Extended abstract version of short abstract accepted for conference presentation GEOCAT# 73701

Australia has a rich uranium endowment. Amongst other favourable geological conditions for the formation of uranium deposits, such as the presence of intracratonic sedimentary basins, Australia is host to widespread uranium-rich felsic igneous rocks spanning a wide range of geological time. Many known uranium deposits have an empirical spatial relationship with such rocks. While formation of some mineral systems is closely associated with the emplacement of uranium-rich felsic magmas (e.g., the super-giant Olympic Dam deposit), most other systems have resulted from subsequent low temperature processes occurring in spatial proximity to these rocks. Approximately 91% of Australia's initial in-ground resources of uranium occur in two main types of deposits: iron-oxide breccia complex deposits (~ 75%) and unconformity-related deposits (~ 16%). Other significant resources are associated with sandstone- (~ 5%) and calcrete-hosted (~ 1%) deposits. By comparison, uranium deposits associated with orthomagmatic and magmatic-hydrothermal uranium systems are rare. Given the paucity of modern exploration and the favourable geological conditions with Australia, there remains significant potential for undiscovered uranium deposits. This paper discusses mineral potential of magmatic- and basin-related uranium systems.

CONTROL ID: 1813538 TITLE: 'Big Data' can make a big difference: Applying Big Data to National Scale Change Analyses AUTHORS (FIRST NAME, LAST NAME): Norman Roland Mueller1, Steven Curnow1, Rachel Melrose1, Matthew Brian John Purss1, Adam Lewis1 INSTITUTIONS (ALL): 1. Geoscience Australia, Canberra, ACT, Australia. ABSTRACT BODY: The traditional method of change detection in remote sensing is based on acquiring a pair of images and conducting a set of analyses to determine what is different between them. The end result is a single change analysis for a single time period. While this may be repeated several times, it is generally a time consuming, often manual process providing a series of snapshots of change. As datasets become larger, and time series analyses become more sophisticated, these traditional methods of analysis are unviable. The Geoscience Australia 'Data Cube' provides a 25-year time series of all Landsat-5 and Landsat-7 data for the entire Australian continent. Each image is orthorectified to a standard set of pixel locations and is fully calibrated to a measure of surface reflectance (the 25m Australian Reflectance Grid [ARG25]). These surface reflectance measurements are directly comparable, between different scenes, and regardless of whether they are sourced from the Landsat-5 TM instrument or the Landsat-7 ETM+. The advantage of the Data Cube environment lies in the ability to apply an algorithm to every pixel across Australia (some 1013 pixels) in a consistent way, enabling change analysis for every acquired observation. This provides a framework to analyse change through time on a scene to scene basis, and across national-scale areas for the entire duration of the archive. Two examples of applications of the Data Cube are described here: surface water extent mapping across Australia; and vegetation condition mapping across the Murray-Darling Basin, Australia's largest river system.. Ongoing water mapping and vegetation condition mapping is required by the Australian government to produce information products for a range of requirements including ecological monitoring and emergency management risk planning. With a 25 year archive of Landsat-5 and Landsat-7 imagery hosted on an efficient High Performance Computing (HPC) environment, high speed analyses of long time series for water and vegetation condition are now viable. www.ga.gov.au KEYWORDS: 1906 INFORMATICS Computational models, algorithms, 1988 INFORMATICS Temporal analysis and representation, 1980 INFORMATICS Spatial analysis and representation. (No Image Selected) (No Table Selected) Additional Details Previously Presented Material: Contact Details CONTACT (NAME ONLY): Norman Mueller CONTACT (E-MAIL ONLY): norman.mueller@ga.gov.au TITLE OF TEAM:

Magnetotelluric data were acquired for Geoscience Australia by contract along the north-south 08GA-C1-Curnamona seismic traverse to the east of Lake Frome from November 2008 to January 2009 as part of the Australian Government's energy security initiative. 25 sites were spaced an average of 10 km apart, and five-component broadband data were recorded with a frequency bandwidth of 0.001 Hz to 250 Hz and dipole lengths of 100 m. Apparent resistivity and phase plots are presented, along with dimensional analyses of the data based on rotational invariants, the representation of the data by the phase tensor, and Parkinson arrows. These analyses provide insight into the complexity of the Earth conductivity giving rise to the MT responses and are a useful precursor to modelling.

Rare-earth-element (REE) mineral systems in Australia are associated with igneous, sedimentary, and metamorphic rocks in a range of geological environments (http://www.ga.gov.au/image_cache/GA19657.pdf). Elevated concentrations of these elements have been documented in various carbonatite intrusions, (per)alkaline igneous rocks, iron-oxide breccia complexes, calc-silicate rocks (skarns), fluorapatite veins, pegmatites, phosphorites, fluvial sandstones, unconformity-related uranium deposits, lignites and heavy-mineral sand deposits (beach, dune, marine tidal, and channel). The distribution and concentration of REE in these deposits is influenced by various rock-forming processes including enrichment in magmatic or hydrothermal fluids, separation into mineral species and precipitation, and subsequent redistribution and concentration through weathering and other surface processes. The lanthanide series of REE and yttrium, show a close association with alkaline felsic igneous rocks, however, scandium in laterite profiles has an affinity with ultramafic-mafic igneous rocks.

Since the 1989 Newcastle earthquake, the city of Newcastle, Australia, has become an extensive focus for earthquake hazard and risk assessment. The surficial geology varies between deeper alluvial deposits near the Hunter River, to shallower soils overlying weathered rock on the valley margins. Ambient vibration techniques, based on the dispersion property of surface waves in layered media, is one promising method for assessing the subsurface geophysical structure, in particular the shear-wave velocity (Vs). Using one such technique, the Spatial Auto-Correlation (SPAC) method, we characterise soil deposits at 23 sites in and around the city of Newcastle. Results show that values for soil overlying bedrock ranges from 200 m/s to 1000 m/s, with the higher velocity values observed in shallow soils which are relatively consolidated and far from river deposits. Bedrock depth varies from 6 to 56 m, but an accurate quantification is hampered by the low frequency picks (< 2 Hz) which are either unavailable or of dubious quality. Some shear-wave velocity profiles show two abrupt changes in Vs, the first ~ 4-15 m and the second ~19-56 m. Low Vs values are of particular interest as they may indicate areas of higher seismic hazard.

Like many of the basins along Australia's eastern seaboard, there is currently only a limited understanding of the geothermal energy potential of the New South Wales extent of the Clarence-Moreton Basin. To date, no study has examined the existing geological information available to produce an estimate of subsurface temperatures throughout the region. Forward modelling of basin structure using its expected thermal properties is the process generally used in geothermal studies to estimate temperatures at depth in the Earth's crust. The process has seen increasing use in complex three-dimensional (3D) models, including in areas of sparse data. The overall uncertainties of 3D models, including the influence of the broad assumptions required to undertake them, are generally only poorly examined by their authors and sometimes completely ignored. New methods are presented in this study which will allow estimates and uncertainties to be addressed in a quantitative and justifiable way. Specifically, this study applies Monte Carlo Analysis to constrain uncertainties through random sampling of statistically congruent populations. Particular focus has been placed on the uncertainty in assigning thermal conductivity values to complex and spatially extensive geological formations using only limited data. As a case study these new methods are then applied to the New South Wales extent of the Clarence-Moreton Basin. The geological structure of the basin has been modelled using data from existing petroleum drill holes, surface mapping and information derived from previous studies. A range of possible lithological compositions was determined for each of the major geological layers through application of compositional data analysis. In turn, a range of possible thermal conductivity values was determined for the major lithology groups using rock samples held by the NSW Department of Primary Industries (DPI). These two populations of values were then randomly sampled to establish 120 different forward models, the results of which have been interpreted to present the best estimate of expected subsurface temperatures, and their uncertainties. These results suggest that the Clarence-Moreton Basin has a moderate geothermal energy potential within an economic drilling depth. This potential however, displays significant variability between different modelling runs, which is likely due to the limited data available for the region. While further work could improve these methods, it can be seen from this study that uncertainties can provide a means by which to add confidence to results, rather than undermine it.

In the 2011/12 Budget, the Australian Government announced funding of a four year National CO2 Infrastructure Plan (NCIP) to accelerate the identification and development of suitable long term CO2 storage sites, within reasonable distances of major energy and industrial emission sources. The NCIP funding follows on from funding announced earlier in 2011 from the Carbon Storage Taskforce through the National Carbon Mapping and Infrastructure Plan and previous funding recommended by the former National Low Emissions Coal Council. Four offshore sedimentary basins and several onshore basins have been identified for study and pre-competitive data acquisition.

The response to emergency situations such as floods and fires demand products in short time frames. If you use remote sensing then the response typically involves detailed examination of imagery in order to determine the spectral bands, ratios and associated thresholds that map the desired features such as flood or burn extent. The trial and error process associated with manual threshold selection is often time consuming and can result in significant errors due to confounding factors such as clouds and shadowed areas. By modelling features such as flood waters or fire scars as Gaussian distributions, allowing for fuzzy thresholds with neighbouring features, the required thresholds can be automatically derived from the imagery and emergency events can have extents determined much more rapidly. Automatic threshold selection minimises trial and error, thereby dramatically reducing processing turn-around time.

Summary of GA's plans for marine seismic and reconnaissance surveys off southwestern Australia in 2008/09 as part of the Offshore Energy Security Program