4 maps for Ministerial. Refer to GeoCats 73029 & 73030 Not for sale or public distribution Contact Manager LOSAMBA project, PMD

Geoscience Australia has been acquiring deep crustal reflection seismic transects throughout Australia since the 1960s. The results of these surveys have motivated major interpretations of important geological regions, contributed to the development of continental-scale geodynamic models, and improved understanding about large-scale controls on mineral systems. Over the past five years, Geoscience Australia has acquired over 6000 km of deep crustal seismic reflection data under the auspices of the Predictive Mineral Discovery Cooperative Research Centre (pmd*CRC), Onshore Energy Security Program (OESP), AuScope Earth Imaging (part of the National Collaborative Research Infrastructure Strategy), and all mainland State and Territory governments. These seismic datasets continue to underpin fundamental research into the geodynamics of the Australian continent and provide the third dimension for pre-competitive geoscience information related to mineral and energy resources in selected provinces and basins. Regional seismic reflection surveys currently utilise three Hemi 50 or 60 vibrators at 80 m VP with 40 m group interval, resulting in 75 fold data to 20 s TWT. In-house processing is aimed at providing a whole of crust image, without sacrificing shallow detail. Gravity readings are also collected along the lines at 400 m intervals to assist integrated regional interpretations based on the seismic traverses. Magnetotelluric (MT) soundings, including both broad-band and long period, have been acquired along most traverses. MT provides an image of the conductivity of the crust which is complementary to the structural information obtained from reflection seismic. Geoscience Australia is currently developing an in-house MT processing and modelling capability.

As part of initiatives by the Australian and Queensland Governments to support energy security and mineral exploration, a deep seismic reflection and magnetotelluric survey was conducted in 2007 to establish the architecture and geodynamic framework of north Queensland. With additional support from AuScope, nearly 1400 km of seismic data were acquired along four lines, extending from near Cloncurry in the west to almost the Queensland coast.

Assessment of existing volcanic ash hazard models for South East Asia: towards development of an open-source, volcanic ash impact computational model for Indonesia

A key component of Geoscience Australia's marine program involves developing products that contain spatial information about the seabed for Australia's marine jurisdiction. This spatial information is derived from sparse or unevenly distributed samples collected over a number of years using many different sampling methods. Spatial interpolation methods are used for generating spatially continuous information from the point samples. These methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Machine learning methods, like random forest (RF) and support vector machine (SVM), have proven to be among the most accurate methods in disciplines such as bioinformatics and terrestrial ecology. However, they have been rarely previously applied to the spatial interpolation of environmental variables using point samples. To improve the accuracy of spatial interpolations to better represent the seabed environment for a variety of applications, including prediction of biodiversity and surrogacy research, Geoscience Australia has conducted two simulation experiments to compare the performance of 14 mathematical and statistical methods to predict seabed mud content for three regions (i.e., Southwest, North, Northeast) of Australia's marine jurisdiction Since 2008. This study confirms the effectiveness of applying machine learning methods to spatial data interpolation, especially in combination with OK or IDS, and also confirms the effectiveness of averaging the predictions of these combined methods. Moreover, an alternative source of methods for spatial interpolation of both marine and terrestrial environmental properties using point survey samples has been identified, with associated improvements in accuracy over commonly used methods.

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) March 2010 Not for sale or public distribution Contact Manager LOSAMBA project, PMD

A seismic structure imaged in a single 2D seismic profile from the offshore Canning Basin, Western Australia, is interpreted to be a possible complex impact crater on the basis of its seismic character. The feature, herein referred to as the Haines Structure, is symmetrical in two dimensions over ~2.5 km and comprises a centrally uplifted basal surface, a depressed upper surface, a highly deformed intervening package and an overlying horizon that is `sagging' over the depression. The possible impact structure lies within carbonate units of Eocene or Early Oligocene age as determined from seismic correlation to petroleum exploration wells. The structure has not been drilled; therefore distinguishing characteristics used to define an impact origin, such as shock metamorphism, are not available. Comparison with other features in the Neogene succession of Australia's North West Shelf that have previously been interpreted as impact structures highlights the presence of key elements in the Haines Structure that characterise known complex impact craters, and the absence of seismic features related to alternative processes, such as a link to deeper structures that would be expected beneath a volcanic pipe.

The Pine Creek AEM survey was flown over the Pine Creek Orogen in the Northern Territory during 2008 and 2009 as part of the Australian Government's Onshore Energy Security Program at Geoscience Australia (GA). The survey provides pre-competitive data for enhancing uranium and other mineral exploration. Flight line spacing was 1666 m and 5000 m covering an area of 74,000 km2 (roughly the size of Tasmania) which hosts several uranium deposits, including the Ranger Uranium Mine, Rum jungle, Ranger and Nabarlek. The region is also prospective for metals including copper, lead, zinc, gold, tin, rare earths, tantalum, tungsten, molybdenum and nickel. The Pine Creek AEM survey comprises three areas: Kombolgie to the east of Kakadu National Park; Woolner Granite near Darwin; and, Rum Jungle to the west of Kakadu National Park. Collaboration with the National Water Commission and eight private infill companies brought an additional investment of approximately $1 m into the survey, with follow-up exploration equal to or exceeding this amount. The Woolner Granite and Rum Jungle survey area data were acquired using the TEMPEST fixed wing AEM system. The acquisition and processing were carried out by Fugro Airborne Surveys Pty. Ltd., under contract to GA. The Woolner Granite and Rum Jungle surveys were flown between August 2008 and May 2009 and the data were publicly released by GA in July and September 2009 respectively. In the Kombolgie survey area, the data were acquired a by Geotech Airborne Pty. Ltd. using the VTEM helicopter AEM system. The survey was flown between August and November of 2008, and additional calibration flights relating to the survey were flown in April 2009. The Kombolgie data were publicly released by GA in December 2009.

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.

This map shows the boundary of the security regulated port for the purpose of the Maritime Transport & Office Security Act 2003. 2 Sheets (Colour) January 2010 Not for sale or public distribution Contact Manager LOSAMBA project, PMD