The Layered Geology of Australia web map service is a seamless national coverage of Australia’s surface and subsurface geology. Geology concealed under younger cover units are mapped by effectively removing the overlying stratigraphy (Liu et al., 2015). This dataset is a layered product and comprises five chronostratigraphic time slices: 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. The Cenozoic time slice layer for the national dataset was extracted from Raymond et al., 2012. Surface Geology of Australia, 1:1 000 000 scale, 2012 edition. Geoscience Australia, Canberra.

The Layered Geology of Australia web map service is a seamless national coverage of Australia’s surface and subsurface geology. Geology concealed under younger cover units are mapped by effectively removing the overlying stratigraphy (Liu et al., 2015). This dataset is a layered product and comprises five chronostratigraphic time slices: 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. The Cenozoic time slice layer for the national dataset was extracted from Raymond et al., 2012. Surface Geology of Australia, 1:1 000 000 scale, 2012 edition. Geoscience Australia, Canberra.

The Officer Basin spanning South Australia and Western Australia is the focus of a regional stratigraphic study being undertaken as part of the Exploring for the Future (EFTF) program, an Australian Government initiative dedicated to increasing investment in resource exploration in Australia. Despite numerous demonstrated oil and gas shows, the Officer Basin remains a frontier basin for energy exploration with significant uncertainties due to data availability. Under the EFTF Officer-Musgrave Project, Geoscience Australia acquired new geomechanical rock property data from forty core samples in five legacy stratigraphic and petroleum exploration wells that intersected Paleozoic and Neoproterozoic aged intervals. These samples were subjected to unconfined compressive rock strength tests, Brazilian tensile strength tests and laboratory ultrasonic measurements. Petrophysical properties were also characterised via X-ray computerised tomography scanning, grain density and porosity-permeability analysis. Accurate characterisation of static geomechanical rock properties through laboratory testing is essential. In the modern exploration environment, these datasets are a precompetitive resource that can simplify investment decisions in prospective frontier regions such as the Officer Basin. Appeared in The APPEA Journal 62 S385-S391, 13 May 2022

The Solid Geology of the North Australian Craton web service delivers 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.

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.

<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>

The Neoproterozoic–Paleozoic Officer Basin, located in South Australia and Western Australia, remains a frontier basin for energy exploration with significant uncertainty due to a paucity of data. As part of Geoscience Australia’s Exploring for the Future (EFTF) program, the objective of this study is to derive the petrophysical properties and characterise potential reservoirs in the Neoproterozoic–Cambrian sedimentary succession in the Officer Basin through laboratory testing, and well log interpretation using both conventional and neural network methods. Laboratory measurements of forty-one legacy core samples provide the relationships between gas permeability, Klinkenberg corrected permeability, and nano-scale permeability, as well as grain density, effective and total porosity for various rock types. Conventional log interpretation generates the volume fraction of shale, effective and total porosity from gamma ray and lithology logs. Self-organising map (SOM) was used to cluster the well log data to generate petrophysical group/class index and probability profiles for different classes. Neural network technology was employed to approximate porosity and permeability from logs, conventional interpretation results and class index from SOM modelling. The Neoproterozoic-Cambrian successions have the potential to host both conventional and tight hydrocarbon reservoirs. Neoproterozoic successions are demonstrated to host mainly tight reservoirs with the range in average porosity and geometric mean permeability of 4.77%-6.39% and 0.00087-0.01307 mD, respectively, in the different sequences. The range in average porosity and geometric mean permeability of the potential Cambrian conventional reservoirs is 14.54%-26.38% and 0.341-103.68 mD, respectively. The Neoproterozoic shales have favourable sealing capacities. This work updates the knowledge of rock properties to further the evaluation of the resource potential of the Officer Basin. Published in The APPEA Journal 2022 <b>Citation:</b> Wang Liuqi, Bailey Adam H. E., Carr Lidena K., Edwards Dianne S., Khider Kamal, Anderson Jade, Boreham Christopher J., Southby Chris, Dewhurst David N., Esteban Lionel, Munday Stuart, Henson Paul A. (2022) Petrophysical characterisation of the Neoproterozoic and Cambrian successions in the Officer Basin. <i>The APPEA Journal</i><b> 62</b>, 381-399. https://doi.org/10.1071/AJ21076

This Record presents data collected in July–August 2020 as part of the ongoing Northern Territory Geological Survey–Geoscience Australia SHRIMP geochronology project under the National Collaboration Framework agreement and Geoscience Australia's Exploring for the Future Program. New U–Pb SHRIMP zircon geochronological results derived from eight sedimentary samples from the western Amadeus Basin in the Northern Territory are presented herein. Detrital zircon U–Pb ages were determined from four samples of the Winnall Group: three samples of the Liddle Formation and one of the Puna Kura Kura Formation. Zircon U–Pb ages were also determined from two samples of the Pertaoorrta Group (Cleland Sandstone and Tempe Formation), one sample of the Larapinta Group (Stairway Sandstone) and one sample of the Mereenie Sandstone. <b>Bibliographic Reference:</b> Kositcin N, Verdel C, Normington VJ and Simmons JM, 2021. Summary of results. Joint NTGS–GA geochronology project: western Amadeus Basin, July–August 2020. <i>Northern Territory Geological Survey, Record</i> <b>2021-002</b>.

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.

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.