From 1 - 10 / 20
  • The ISOTOPE database stores compiled age and isotopic data from a range of published and unpublished (GA and non-GA) sources. This internal database is only publicly accessible through the webservices given as links on this page. This data compilation includes sample and bibliographic links. The data structure currently supports summary ages (e.g., U-Pb and Ar/Ar) through the INTERPRETED_AGES tables, as well as extended system-specific tables for Sm-Nd, Pb-Pb, Lu-Hf and O- isotopes. The data structure is designed to be extensible to adapt to evolving requirements for the storage of isotopic data. ISOTOPE and the data holdings were initially developed as part of the Exploring for the Future (EFTF) program. During development of ISOTOPE, some key considerations in compiling and storing diverse, multi-purpose isotopic datasets were developed: 1) Improved sample characterisation and bibliographic links. Often, the usefulness of an isotopic dataset is limited by the metadata available for the parent sample. Better harvesting of fundamental sample data (and better integration with related national datasets such as Australian Geological Provinces and the Australian Stratigraphic Units Database) simplifies the process of filtering an isotopic data compilation using spatial, geological and bibliographic criteria, as well as facilitating ‘audits’ targeting missing isotopic data. 2) Generalised, extensible structures for isotopic data. The need for system-specific tables for isotopic analyses does not preclude the development of generalised data-structures that reflect universal relationships. GA has modelled relational tables linking system-specific Sessions, Analyses, and interpreted data-Groups, which has proven adequate for all of the Isotopic Atlas layers developed thus far. 3) Dual delivery of ‘derived’ isotopic data. In some systems, it is critical to capture the published data (i.e. isotopic measurements and derived values, as presented by the original author) and generate an additional set of derived values from the same measurements, calculated using a single set of reference parameters (e.g. decay constant, depleted-mantle values, etc.) that permit ‘normalised’ portrayal of the data compilation-wide. 4) Flexibility in data delivery mode. In radiogenic isotope geochronology (e.g. U-Pb, Ar-Ar), careful compilation and attribution of ‘interpreted ages’ can meet the needs of much of the user-base, even without an explicit link to the constituent analyses. In contrast, isotope geochemistry (especially microbeam-based methods such as Lu-Hf via laser ablation) is usually focused on the individual measurements, without which interpreted ‘sample-averages’ have limited value. Data delivery should reflect key differences of this kind.

  • This release comprises the 3D geological model of the Yilgarn-Officer-Musgrave (YOM) region, Western Australia, as Gocad voxets and surfaces. The YOM 3D geological model was built to highlight the broad-scale crustal architecture of the region and extends down to 60 km depth.

  • 3D visualisation of the Mount Isa Crustal Seismic Survey

  • The aim of this document is to: * outline the general process adopted by Geoscience Australia in modelling tsunami inundation for a range of projects conducted in collaboration with Australian and State Government emergency management agencies * allow discoverability of all data used to generate the products for the collaborative projects as well as internal activities.

  • The purpose of this study is to determine the potential of tsunami inundation from historical and potential submarine mass failures of the NSW coast based on the findings from the October 2006 Continental Slope Survey conducted by GA. The learnings from this study are intended for use by the Australian Tsunami Warning Project and NSW emergency managers.

  • A 3D map of the Cooper Basin region has been produced over an area of 300 x 450 km to a depth of 20 km. The 3D map was constructed from 3D inversions of gravity data using geological data to constrain the inversions. It delineates regions of low density within the basement of the Cooper/Eromanga Basins that are inferred to be granitic bodies. This interpretation is supported by a spatial correlation between the modelled bodies and known granite occurrences. The 3D map, which also delineates the 3D geometries of the Cooper and Eromanga Basins, therefore incorporates both potential heat sources and thermally insulating cover, key elements in locating a geothermal play. This study was conducted as part of Geoscience Australia's Onshore Energy Security Program, Geothermal Energy Project.

  • The aim of this document is to * outline the general process adopted by Geoscience Australia in modelling storm surge inundation for projects conducted in collaboration with Australian and State Government planning agencies * allow discoverability of all data used to generate the products for the collaborative projects as well as internal activities

  • Demand for critical raw materials is expected to accelerate over the next few decades due to continued population growth and the shifting consumption patterns of the global economy. Sedimentary basins are important sources for critical raw materials and new discoveries of sediment–hosted Mississippi Valley–type (MVT) and/or clastic–dominated (CD) Zn–Pb deposits are likely required to mitigate future supply chain disruptions for Zn, Pb, Ag, Cd, Ga, Ge, Sb, and In. Herein we integrate public geoscience datasets using a discrete global grid to system to model the mineral potential for MVT and CD deposits across Canada, the United States of America, and Australia. Statistical analysis of the model results demonstrates that surface–wave tomography and derivative products from satellite gravity datasets can be used to map the most favourable paleo–tectonic settings of MVT and CD deposits inboard of orogenic belts and at the rifted edges of cratonic lithosphere, respectively. Basin development at pre–existing crustal boundaries was likely important for maintaining the low geothermal–gradients that are favourable for metal transport and generating the crustal fluid pathways that were reactivated during ore–formation, as suggested by the statistical association of both sediment–hosted mineral deposit types with the edges of upward–continued gravity and long–wavelength magnetic anomalies. Multivariate statistical analysis demonstrates that the most prospective combination of these geophysical datasets varies for each geological region and deposit type. We further demonstrate that maximum and minimum geological ages, coupled with Phanerozoic paleogeographic reconstructions, represent mappable proxies for the availability of oxidized, brine–generating regions that are the most likely source of ore–forming fluids (e.g., low– to mid–latitude carbonate platforms and evaporites). Ore deposition was likely controlled by interaction between oxidized, low–temperature brines and sulfidic and/or carbonaceous rocks, which, in some cases, can be mapped at the exposed surface or identified using the available rock descriptions. Baseline weights–of–evidence models are based on regional geophysics and are the least impacted by missing surface information but yield relatively poor results, as demonstrated by the low area–under–the–curve (AUC) for the spatially independent test set on the success–rate plot (AUC = 0.787 for MVT and AUC = 0.870 for CD). Model performance can be improved by: (1) using advanced methods that were trained and validated during a series of semi–automated machine learning competitions; and/or (2) incorporating geological and geophysical datasets that are proxies for each component of the mineral system. The best–performing gradient boosting machine models yield higher AUC for the test set (AUC = 0.983 for MVT and AUC = 0.991 for CD) and reduce the search space by >94%. The model results highlight the potential benefits of mapping sediment–hosted mineral systems at continental scale to improve mineral exploration targeting for critical raw materials.

  • 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.

  • The aim of this document is to * outline the information management process for inundation modelling projects using ANUGA * outline the general process adopted by Geoscience Australia in modelling inundation using ANUGA * allow a future user to understand (a) how the input and output data has been stored (b) how the input data has been checked and/or manipulated before use (c) how the model has been checked for appropriateness