To be technically viable, a geothermal energy prospect has two requirements: sufficiently high temperatures at economically-accessible depths; and a viable reservoir from which to extract the heat by flowing fluid at a suitable rate. In recent years, Geoscience Australia (GA) has applied conductive thermal modelling to 3D geological maps to improve predictive targeting of elevated temperatures in the Australian crust. GA is developing capability to improve targeting of favourable reservoir characteristics, using a combination of geothermal modelling techniques, and the use of geophysical and other geoscience data. GA's assessments of crustal temperature potential have incorporated temperature measurements, heat flow data, thermal conductivity measurements and heat production estimates based on geochemistry data. They have also incorporated other datasets such as outcrop geology, drillhole intersections, seismic and gravity data. GA's initial assessment of North Queensland was qualitative and based on a 2D GIS approach. Subsequent assessments were quantitative and based on 3D thermal models, however, due to computational restrictions; uncertainty in the temperature predictions was assessed only qualitatively. More recently, thermal modelling was conducted on a 3D geological map of the Cooper Basin region in South Australia and Queensland (Meixner et al., 2012) using the SHEMAT software (Clauser, 2003). Uncertainty in the temperature predictions was estimated via a Monte-Carlo based approach using the National Computational Infrastructure (NCI) at the Australian National University. The second requirement for a viable geothermal energy prospect is reservoir potential. GA is developing capability to identify reservoir potential using two related approaches. The first involves use of the TOUGH2-MP reservoir modelling code on the NCI. This code will be used to simulate fluid-flow in synthetic geothermal reservoirs with varying geometries and permeability structures, to identify the most desirable characteristics. The second approach involves application of geophysical methods to improve predictive targeting of geothermal reservoirs. GA has used numerical modelling techniques to improve predictive targeting of elevated crustal temperatures and is now building capability to assist predictive targeting of favourable reservoir characteristics. This will allow new geothermal targets to be identified based on the two geological requirements for a successful geothermal prospect. By applying this approach on a national scale, GA will be able to provide an integrated, Australia-wide assessment of geothermal potential. Clauser, C. (ed.), 2003. Numerical Simulation of Reactive Flow in Hot Aquifers: SHEMAT and Processing SHEMAT. Springer-Verlag: Berlin Heidelberg. Meixner, A.J., Kirkby, A.L., Lescinsky, D.T., and Horspool, N., 2012b. The Cooper Basin 3D Map Version 2: Thermal modelling and temperature uncertainty. Record 2012/60. Geoscience Australia: Canberra.

Heat flow data across Australia are sparse, with around 150 publicly-available data-points. The heat flow data are unevenly distributed and mainly come from studies undertaken by the Bureau of Mineral Resources (BMR) and the Research School Earth Sciences at the Australian National University in the 1960s and 1970s. Geoscience Australia has continued work started under the federally-funded Onshore Energy Security Program (OESP), collecting data to add to the heat flow coverage of the continent. This report presents temperature, natural gamma and thermal conductivity data for eight boreholes across Australia. Temperature logging was performed down hole with temperatures recorded at intervals less than 20 cm. Samples of drill core were taken from each well and measured for thermal conductivity at Geoscience Australia. One dimensional, conductive heat flow models for the boreholes are presented here. These new determinations will add to the 53 already released by Geoscience Australia under the OESP, totalling 61 determinations added to the Australian continental heat flow dataset since 2007.

A new approach for developing a 3D temperature map of the Australian continent is currently being developed that relies on combining available proxy data using high-performance computing and large continental-scale datasets. The new modelling approach brings together the current national-scale knowledge of datasets collected by Geoscience Australia and others, including AusMoho, OZTemp, OzSeebase, OZCHEM, surface temperature, the Surface Geology of Australia, sedimentary basins' thermal conductivity and the National Gravity Map of Australia. Bringing together such a range of datasets provides a geoscientific basis by which to estimate temperature in regions where direct observations are not available. Furthermore, the performance of computing facilities, such as the National Computational Infrastructure, is enabling insights into the nature of Australia's geothermal resources which had not been previously available. This should include developing an understanding of the errors involved in such a study through the quantification of uncertainties. Currently the new approach is being run as a pilot study however, initial results are encouraging. The pilot study has been able to reproduce the temperature trends observed in areas that have been heavily constrained by bore-hole observations. Furthermore, a number of areas have now been identified, due to the difference in their estimated temperature from previous methods, which warrant further study.

Geothermal energy is a renewable energy technology reported to have a large potential resource base. However, existing geothermal data for Australia (borehole temperatures and heat flow determinations), are limited and collection of additional data is both time consuming and restricted to accessing to wells drilled for other purposes. It is therefore important to develop "deposit" or resource models to aid exploration; improving the quality of subsurface thermal estimates, and helping to identify the distal footprints of geothermal systems. Conceptually, the fundamental requirements of a geothermal system are well understood. However, the complex interplay between the various elements makes it difficult to compare different geographical regions and to assess their relative prospectively. As such, the results of some 130,000 synthetic thermal-modelling runs have been used to calibrate a new tool called the 'Geothermal Calculator'. The Calculator acts as an emulator, or surrogate model, falling into a class of functions which seek to approximate the input / output behaviour of more-complex systems. This presentation will explore the mechanics of the Calculator, before examining some of its possible uses; from simple point-spot estimates to the broader continental scale. The functionality of the Geothermal Calculator presents a significant step forward in our ability to produce subsurface temperature estimates, and represents a notable milestone in the pathway to realising our subsurface geothermal energy potential.

3D constrained gravity inversions have been applied to gravity data in the Cooper Basin region of South Australia to delineate low density regions within the basement, beneath thick sequences of sedimentary cover. The low density regions, which are interpreted as granite bodies, may act as heat sources beneath thermally insulating sediments, thereby enhancing geothermal prospectivity. The Cooper Basin is the site of Australia's first geothermal project , where elevated crustal temperatures result from high-heat producing granites of the Big Lake Suite beneath the basin sediments. A 3D map of sediment stratigraphy was populated with densities and used to constrain the contribution of low density cover sediments to the observed gravity field. The resulting constrained density inversion model produced low density regions in the basement that coincide with local gravity lows. Further gravity inversions were generated and combined with gravity worm data to constrain the lateral and vertical extent of these discrete low density regions which we interpret as granite bodies. These Interpreted Granite Bodies (IGBs) coincide with granites intersected in wells. Analyses of a regional thermal model generated for a previous study, indicate that extra heat-production is required in the regions of the model that coincide with a number of the IGBs. Further thermal modelling was undertaken to determine the heat production differential between these high-heat producing IGBs and the surrounding basement. Two regions were identified where the high-heat producing IGBs are located beneath thick sequences of thermally insulating sediments. These regions, located to the east of the Big Lake Suite granodiorite and in the centre of the study area coinciding with the Barrolka gravity low, are considered to have high geothermal prospectivity.

The Virtual Geophysics Laboratory (VGL) is an environment that was developed as a data discovery and delivery facility with software and computing facilities. This design enables geoscientists to store, discover, retrieve and process datasets. Recent developments are expanding the VGL to incorporate the functionality of the Underworld software. Underworld is open source, parallel software capable of calculating the 3D temperature distribution in the crust. Numerical modelling of temperature is a tool that can be used to predict the temperature distribution at depth between and beneath measurement points based on a 3D geological map. Computing models on a regional scale tends to be computationally intensive, and high-performance computing (HPC) facilities are often required to run computations at full resolution. In order to assess uncertainty quantitatively, HPC facilities are almost always a requirement. The new developments to VGL will facilitate the discovery and access to 3D geological maps. It will also provide easier access to the Underworld software, and will provide the high performance and cloud computing facilities (hosted at the National Computing Infrastructure and elsewhere) required to run large models. The metadata associated with each run performed using VGL is automatically stored, and therefore runs completed on VGL will be repeatable and testable.

A new approach for developing a 3D temperature map of the Australian continent has been trialled that combines available proxy data using high-performance computing and large continental-scale datasets. The Thermal Map from Assessed Proxies (TherMAP) is a new 3D modelling approach that brings together up-to-date national-scale datasets. Bringing together such a range of datasets provides a geoscientific basis by which to estimate temperature in regions where direct observations are not available. Furthermore, the National Computational Infrastructure (NCI) is enabling insights into the nature of Australia's geothermal resources that had not been previously available.

This map presents radiogenic crustal heat production values calculated from available geochemical data from basement rock exposures from across the Australian Antarctic Territory (AAT). Heat production is derived from the radiogenic decay of the radioactive elements, primarily, U, Th and K. This map, along with the companion GA record (2012/63), highlights the magnitude and heterogeneity of crustal heat production across the AAT, and provides earth scientists with the first crustal heat production assessment across much of East Antarctica. Crustal heat production values across the AAT show a wide range from negligible to as much as 65 'Wm-3. Generally, elevated heat production values are characteristic of Cambrian felsic intrusives, with intermediate values from Proterozoic intrusive and metasediments (2-8 Wm-3), and low values (<2 'Wm-3) from Archean rocks. A good illustration of the correlation of geological age with heat production is from Prydz Bay (map 5), where the Vestfold Hills (mostly ~2500 Ma in age) exhibits uniformly low heat production (average ~0.8 'Wm-3), whereas Proterozoic rocks south of the Vestfold Hills have intermediate values (average ~2.6 'Wm-3). Cambrian intrusives, in contrast, have significantly elevated values (average ~15 'Wm-3). We anticipate that this simple compilation of crustal heat production may form a basis for future studies on the thermal structure of the East Antarctic crust, in particular, sub-glacial heat flow, which remains a critical, yet poorly characterised, boundary parameter controlling the dynamic behaviour of the vast Antarctic ice sheet. For further information and data tables, the reader is referred to 'A reconnaissance crustal heat production assessment of the Australian Antarctic Territory (AAT)' by C. J. Carson and M. Pittard, GA record 2012/063 (pp 57), Geocat 74073.

<p>The Geological Survey of South Australia commissioned the Gawler Craton Airborne Survey (GCAS) as part of the PACE Copper initiative. The airborne geophysical survey was flown over parts of the Gawler Craton in South Australia. The program was designed to capture new baseline geoscientific data to provide further information on the geological context and setting of the area for mineral systems (http://energymining.sa.gov.au/minerals/geoscience/pace_copper/gawler_craton_airborne_survey). <p>The survey design of 200 m spaced lines at a ground clearance of 60 m can be compared with the design of previous regional surveys which generally employed 400 m line spacing and a ground clearance of 80 m. The new survey design results in ~2 x the data coverage and ~25% closer to the ground when compared to previous standards for regional surveys in South Australia. <p>Survey blocks available for download include: <p>Streaky Bay, block 5 <p>Gairdner, block 6A <p>Spencer, block 7 <p>Kingoonya, block 9B <p>The following grids are available in this download: <p>• Laser-derived digital elevation model grids (m). Height relative to the Australian Height Datum. <p>• Radar-derived digital elevation model grids (m). Height relative to the Australian Height Datum. <p>• Total magnetic intensity grid (nT). <p>• Total magnetic intensity grid with variable reduction to the pole applied (nT). <p>• Total magnetic intensity grid with variable reduction to the pole and first vertical derivative applied (nT/m). <p>• Dose rate concentration grid (nGy/hr). <p>• Potassium concentration grid (%). <p>• Thorium concentration grid (ppm). <p>• Uranium concentration grid (ppm). <p>• NASVD processed dose rate concentration grid (nGy/hr). <p>• NASVD processed potassium concentration grid (%). <p>• NASVD processed thorium concentration grid (ppm). <p>• NASVD processed uranium concentration grid (ppm). <p>The following point located data are available in this download: <p>• Elevation. Height relative to the Australian Height Datum. Datum: GDA94 <p>• Total Magnetic Intensity. Datum: GDA94 <p>• Radiometrics. Datum: GDA94