Weathering is an important process of the Earth’s surface that has a major influence on the chemical and physical properties of rock and soil. The intensity of this process largely controls the degree to which primary minerals are altered to secondary components, including clay and oxide minerals. The degree of surface weathering is particularly important in Australia, where variations in weathering intensity correspond to differences in the nature and distribution of regolith (weathered bedrock and sediments), which mantles approximately 80% of the Australian continent. Here, I use a random forest decision tree machine learning algorithm to first establish a relationship between field estimates of the degree of weathering and a comprehensive suite of covariate or predictive datasets. I then apply this relationship to generate an improved national model of surface to near-surface weathering intensity. Covariates include satellite imagery, terrain attributes, airborne radiometric imagery and mapped geology. The model performs very well, with an r-squared correlation of 0.85 based on 5 K-fold cross-validation on the mean and standard deviation of 300 random forest models. This new weathering intensity model has broad utility for mineral exploration in variably weathered landscapes, agricultural mapping of chemical and physical soil attributes, ecology, and advancing the understanding of weathering processes within the upper regolith. <b>Citation:</b> Wilford, J., 2020. Revised weathering intensity model of Australia. 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.

Seismological data are used for a variety of purposes, from earthquake hazard zonation to mapping Earth structure and mineral resource exploration. The immense volumes of seismic data now available challenge the application of routine seismic analysis techniques using existing tools. These tools fail to take advantage of recent advances in computing hardware and data formats. Given the scale of data to process and the computational complexity of algorithms involved, a more efficient approach that scales on high-performance computing and data (HPC-HPD) platforms is needed. In addition, different agencies have tended to use bespoke and ad hoc data formats, data curation processes and quality standards, hindering large-scale analyses and modelling. High-performance seismological tools (HiPerSeis) facilitate the transformation of source seismological data into formats geared towards HPC-HPD platforms. HiPerSeis also implements optimised seismological workflows that can be run at large scale on HPC-HPD platforms. <b>Citation:</b> Hassan, R., Hejrani, B., Medlin, A., Gorbatov, A. and Zhang, F., 2020. High-performance seismological tools (HiPerSeis). 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.

Remotely sensed data and updated DEM and radiometric datasets, combined with existing surface material and landform mapping were used to map regolith landform units for the Alice Springs study area of the SSC project. This report describes the methods used and outlines the new mapping.

There is a growing recognition that lithospheric structure places first-order controls on the distribution of resources within the upper crust. While this structure is increasingly imaged using geophysical techniques, there is a paucity of geological constraints on its morphology and temporal evolution. Cenozoic intraplate volcanic rocks along Australia’s eastern seaboard provide a significant opportunity to constrain mantle conditions at the time of their emplacement and thereby benchmark geophysical constraints. This volcanic activity is subdivided into two types: age-progressive provinces generated by the passage of mantle plumes beneath the plate; and age-independent provinces, which may arise from edge-driven convection at a lithospheric step. In this study, we collected and analysed 78 igneous rock samples from both types of volcanoes across Queensland. We combined these analyses with previous studies to create and augment a comprehensive database of Australian Cenozoic volcanism. Geochemical modelling techniques were used to estimate mantle temperatures and lithospheric thicknesses beneath each province. Our results show that melting occurred at depths of 45–70 km across eastern Australia. Mantle temperatures are inferred to be ~50–100 °C higher beneath age-progressive provinces than beneath age-independent provinces. These results agree with geophysical observations used to aid resource assessments and indicate that upper mantle temperatures have varied over Cenozoic times. <b>Citation:</b> Ball, P.W., Czarnota, K., White, N.J. and Champion, D.C. 2020. Exploiting Cenozoic volcanic activity to quantify upper mantle structure beneath eastern Australia. 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.

We present a multifaceted hydrogeological investigation of the McBride and Nulla basalt provinces in the Upper Burdekin region, north Queensland. The project aims to better understand their key groundwater system processes to inform future development and water management decisions. This work, carried out as part of the Exploring for the Future Upper Burdekin Groundwater Project, has shown that basalt aquifers in each province are typically unconfined where monitored. Groundwater recharge is widespread but highly variable, largely occurring within the boundaries of the basalt provinces. Groundwater salinity based on electrical conductivity is <1000 μS/cm in the McBride Basalt Province (MBP) and up to 2000 μS/cm in the Nulla Basalt Province (NBP). Groundwater levels have been declining since 2011 (following major flooding in Queensland), showing that the study period covers a small fraction of a longer-functioning dynamic groundwater system. The basalt provinces contain distinct lava flows, and the degree of hydraulic connectivity between them is unclear. Despite similarities in their rock properties, the geometry of lava emplacement leads to different groundwater flow regimes within the two basalt provinces. Radial flow away from the central high elevations towards the edges is characteristic of the MBP, while regional flow from west to east dominates the NBP. Basalt aquifers in both provinces support a range of groundwater-dependent ecosystems, such as springs, some of which sustain flow in tributaries of the Burdekin River. Where streams intersect basalt aquifers, this also results in direct groundwater discharge. Springs and perennial tributaries, particularly emanating from the MBP, provide important inflows to the Burdekin River, especially in the dry season. This work has highlighted that management of MBP and NBP groundwater sources is crucial for maintaining a range of environmental assets in the region and for ensuring access for existing and future users. <b>Citation:</b> Ransley, T.R., Dixon-Jain, P., Cook, S.B., Lai, E.C.S., Kilgour, P., Wallace, L., Dunn, B., Hansen, J.W.L. and Herbert, G., 2020. Hydrogeology of the McBride and Nulla basalt provinces in the Upper Burdekin region, north Queensland. 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.

One of the aims of the Exploring for the Future (EFTF) program is to characterise the geochemistry of sedimentary and volcanic units, overbank sediments and groundwater in northern Australia to de-risk resource exploration and inform decision making. Underpinning this effort has been the generation of high-quality geochemical data from Geoscience Australia’s laboratories. A streamlined workflow from sample collection to reporting ensures that samples are processed consistently and to a high standard, and use of rigorously tested methodologies and appropriate QA/QC practices ensures data quality. This abstract highlights many of the processes undertaken in the laboratories, ranging from new sample preparation procedures (including automated milling and setting up temporary remote processing facilities) to organic geochemistry, mineralogy, inorganic geochemistry and geochronology. The laboratories were also instrumental in assisting with fieldwork, outsourcing sample analyses and storing data in corporate databases. The large volume of new data generated over the EFTF program has been used to characterise the geology and geochemistry of a range of rocks, regolith, oils, gas and groundwater, and has been instrumental in increasing knowledge of the resource potential of northern Australia and informing decision making. <b>Citation:</b> Jarrett, A.J.M., Thun, C., Champion, D.C., Boreham, C.J., Main, P., Waltenberg, K., Schroder, I., Bastrakov, E., DiBugnara, D., Long, I., Chen, J., Hong, Z., Sohn, J., Jinandasa, N., Palatty, P.,Webber, S., Webster, T., Byass, J., Gilmore, S., Williamson, A., Tubby, J., Long, R., Linehan, B. and Magee, C., 2020. Generation of high-quality data for energy, minerals and groundwater by Geoscience Australia’s laboratories. 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.

High-grade gold (Au), copper (Cu) and bismuth (Bi) ores in the Tennant Creek goldfield have been mined from hydrothermal magnetite and/or hematite-rich ironstone bodies. Less well known is a style of Au-Cu-Bi mineralisation hosted by quartz vein systems within shear zones outside ironstones. Sensitive High Resolution Ion Micro Probe (SHRIMP) U-Pb-Th analyses of hydrothermal monazite [(LREE)PO4] associated with this mineralisation style at the Orlando East Au-Cu-Bi deposit and Navigator 6 Au prospect yield ages of 1659 ± 13 Ma and 1659 ± 15 Ma, respectively. These ages are nearly 200 million years younger than the age established from ironstone-hosted ores in the district. This new result widens the exploration ‘search space’ for gold into rock formations previously regarded as too young to host this style of mineralisation. <b>Citation:</b> Skirrow, R.G., Cross, A.J., Magee, C.W., Lecomte, A., and Mercadier, J., 2020. Identification of a new ca. 1660 Ma Au-Cu-Bi metallogenic event at Tennant Creek. 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.

Remotely sensed data and updated DEM and radiometric datasets, combined with existing surface material and landform mapping were used to map regolith landform units for the Ti Tree, Western Davenport and Tennant Creek regions of the SSC project. This report describes the methods used and outlines the new mapping.

For more than half a century, seismic tomography has been used to map the volumetric structure of Earth’s interior, but only recent advances in computation have enabled the application of this technique at scale. Estimates of surface waves that travel between two seismic stations can be reconstructed from a stack of cross-correlations of continuous data recorded by seismometers. Here, we use data from the Exploring for the Future program AusArray deployment to extract this ambient noise signal of Rayleigh waves and use it to image mid- to upper-crustal structure between Tennant Creek and Mount Isa. Our aim was to establish a repeatable, semi-automatic workflow that can be extended to the entire Australian continent and beyond. Shear wave velocity models at 4, 6, 8 and 10 s periods are presented. A strong low-velocity anomaly (2.5 km/s) at a period of 4 s (~2–4 km depth) delineates the outline of the newly discovered, and prospective for hydrocarbons, Carrara Sub-basin. A near-vertical high-velocity anomaly (3.5 km/s) north of Mount Isa extends from the near surface down to ~12 km and merges with northeast-trending anomalies. These elongate features are likely to reflect compositional variations within the mid-crust associated with major structures inferred to be associated with base metal deposits. These outcomes demonstrate the utility of the ambient noise tomography method of imaging first-order features, which feed into resource potential assessments. <b>Citation: </b>Hejrani, B., Hassan, R., Gorbatov, A., Sambridge, M. Hawkins, R., Valentine, A., Czarnota, K. and Zhao, J., 2020. Ambient noise tomography of Australia: application to AusArray deployment. 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. <b>See eCat record <a href="https://dx.doi.org/10.26186/148676">#148676</a> for the updated version of the model package.</b>

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.