Close up map of Submarine Cables and southern protection zone around Clovelly / Tamarama, Sydney. For internal use by ACMA. Included in this version (July 2010) is the Telstra Endeavour Cable. This map developed from previous map GeoCat 65415 (September 2007). Upated in July 2010 with the Telstra Endeavour Cable. For internal use of ACMA. Not for sale or public distribution.

An extensive AEM survey recently commissioned by Geoscience Australia involved the use of two separate SkyTEM helicopter airborne electromagnetic (AEM) systems collecting data simultaneously. In order to ensure data consistency between the two systems, we follow the Danish example (conceived by the hydrogeophysics group from Aarhus University) of using a hover test site to calibrate the AEM data to a known reference. Since 2001, Denmark has employed a national test site for all electromagnetic (EM) instruments that are used there, including the SkyTEM system. The Lyngby test-site is recognised as a well-understood site with a well-described layered-earth structure of 5 layers. The accepted electrical structure model of the site acts as the reference model, and all instruments are brought to it in order to produce consistent results from all EM systems. Using a ground-based time-domain electromagnetic (TEM) system which has been calibrated at the Lyngby test site, we take EM measurements at a site selected here in Australia. With sufficient information of the instrument, we produce a layered-earth model that becomes the reference model for the two AEM systems used in the survey. We then bring the SkyTEM systems to the hover site and take soundings at multiple altitudes. From the hover test data and the ground based model, we calculate an optimal time shift and amplitude scale factor to ensure that both systems are able reproduce the accepted reference model. Conductivity sections produced with and without calibration factors show noticeably different profiles.

Predictive maps of the subsurface can be generated when geophysical datasets are modelled in 2D and 3D using available geological knowledge. Inversion is a process that identifies candidate models which explain an observed dataset. Gravity, magnetic, and electromagnetic datasets can now be inverted routinely to derive plausible density, magnetic susceptibility, or conductivity models of the subsurface. The biggest challenge for such modelling is that any geophysical dataset may result from an infinite number of mathematically-plausible models, however, only a very small number of those models are also geologically plausible. It is critical to include all available geological knowledge in the inversion process to ensure only geologically plausible physical property models are recovered. Once a set of reasonable physical property models are obtained, knowledge of the physical properties of the expected rocks and minerals can be used to classify the recovered physical models into predictive lithological and mineralogical models. These predicted 2D and 3D maps can be generated at any scale, for Government-funded precompetitive mapping or drilling targets delineation for explorers.

The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales of their application. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P) and as the goodness-of-fit between targets and surrogates (R2). A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and method used to construct it all influenced surrogate effectiveness, according to at least either P or R2. The type of surrogate used (higher-taxa, cross-taxa or subset taxa) was the best predictor of its effectiveness, with the higher-taxa type outperforming all others. Surrogate effectiveness was maximal for higher-taxa surrogates at a < 10-km spatial scale, in low-complexity marine ecosystems such as soft bottoms, and using multivariate-based methods. Our comparisons with terrestrial studies of biological surrogates reveal that marine applications of biological surrogates still ignore some problems with several widely used statistical approaches to surrogacy, provide a benchmark for the reliable use of biological surrogates in all ecosystems, and highlight directions for future development of biological surrogates in predicting biodiversity.

This map shows the boundary of the Maritime Security Zones for each port for the purpose of the Maritime Transport & Office Security Act 2003. 1 Sheet (Colour) May 2010 Not for sale or public distribution Contact Manager LOSAMBA project, PMD

Regional geology and prospectivity of the Aileron Province in the Alcoota 1:250 000 mapsheet area

Current understanding of the temperature distribution in the Australian continent is based on sparse and unevenly distributed borehole temperature measurements, and even fewer heat flow determinations. To address this, the Geothermal Project at Geoscience Australia (GA), established under the $58.9M Onshore Energy Security Program, has set up a capability for determining surface heat flow across the country through temperature logging and thermal conductivity measurement. Without the resources to drill new holes, GA has worked with state governments and mineral exploration companies to access exploration and water bores for temperature logging. In addition to the continuous temperature logs recorded, the logging tool has a natural gamma detector. As of December 2010, 156 new temperature logs have been collected across all states and territories. Samples have been collected from most of these holes, and thermal conductivity measurement of these samples is ongoing. GA uses an Anter 2022 Unitherm thermal conductivity meter. As part of the set up procedures, an inter-lab comparison was performed between GA and Southern Methodist University (U.S.), Hot Dry Rocks Pty Ltd, and Torrens Energy Ltd. A comparison has also been performed between GA and the National Geophysical Research Institute (India). Where temperature data are sparse, it is necessary to use other geoscience information to assess the geothermal potential of an area. A thermal calculation module has been built for the GeoModeller software package by Intrepid Geophysics. GA is using this and other software to allow non-geothermal-specific data to also be incorporated into regional geothermal resource assessments.

Regional airborne electromagnetic (AEM) data provide valuable information for mapping the shallow crust. Data are particularly useful for mapping buried paleotopography including paleovalleys and paleochannels, showing the depth to conductive geological units (and perhaps related faults), and altered and weathered unconformity surfaces, that may be less evident in other regional datasets. Geoscience Australia (GA) has recently acquired and released regional AEM data in the Paterson area of Western Australia, which is one of the most highly prospective areas in Australia. GA is currently in the process of assessing the potential of basinal fluid-related uranium systems in the area, including unconformity-related, sandstone-hosted and calcrete-hosted systems. Interpretation uses this key dataset, along with other available geological, geophysical and remotely sensed data and publicly available drill hole data, Outputs of this assessment include a number of prospectivity maps for these uranium systems. Preliminary interpretations of the AEM data have identified paleovalleys containing Permian and younger sediments and fluid pathways as aquifers in Permian and younger sediments on-lapping the Rudall Complex, Fortescue Basin and Pilbara Craton. In some places, the AEM data map unconformities of Mesozoic over Permian and Permian over the Neoproterozoic Yeneena and Officer Basins and Mesoproterozoic Rudall Complex. The unconformity surface between the Neoproterozoic Yeneena and Officer Basin sediments over rocks of the Rudall Complex or Pilbara Craton appears poorly defined in the data. The AEM data are opening up new avenues of investigation for uranium systems and have shown the utility of flying regional AEM surveys over highly prospective areas.

An orogenic cycle typically follows a sequence of events or stages. These are basin formation and magmatism during extension, inversion and crustal thickening during contractional orogenesis, and finally extensional collapse of the orogen. The Archaean granite-greenstone terranes of the Eastern Yilgarn Craton (EYC) record a major deviation in this sequence of events. Within the overall contractional stage, the EYC underwent a lithospheric-scale extensional event between 2665 Ma and 2655 Ma, resulting in changes to the entire orogenic system. These changes associated with regional extension include: the crustal architecture; greenstone stratigraphy; granite magmatism; thermo-barometry (PTt paths); and structure. Synchronous with these changes was the deposition of the first significant gold, and it is likely that the intra-orogenic extensional event was one of the critical factors in the region's world-class gold endowment.

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.