Interpretation of the Thomson Orogen and its context within the Tasmanides of eastern Australia is hampered by vast areas of deep sedimentary cover which also mask potential relationships between central and eastern Australia. Within covered areas, basement drill cores offer the only direct geological information. This study presents new detrital zircon isotopic data for these drill cores and poorly understood outcropping units to provide new age and provenance information on the Thomson Orogen. Two distinct detrital zircon signatures are revealed. One is dominated by Grenvillian-aged (1300900 Ma) zircons with a significant peak at ~1180 Ma and lesser peak at ~1070 Ma. These age peaks, along with Lu-Hf isotopic compositions (median Hf(t) = +1.5), dominantly mantle-like 18O values (median = 5.53) and model ages of ~1.89 Ga, support a Musgrave Province (central Australia) source. The dominance of Grenvillian-aged material additionally points to deposition during the Petermann Orogney (570530 Ma) when the Musgrave Province was uplifted shedding abundant material to the Centralian Superbasin. Comparable age spectra suggest that parts of the Thomson Orogen were connected to the Centralian Superbasin during this period. We use the term `Syn-Petermann to describe this signature which is observed in two drill cores adjacent to the North Australian Craton and scattered units in the outcropping Thomson Orogen. The second signature marks a significant provenance shift and is remarkably consistent throughout the Thomson Orogen. Age spectra exhibit dominant peaks at 600560 Ma, lesser 1300900 Ma populations and maximum depositional ages of ~496 Ma. This pattern is termed the `Pacific Gondwana detrital zircon signature and is recognised throughout eastern Australia, Antarctica and central Australia. LuHf isotope data for Thomson Orogen rocks with this signature is highly variable with Hf(t) values between -49 and +10 and dominantly supracrustal 18O values suggesting input from different and more diverse source regions.

This report presents key results of groundwater level interpretations from the Upper Burdekin Groundwater Project in North Queensland, conducted as part of Exploring for the Future (EFTF)—an eight year, $225 million Australian Government funded geoscience data and information acquisition program focused on better understanding the potential mineral, energy and groundwater resources across Australia. The Upper Burdekin Groundwater Project is a collaborative study between Geoscience Australia and the Queensland Government. It focuses on basalt groundwater resources in two geographically separate areas: the Nulla Basalt Province (NBP) in the south and the McBride Basalt Province (MBP) in the north. This report interprets groundwater levels measured in both provinces by Geoscience Australia and the Queensland Government to provide recommendations for resource management. The NBP and MBP basalt aquifers are heterogeneous, fractured, vesicular systems. Several lava flows are mapped at surface in both provinces, and the degree of hydraulic connectivity between these flows is unclear. Although there was some uncertainty due to monitoring well construction issues, barometric efficiency analyses from supporting project documents suggest that the basalts of the NBP and MBP were unconfined where monitored during the EFTF project. That finding generally matches observations presented here. Longer term groundwater hydrographs suggest that groundwater levels have been declining in the NBP and MBP following major flooding in 2010-2011 related to one of the strongest La Niña events on record. Groundwater levels are yet to decline to pre-flood elevations in places. Importantly, these longer term hydrographs set the project in context: the EFTF monitoring period is only a small fraction of a much longer-functioning, dynamic groundwater system. Nulla Basalt Province The NBP is elongated east-west, and is situated entirely within the Burdekin River catchment. Volcanic vents in the west identify that area as the main extrusive centre. Regionally, groundwater migrates through the basalts of the NBP from the western high ground towards the Burdekin River in the east. Although lava flows of the NBP reach the Burdekin River, direct groundwater discharge in this area has not yet been proven. However, groundwater does discharge to various springs and surface watercourses in the NBP that are known tributaries of the Burdekin River. Despite the presence of many registered extraction bores, no clear signs of pumping were observed in groundwater hydrographs from the NBP during the EFTF monitoring period. Water levels in many bores responded to major rainfall events, ranging from a simple change in declining hydrograph slope to a water level increase of ~6.8 m in the central west. While some responses could have been induced by loading, electrical conductivity loggers and the extent of water level rise showed that many were clearly caused by recharge. At nested monitoring locations, groundwater levels remained commensurate with downward flow potentials throughout the EFTF monitoring period. McBride Basalt Province The MBP is approximately circular in plan, with volcanic vents present in a north-northeast trending band through the province centre. Lava flows extend away from the high ground of the province centre towards lower ground near the edges. In part due to its geometry, the MBP is situated within four river catchments; only surface water landing in the east flows into the Burdekin River. Regionally, groundwater migrates through the basalts of the MBP from the central high ground radially towards the edges. Direct groundwater discharge from the MBP basalts into the Burdekin River has been shown in this project. Similarly to the NBP, groundwater is also known to discharge to numerous springs and surface watercourses in the MBP. Water levels in many bores responded to major rainfall events. Responses ranged from a change in declining hydrograph slope to a water level increase of ~6.8 m in the southeast. While some responses could have been induced by loading, the extent of water level rise showed that others were clearly caused by recharge. No nested monitoring locations were installed for the EFTF project, so vertical head gradients are currently unknown. Although there are numerous registered extraction bores in the MBP, groundwater level response to pumping was only definitively identified in the east in bore RN12010016. However, several registered bores with high estimated yields have been installed in the northeast since EFTF fieldwork completion. It is possible that these higher yielding extraction bores may induce visible drawdown in monitoring bores in the future. Their high estimated yields may be associated with lava tubes; features not reported in the literature reviewed for this project for the NBP, but identified at surface and potentially in several Queensland Government bores drilled in the MBP. Conclusions and recommendations The Upper Burdekin Groundwater Project has provided abundant information on various aspects of the hydrogeology of the Nulla and McBride basalt provinces. General groundwater flow processes are understood at a regional scale for the EFTF monitoring period, but more detailed investigations and longer term monitoring are required to fully evaluate local conditions. One of the main observations of this study are the long term groundwater level declines in both the NBP and MBP following the 2010-2011 La Niña-associated floods. Groundwater levels are yet to reduce to pre-flood elevations in places, showing that the EFTF monitoring period represents only a small fraction of a much longer-functioning, dynamic groundwater system. It is unclear what, if any, contribution groundwater extraction has made to regional water level declines. Numerous correlations were assessed between groundwater hydrograph characteristics and potentially influencing factors, but the results were mostly inconclusive. There is uncertainty in hydraulic connectivity across lava flow boundaries and between intra-lava flow aquifers. Although interesting groundwater processes were identified at many bores, at the current bore spacing it is not generally possible to interpolate between locations with any certainty. Knowledge gaps and suggestions for further investigation are recorded in Section 5 of the report. The gaps identified should assist planning of future work to inform: - Further characterisation of groundwater resources. - Protection of groundwater dependent ecosystems. - Appropriate groundwater resource management.

<p>The outcrop extent of the McBride Basalt Province, selected from the Queensland Detailed Surface Geology vector polygon mapping, March 2017. <p>© State of Queensland (Department of Natural Resources and Mines) 2017 Creative Commons Attribution

<p>Geoscience Australia (GA) generated a series of gravity and magnetic grids and enhancements covering Northern Australia. Several derivative gravity datasets have been generated 1) for the North-West Shield Western Australia region (approximately between latitudes 7‒26⁰ S and longitudes 110‒130⁰ E), 2) for the Northern Territory (approximately between latitudes 7‒26⁰ S and longitudes 125.5‒141⁰ E) and for Queensland (approximately between latitudes 7‒30⁰ S and longitudes 135‒160⁰ E). The magnetic dataset has been generated only for the North-West Shield Western Australia region (approximately between latitudes 7‒26⁰ S and longitudes 110‒130⁰ E). The magnetic and gravity data were downloaded from the Geophysical Archive Data Delivery System (GADDS), website (http://www.geoscience.gov.au/cgi-bin/mapserv?map=/nas/web/ops/prod/apps/mapserver/gadds/wms_map/gadds.map&mode=browse). Satellite Free-air (FA) gravity v27.1 (released March 11, 2019) and Satellite Topography v19.1 (released January 14, 2019) data were sourced from Sandwell et al. (2014) and downloaded from the Scripps Institution of Oceanography (SIO), National Oceanic and Atmospheric Administration (NOAA), U.S. Navy and National Geospatial-Intelligence Agency (NGA) (SIO Satellite Geodesy, website, http://topex.ucsd.edu/WWW_html/mar_grav.html). The Satellite Bouguer gravity grid with onshore correction density of 2.67 gcm-3 and offshore correction density of 2.20 gcm-3 was derived from the Free-air gravity v27.1 and Topography data V19.1. This Bouguer gravity grid was used for filling areas of data gaps in the offshore region. <p>Data evaluation and processing of gravity and magnetic data available in the area of interest resulted in the production of stitched onshore-offshore Bouguer gravity grid derived from offshore satellite Bouguer gravity grid and GA’s onshore ground and airborne gravity survey data and a stitched Total Magnetic Intensity (TMI) grid derived from airborne and shipborne surveys (Tables 1 and 5). A Reduction to the Pole (RTP) grid was derived from the stitched TMI grid. The TMI, RTP, FA and terrain corrected Bouguer gravity anomalies are standard datasets for geological analysis. The free-air gravity anomaly provides the raw and basic gravity information. Images of free-air gravity are useful for first-pass interpretation and the data is used for gravity modelling. Magnetic anomalies provide information on numerous magnetic sources, including deep sources as arising from the structure and composition of magnetic basement and shallow sources such as intra-sedimentary magnetic units (e.g. volcanics, intrusions, and magnetic sedimentary layers). A standard TMI image will contain information from all these sources. Geosoft Oasis montaj software was used throughout the data processing and enhancement procedure and the montaj GridKnit module was used to generate the stitched gravity and magnetic grids. <p>Enhancement techniques have been applied to the final processed Bouguer gravity and RTP magnetic grids to highlight subtle features from various sources and to separate anomalies from different source depths. These enhancement techniques are described in the next section. <p>Enhancement processing techniques and results <p>A summary of image processing techniques used to achieve various outcomes is described in Table 1. <p>Data type Filter applied Enhancement/outcome <p>Gravity/Magnetic First vertical derivative (1VD) Near surface features (e.g. intrabasinal) <p>Gravity/Magnetic Upward continuation Noise reduction in data <p>Gravity/Magnetic Low pass filter, or large distance upward continuation Enhancement of deep features (e.g. basement) <p>Gravity/Magnetic High pass filter Enhancement of shallow features (e.g. surface anomalies) <p>Gravity/Magnetic Tilt filter and 1VD Enhancement of structure (e.g. in basement) <p>Gravity/Magnetic ZS-Edgezone and ZS-Edge filters Enhancement of edges <p>Gravity/Magnetic horizontal modulus / horizontal gradient Enhancement of boundaries <p>Magnetic RTP (reduction to the pole), Compound Anomaly, and Analytic Signal filter Accurate location of sources

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.

Queensland Fire and Emergency Services are leading the development of consistent risk information relating to the potential impacts of disasters across Queensland. The stated aim is to ensure all local, district and state government stakeholders have access to the same information to guide risk-based planning in the preparation for natural disasters. This extends to future projections natural hazard activity, including tropical cyclones (TC), in the Queensland region. To achieve this last objective, Queensland’s Department of Environment and Science (DES) have undertaken a program of regional climate simulations, with a view to informing long-term planning decisions. When it comes to TCs – a major cause of disasters in Queensland – many of the stakeholders want to answer the question: “How many severe tropical cyclones will the future hold for us?”, or similar questions around the likelihood of TC occurrence. To answer this, DES and Geoscience Australia are interrogating the regional climate simulations to extract Tropical Cyclone-Like Vortices (TCLVs). The behaviour of these TCLVs is then analysed to understand changes in frequency, intensity and spatial distribution. The TCLVs – with some additional bias corrections - can also be used as input to stochastic models that can provide probabilistic wind hazard information across the entire state of Queensland. In this paper we demonstrate the challenges of extracting TCLVs from regional climate models and the bias corrections required to make useful projections of TC activity into the future. Abstract presented at the 2020 Australian Meteorological and Oceanographic Society 2020 National Conference (http://amos-2020.w.amos.currinda.com/)

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.

The geology and mineral prospectivity of the southern Thomson Orogen is poorly understood because the vast majority of its extent is buried beneath younger regolith and/or sedimentary rocks. To address this issue a collaborative program to drill 16 stratigraphic boreholes was proposed to collect samples of the basement geology that can be comprehensively analysed to improve the understanding of the geological evolution of this region. To reduce the uncertainty associated with intersecting the target stratigraphy at each of the borehole sites, estimates of the cover thickness were obtained by applying the geophysical techniques of refraction seismic, audio-magnetotellurics (AMT) and targeted magnetic inversion modelling (TMIM) prior to drilling. Refraction seismic was acquired at all 16 proposed borehole sites using a system with 48 single-component geophones and a propelled weight drop primary-wave source. At 14 of the sites clear basement refractors were observed in the data. At the two other sites, Nantilla 1 and Barrygowan 1, loss of signal due to seismic attenuation at far offsets meant that a clear basement refractor was not observed. With the exception of these two sites, three distinct refractors are generally observed in the data. Those with velocities ranging from 0.4 km/s to 1.5 km/s are interpreted as regolith, those ranging from 1.8 km/s to 2.4 km/s are interpreted as Eromanga Basin sediments, and those ranging from 3.9 km/s to 5.7 km/s are interpreted as metamorphic/igneous basement. Two-dimensional velocity models of the subsurface geology were then generated using the time-term inversion method, which allowed for the thickness of each layer to be estimated. Cover thickness estimates using refraction data vary widely from site to site, with the shallowest estimate being Overshot 1 (49 m - 55 m) and the deepest Adventure Way 1 (295 m - 317 m). These variations in cover thickness estimates from site to site are indicative of basement topography variations and are not error margins. Audio-magnetotelluric data was collected at ten sites by simultaneously deploying four porous pot electrodes, to collect the two orthogonal components of telluric data (Ex and Ey), and three magnetic induction coils, to collect the three components of magnetic data (Hx, Hy and Hz). For each dataset, a one-dimensional inversion model was produced, from which resistivity contrasts were identified and used to describe electrical conductivity discontinuities in the subsurface geology. In general, the models show a near-surface conductive layer with resistivity values ≤10 Ω·m overlying layers with continuously increasing resistivities with depth (up to 102-103 Ω·m). Those layers which were >10 Ω·m were interpreted as metamorphic/igneous basement rocks and were observed to occur at depths of ~100 m to ~300 m across the survey sites, except at Overshot 1 (38 m ±10%) and Barrygowan 1 (480 m ±10%). Targeted magnetic inversion modelling (TMIM) was applied to freely available, good quality, regional airborne magnetic survey data. Depth to magnetic source estimates were generated for 53 targets, with confidence ratings, using a dipping tabular source body to model targeted magnetic anomalies in the vicinity of the borehole sites. A combined depth estimate was generated using a distance and confidence weighted average from multiple depth estimates at all but two borehole sites. Only a single depth estimate was available at Adventure Way 1 while no depth estimates were generated at Eulo 1. These combined depth estimates provide cover thickness estimates at the sites as they are likely sourced from, or near, the top of basement. Of the ten proposed borehole sites with coincident AMT and refraction seismic data, five sites have overlapping cover thickness estimates. Cover thickness estimates from the TMIM overlap both the AMT and refraction data at four sites and at two sites where only the refraction depth estimates were available. 2 Estimating Cover Thickness in the Southern Thomson Orogen The cover thickness estimates presented in this report lower the risks associated with the proposed southern Thomson Orogen stratigraphic drilling program by reducing the uncertainty in intersecting the target stratigraphy at each of the borehole sites as well as allowing for better project and program planning. Successful completion of the stratigraphic drilling program in the southern Thomson Orogen will allow for each of these geophysical methods for estimating cover thickness to be benchmarked using actual cover thicknesses measured in the boreholes.

<div>This document provides metadata for the gross depositional environment (GDE) interpretations that have been generated in support of the energy resource assessments under the Australia’s Future Energy Resources (AFER) project.&nbsp;&nbsp;</div><div>The AFER projects is part of Geoscience Australia’s Exploring for the Future (EFTF) Program—an eight year, $225 million Australian Government funded geoscience data and precompetitive information acquisition program to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia’s geology and resource potential. This will help support a strong economy, resilient society and sustainable environment for the benefit of all Australians. The EFTF program is supporting Australia’s transition to a low emissions economy, industry and agriculture sectors, as well as economic opportunities and social benefits for Australia’s regional and remote communities. Further details are available at http://www.ga.gov.au/eftf.&nbsp;</div><div>The GDE data sets provide high level classifications of interpreted environments where sediments were deposited within each defined play interval in the Pedirka, Simpson and Western Eromanga basins. Twelve gross depositional environments have been interpreted and mapped in the study (Table 1). A total of 14 play intervals have been defined for the Pedirka, Simpson and Western Eromanga basins by Bradshaw et al. (2022, in press), which represent the main chronostratigraphic units separated by unconformities or flooding surfaces generated during major tectonic or global sea level events (Figure 1). These play intervals define regionally significant reservoirs for hydrocarbon accumulations or CO2 geological storage intervals, and often also include an associated intraformational or regional seal.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</div><div>GDE interpretations are a key data set for play-based resources assessments in helping to constrain reservoir presence. The GDE maps also provide zero edges showing the interpreted maximum extent of each play interval, which is essential information for play-based resource assessments, and for constructing accurate depth and thickness grids.&nbsp;&nbsp;</div><div>GDE interpretations for the AFER Project are based on integrated interpretations of well log and seismic data, together with any supporting palynological data. Some play intervals also have surface exposures within the study area which can provide additional published paleo-environmental data. The Pedirka, Simpson and Western Eromanga basins are underexplored and contain a relatively sparse interpreted data set of 42 wells and 233 seismic lines (Figure 2). Well and outcrop data provide the primary controls on paleo-environment interpretations, while seismic interpretations constrain the interpreted zero edges for each play interval. The sparse nature of seismic and well data in the study area means there is some uncertainty in the extents of the mapped GDE’s.&nbsp;&nbsp;</div><div>The data package includes the following datasets:&nbsp;&nbsp;</div><div>Play interval tops for each of the 42 wells interpreted – provided as an ‘xlsx’ file.&nbsp;</div><div>A point file (AFER_Wells_GDE) capturing the GDE interpretation for each of the 14 play intervals in each of the 42 wells – provided as both a shapefile and within the AFER_GDE_Maps geodatabase.&nbsp;</div><div>Gross depositional environment maps for each of the 14 play intervals (note that separate GDE maps have been generated for the Namur Sandstone and Murta Formation within the Namur-Murta play interval, and for the Adori Sandstone and Westbourne Formation within the Adori-Westbourne play interval) – provided as both shapefiles and within the AFER_GDE_Maps geodatabase.&nbsp;</div><div>&nbsp;</div><div>These GDE data sets are being used to support the AFER Project’s play-based energy resource assessments in the Western Eromanga, Pedirka and Simpson basins.&nbsp;</div><div><br></div>

<div>This study investigates the feasibility of mapping potential groundwater dependent vegetation (GDV) at a regional scale using remote sensing data. Specifically, the Digital Earth Australia (DEA) Tasseled Cap Percentiles products, integrated with the coefficient of greenness and/or wetness, are applied in three case study regions in Australia to identify and characterise potential terrestrial and aquatic groundwater dependent ecosystems (GDE). The identified high potential GDE are consistent with existing GDE mapping, providing confidence in the methodology developed. The approach provides a consistent and rapid first-pass approach for identifying and assessing GDEs, especially in remote areas of Australia lacking detailed GDE and vegetation information.</div>