitating ‘audits’ targeting missing isotopic data. 2) Generalised, extensible structures for isotopic data. The need for system-specific tables for isotopic analyses does not preclude the development of generalised data-structures that reflect universal relationships. GA has modelled relational tables linking system-specific Sessions, Analyses, and interpreted data-Groups, which has proven adequate for all of the Isotopic Atlas layers developed thus far. 3) Dual delivery of ‘derived’ isotopic data. In some systems, it is critical to capture the published data (i.e. isotopic measurements and derived values, as presented by the original author) and generate an additional set of derived values from the same measurements, calculated using a single set of reference parameters (e.g. decay constant, depleted-mantle values, etc.) that permit ‘normalised’ portrayal of the data compilation-wide. 4) Flexibility in data delivery mode. In radiogenic isotope geochronology (e.g. U-Pb, Ar-Ar), careful compilation and attribution of ‘interpreted ages’ can meet the needs of much of the user-base, even without an explicit link to the constituent analyses. In contrast, isotope geochemistry (especially microbeam-based methods such as Lu-Hf via laser ablation) is usually focused on the individual measurements, without which interpreted ‘sample-averages’ have limited value. Data delivery should reflect key differences of this kind.

A 3D map of the Cooper Basin region has been produced over an area of 300 x 450 km to a depth of 20 km. The 3D map was constructed from 3D inversions of gravity data using geological data to constrain the inversions. It delineates regions of low density within the basement of the Cooper/Eromanga Basins that are inferred to be granitic bodies. This interpretation is supported by a spatial correlation between the modelled bodies and known granite occurrences. The 3D map, which also delineates the 3D geometries of the Cooper and Eromanga Basins, therefore incorporates both potential heat sources and thermally insulating cover, key elements in locating a geothermal play. This study was conducted as part of Geoscience Australia's Onshore Energy Security Program, Geothermal Energy Project.

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.

Demand for critical raw materials is expected to accelerate over the next few decades due to continued population growth and the shifting consumption patterns of the global economy. Sedimentary basins are important sources for critical raw materials and new discoveries of sediment–hosted Mississippi Valley–type (MVT) and/or clastic–dominated (CD) Zn–Pb deposits are likely required to mitigate future supply chain disruptions for Zn, Pb, Ag, Cd, Ga, Ge, Sb, and In. Herein we integrate public geoscience datasets using a discrete global grid to system to model the mineral potential for MVT and CD deposits across Canada, the United States of America, and Australia. Statistical analysis of the model results demonstrates that surface–wave tomography and derivative products from satellite gravity datasets can be used to map the most favourable paleo–tectonic settings of MVT and CD deposits inboard of orogenic belts and at the rifted edges of cratonic lithosphere, respectively. Basin development at pre–existing crustal boundaries was likely important for maintaining the low geothermal–gradients that are favourable for metal transport and generating the crustal fluid pathways that were reactivated during ore–formation, as suggested by the statistical association of both sediment–hosted mineral deposit types with the edges of upward–continued gravity and long–wavelength magnetic anomalies. Multivariate statistical analysis demonstrates that the most prospective combination of these geophysical datasets varies for each geological region and deposit type. We further demonstrate that maximum and minimum geological ages, coupled with Phanerozoic paleogeographic reconstructions, represent mappable proxies for the availability of oxidized, brine–generating regions that are the most likely source of ore–forming fluids (e.g., low– to mid–latitude carbonate platforms and evaporites). Ore deposition was likely controlled by interaction between oxidized, low–temperature brines and sulfidic and/or carbonaceous rocks, which, in some cases, can be mapped at the exposed surface or identified using the available rock descriptions. Baseline weights–of–evidence models are based on regional geophysics and are the least impacted by missing surface information but yield relatively poor results, as demonstrated by the low area–under–the–curve (AUC) for the spatially independent test set on the success–rate plot (AUC = 0.787 for MVT and AUC = 0.870 for CD). Model performance can be improved by: (1) using advanced methods that were trained and validated during a series of semi–automated machine learning competitions; and/or (2) incorporating geological and geophysical datasets that are proxies for each component of the mineral system. The best–performing gradient boosting machine models yield higher AUC for the test set (AUC = 0.983 for MVT and AUC = 0.991 for CD) and reduce the search space by >94%. The model results highlight the potential benefits of mapping sediment–hosted mineral systems at continental scale to improve mineral exploration targeting for critical raw materials.

These data comprises the 3D geophysical and geological map of the Georgina-Arunta region, Northern Territory. This 3D map summarises the key basement provinces of this region, including the geometric relationships between these provinces. Depth of cover data, and approximate thicknesses of key basins within the region are also provided. Supporting geophysical studies, including inversions of gravity and magnetic data, and seismic data and their corresponding interpretations acquired under the Australian Government's Onshore Energy Security Program, are included with this 3D map. Finally, additional data, such as topographic data, are also included.

This study brings together a wide range of datasets to provide a comprehensive assessment of the Pandurra Formation sedimentology and geochemistry in 3D. Sedimentology and geochemistry datasets generated this study are combined with pre-existing data to generate a 3D interpretation of the Pandurra Formation and improve understanding of how the Pandurra formation as we see it to today was deposited and subsequently post-depositionally mineralised.

The Cooper Basin is an upper Carboniferous-Middle Triassic intracratonic basin in northeastern South Australia and southwestern Queensland (Gravestock et al., 1998; Draper, 2002; McKellar, 2013; Carr et al., 2016; Hall et al., 2015a). The basin is Australia's premier onshore hydrocarbon producing province and is nationally significant in providing gas to the eastern Australian gas market. The basin also hosts a range of unconventional gas play types within the Permian Gidgealpa Group, including basin-centred gas and tight gas accumulations, deep dry coal gas associated with the Patchawarra and Toolachee formations, the Murteree and Roseneath shale gas plays and deep coal seam gas in the Weena Trough (e.g. Goldstein et al., 2012; Menpes et al., 2013; Greenstreet, 2015). The principal source rocks for these plays are the Permian coals and coaly shales of the Gidgealpa Group (Boreham & Hill, 1998; Deighton et al., 2003; Hall et al., 2016a). Mapping the petroleum generation potential of these source rocks is critical for understanding the hydrocarbon prospectivity of the basin. Geoscience Australia, in conjunction with the Department of State Development, South Australia and the Geological Survey of Queensland, have recently released a series of studies reviewing the distribution, type, quality, maturity and generation potential of the Cooper Basin source rocks (Hall et al., 2015a; 2016a; 2016b, 2016c; 2016d). Petroleum systems models, incorporating new Cooper Basin kinetics (Mahlstedt et al., 2015), highlight the variability in burial, thermal and hydrocarbon generation histories for each source rock across the basin (Hall et al., 2016a). A Geoscience Australia record 'Cooper Basin Petroleum Systems Analysis: Regional Hydrocarbon Prospectivity of the Cooper Basin, Part 3' providing full documentation of the model input data, workflow and results is currently in press. This work provides important insights into the hydrocarbon prospectivity of the basin (Hall et al., 2015b; Kuske et al., 2015). This product contains the working Cooper Basin Trinity-Genesis-KinEx petroleum systems model used to generate the results presented in these studies. This includes maps describing thickness, TOC and original HI for the following Permian source intervals: Toolachee Fm coals and coaly shales Daralingie Fm coals and coaly shales Roseneath Shale Epsilon Fm coals and coaly shales Murteree Shale Patchawarra Fm coals and coaly shales This model is designed for use as a regional scale hydrocarbon prospectivity screening tool. Model resolution is not high enough for this product to be used for sub-basin to prospect scale analysis, without further modification. However, the model provides a regional framework, into which more detailed prospect scale data may be embedded. The systematic workflow applied demonstrates the importance of integrated geochemical and petroleum systems modelling studies as a predictive tool for understanding the petroleum resource potential of Australia's sedimentary basins.