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 web service provides access to datasets generated by the North Australian Craton (NAC) Iron Oxide Copper Gold (IOCG) Mineral Potential Assessment. Two outputs were created: a comprehensive assessment, using all available spatial data, limiting data where possible to capture mineral systems older than 1500 ma, and; a coverage assessment, which is constrained to data that have no reliance on outcrop or age of mineralisation.

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.

As part of the Exploring for the Future program, whole-of-crust 3D gravity and magnetic inversion models have been produced for an area encompassing the North Australia Craton. These models were created to aid 3D geological mapping and identification of large-scale mineral systems such as those associated with iron oxide copper-gold deposits. The inversion models were derived using the University of British Columbia - Geophysical Inversion Facility MAG3D and GRAV3D programs. The inversions were constrained with geological reference models that had layers for Phanerozoic sediments, Proterozoic sediments, undifferentiated crust and the mantle. The reference model for the magnetic inversion incorporated a Curie depth surface below which magnetic susceptibility was set to zero. To allow cross-referencing, both the density and magnetic susceptibility models were designed to occupy the same physical space with identical volumes and cell sizes. A horizontal cell size of 1 km was used with 61 vertical layers, whose thickness increased with depth. The area of interest is 2450 km by 1600 km and extends to a depth of 70 km below the geoid, resulting in a total volume with ~239 million cells. Ultimately, it was not possible to invert a model of this size. Instead, the volume was broken down into a grid of overlapping tiles with 8 rows and 10 columns. Each tile was independently inverted before being recombined into a single coherent output model. When the overall model was reconstructed using the core region of each tile, some low-level edge effects were observed, increasing in significance with depth. These effects were satisfactorily attenuated by applying cosine weighting from the centre of each tile out to the edge of the overlap region during reconstruction. The coincident density and magnetic susceptibility models show a relationship with known iron oxide copper-gold deposits and regions of >2.80 g/cm3 and >0.01 SI in the Tennant Creek and Cloncurry regions. It is suggested that these regions of high-density and high-magnetic susceptibility are related to the magnetite-forming hydrothermal alteration stages of an iron oxide copper-gold deposit. The success of the NAC modelling exercise has demonstrated that this method can be expanded to produce coincident gravity and magnetic inversion models for the entire Australian region. ------------------------------------------------------------------------------------------ DOWNLOADS ------------------------------------------------------------------------------------------ Input Data: The input gravity, magnetic and elevation data (.ers and .tif). Geological Reference Models: The geological reference model as surfaces and 3D volumes (.sg, .ts, and UBCGIF). Observed vs Predicted Data: The input gravity/magnetic data compared to the predicted data (.png). Recombined Models: The recombined (cosine weighted) density and magnetic susceptibility models (.sg, and UBCGIF). Magnetite Proxies: Proxies for magnetite alteration related to IOCG deposits (.ers). Video: Video describing the method and results (.mp4).

Geological maps are one of the most important datasets used in resource exploration and management. Despite increasing demand for subsurface resources such as minerals, groundwater and energy, maps of the inferred subsurface geology of Australia and other continents have been limited to small regions or jurisdictions. Here, we present the first seamless semi-continental chronostratigraphic solid geology dataset of the North Australian Craton. This dataset comprises five time slices of stratigraphic units: Cenozoic, Mesozoic, Paleozoic, Neoproterozoic and pre-Neoproterozoic. Interpretation of covered units is based on available data: surface geology and solid geology maps, magnetic intensity and gravity images, drilling logs, reflection seismic profiles and airborne electromagnetic soundings. In total, 2008 units have been mapped, all linked to the Australian Stratigraphic Units Database. So far, these maps have led to a refinement of sedimentary basin and tectonic province outlines, lessened the risks of mineral exploration through Australia’s extensive superficial cover, disclosed geological units known to host resources elsewhere, and highlighted undercover regions with poor geological constraints. <b>Citation:</b> Stewart, A.J., Liu, S.F., Bonnardot, M.-A., Highet, L.M., Woods, M., Brown, C., Czarnota, K. and Connors, K., 2020. Seamless chronostratigraphic solid geology of the North Australian Craton. 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 fundamental geological framework of the concealed Paleoproterozoic East Tennant area of northern Australia is very poorly understood, despite its relatively thin veneer of Phanerozoic cover and its position along strike from significant Au–Cu–Bi mineralisation of the Tennant Creek mining district within the outcropping Warramunga Province. We present 18 new U–Pb dates, obtained via Sensitive High Resolution Ion Micro Probe (SHRIMP), constraining the geological evolution of predominantly Paleoproterozoic metasedimentary and igneous rocks intersected by 10 stratigraphic holes drilled in the East Tennant area. The oldest rocks identified in the East Tennant area are two metasedimentary units with maximum depositional ages of ca. 1970 Ma and ca. 1895 Ma respectively, plus ca. 1870 Ma metagranitic gneiss. These units, which are unknown in the nearby Murphy Province and outcropping Warramunga Province, underlie widespread metasedimentary rocks of the Alroy Formation, which yield maximum depositional ages of 1873–1864 Ma. While parts of this unit appear to be correlative with the ca. 1860 Ma Warramunga Formation of the Warramunga Province, our data suggest that the bulk of the Alroy Formation in the East Tennant area is slightly older, reflecting widespread sedimentation at ca. 1870 Ma. Throughout the East Tennant area, the Alroy Formation was intruded by voluminous 1854–1845 Ma granites, contemporaneous with similar felsic magmatism in the outcropping Warramunga Province (Tennant Creek Supersuite) and Murphy Province (Nicholson Granite Complex). In contrast with the outcropping Warramunga Province, supracrustal rocks equivalent to the 1845–1810 Ma Ooradidgee Group are rare in the East Tennant area. Detrital zircon data from younger sedimentary successions corroborate seismic evidence that at least some of the thick sedimentary sequences intersected along the southern margin of the recently defined Brunette Downs rift corridor are possible age equivalents of the ca. 1670–1600 Ma Isa Superbasin. Our new results strengthen ca. 1870–1860 Ma stratigraphic and ca. 1850 Ma tectono-magmatic affinities between the East Tennant area, the Murphy Province, and the mineralised Warramunga Province around Tennant Creek, with important implications for mineral prospectivity of the East Tennant area. Appeared in Precambrian Research Volume 383, December 2022.

This web service provides access to datasets generated by the North Australian Craton (NAC) Iron Oxide Copper Gold (IOCG) Mineral Potential Assessment. Two outputs were created: a comprehensive assessment, using all available spatial data, limiting data where possible to capture mineral systems older than 1500 ma, and; a coverage assessment, which is constrained to data that have no reliance on outcrop or age of mineralisation.

This web service provides access to datasets generated by the North Australian Craton (NAC) Iron Oxide Copper Gold (IOCG) Mineral Potential Assessment. Two outputs were created: a comprehensive assessment, using all available spatial data, limiting data where possible to capture mineral systems older than 1500 ma, and; a coverage assessment, which is constrained to data that have no reliance on outcrop or age of mineralisation.

Australia has a significant number of surface sediment geochemical surveys that have been undertaken by industry and government over the past 50 years. These surveys represent a vast investment and have up to now only been able to be used in isolation, independently from one another. The key to maximising the full potential of these data and the information they provide for mineral exploration, environmental management and agricultural purposes is using all the surveys together, seamlessly. These disparate geochemical surveys not only sampled various landscape elements and analysed a range of size fractions, but also used multiple analytical techniques, instrument types and laboratories. The geochemical data from these surveys require levelling to eliminate, as much as possible, non-geological variation. Using a variety of methodologies, including reanalysis of both international standards and small subsets of samples from previous surveys, we have created a seamless surface geochemical map for northern Australia, from nine surveys with 15,605 samples. We tested our approach using two surveys from the southern Thomson Orogen, which demonstrated the successful removal of inter-laboratory and other analytical variation. Creation of the new combined and levelled northern Australian dataset paves the way for the application of statistical and data analytics techniques, such as principal component analysis and machine learning, thereby maximising the value of these legacy data holdings. The methodology documented here can be applied to additional geochemical datasets as they become available.

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.