Abstract # : 1479734 Paper # : GP43B-1142 Session : GP43B Potential-field and EM methods for geologic problems of the mid and upper crust Developments for 3D gravity and magnetic modeling in spherical coordinates Richard Lane - Geoscience Australia - rjllane@gmail.com Qing Liang - China University of Geosciences (Wuhan) - qingliang.cug@gmail.com Chao Chen - China University of Geosciences (Wuhan) - chenchao@cug.edu.cn Yaoguo Li - Colorado School of Mines - ygli@mines.edu At Geoscience Australia (GA), Australia's Commonwealth Government geoscientific agency, we perform gravity and magnetic modeling at a range of scales, from broad regional crustal studies with thousands of kilometer lateral extent and tens of kilometer vertical extent, to detailed local studies with kilometer or less lateral extent and meters to hundreds of meters vertical extent. To achieve greater integration and coherence, and to better understand the geological significance of this work, we are investing in a number of development projects; * Spherical coordinate gravity and magnetic modeling, * Modeling using High Performance Computing facilities, * Utilizing rock property data as an input into the modeling and interpretation of gravity and magnetic data, * Better management of geoscience data and models, and * Visualization of spatial data in a Virtual Globe format. In collaboration with the Colorado School of Mines (CSM) and the China University of Geosciences (CUG), we are developing a capability to model gravity and magnetic data in a spherical coordinate framework. This will provide more accurate calculations and permit us to integrate the results into a single framework that more realistically reflects the shape of the Earth. Modeling gravity and magnetic data in a spherical coordinate framework is far more compute intensive than is the case when performing the corresponding calculations in a Cartesian (rectangular) coordinate framework. To reduce the time required to perform the calculations in a spherical coordinate framework, we will be deploying the modeling software on the National Computational Infrastructure (NCI) High Performance Computing (HPC) facility at the Australian National University (ANU). This will also streamline the management of these software relative to the other main option of establishing and maintaining HPC facilities in-house. We are a participant in the Deep Exploration Technologies Cooperative Research Centre (DET CRC). In combination with this involvement, we are expanding our support for systematic management of rock property data, and developing a better understanding of how these data can be used to provide constraints for the modeling work. We are also using the opportunities afforded through the DET CRC to make progress with documentation and standardization of data storage and transfer formats so that the tasks of management, discovery and delivery of this information to users are simplified and made more efficient. To provide the foundations of integration and analysis of information in a spatial context, we are utilizing and customizing 3D visualization software using a Virtual Globe application, NASA World Wind. This will permit us to view the full range of information types at global to local scales in a realistic coordinate framework. Together, these various development activities will play an important role in the on-going effort by Geoscience Australia to add value to the potential field, rock property, and geological information that we possess. We will then be better able to understand the geology of the Australian region and use this knowledge in a range of applications, including mineral and energy exploration, natural hazard mitigation, and groundwater management.

Basin evolution of the Vlaming Sub-basin and the deep-water Mentelle Basin, both located offshore on the southwest Australian continental margin, were investigated using 2D and 3D petroleum system modelling. Compositional kinetics, determined on the main source sequences, were used to predict timing of hydrocarbon generation and migration as well as GOR evolution and phase behaviour in our 2D and 3D basin models. The main phase of petroleum generation in the Vlaming Sub-basin occurred at 150 Ma and ceased during following inversion and erosion episodes. Only areas which observed later burial have generated additional hydrocarbons during the Tertiary and up to present day. The modelling results indicate the likely generation and trapping of light oils for the Jurassic intervals for a variety of structural traps. It is these areas which are of greatest interest from an exploration point of view. The 2D numerical simulations in the Mentelle Basin indicate the presence of active hydrocarbon generating kitchen areas. Burial histories and generalized petroleum evolutionary histories are investigated.

A nationally-consistent wave resource assessment is presented for Australian shelf (<300 m) waters. Wave energy and power were derived from significant wave height and period, and wave direction hindcast using the AusWAM model for the period 1 March 1997 to 29 February 2008 inclusive. The spatial distribution of wave energy and power is available on a 0.1° grid covering 110'156° longitude and 7'46° latitude. Total instantaneous wave energy on the entire Australian shelf is on average 3.47 PJ. Wave power is greatest on the 3,000 km-long southern Australian shelf (Tasmania/Victoria, southern Western Australia and South Australia), where it widely attains a time-average value of 25-35 kW m-1 (90th percentile of 60-78 kW m-1), delivering 800-1100 GJ m-1 of energy in an average year. New South Wales and southern Queensland shelves, with moderate levels of wave power (time-average: 10-20 kW m-1; 90th percentile: 20-30 kW m-1), are also potential sites for electricity generation due to them having a similar reliability in resource delivery to the southern margin. Time-average wave power for most of the northern Australian shelf is <10 kW m-1. Seasonal variations in wave power are consistent with regional weather patterns, which are characterised by winter SE trade winds/summer monsoon in the north and winter temperate storms/summer sea breezes in the south. The nationally-consistent wave resource assessment for Australian shelf waters can be used to inform policy development and site-selection decisions by industry.

Benthic habitats on the continental shelf are strongly influenced by exposure to the effects of surface ocean waves, and tidal, wind and density driven ocean currents. These processes combine to induce a combined flow bed shear stress upon the seabed which can mobilise sediments or directly influence organisms disturbing the benthic environment. Output from a suite of numerical models predicting these oceanic processes have been utilised to compute the combined flow bed shear stresses over the entire Australian continental shelf for an 8-year period (March 1997- February 2005 inclusive). To quantify the relative influence of extreme or catastrophic combined flow bed shear stress events and more frequent events of smaller magnitude, three methods of classifying the oceanographic levels of exposure are presented: 1. A spectral regionalisation method, 2. A method based on the shape of the probability distribution function, and 3. A method which assesses the balance between the amount of work a stress does on the seabed, and the frequency with which it occurs. Significant relationships occur between the three regionalisation maps indicating seabed exposure to oceanographic processes and physical sediment properties (mean grain size and bulk carbonate content), and water depth, particularly when distinction is made between regions dominated by high-frequency (diurnal or semi-diurnal) events and low-frequency (synoptic or annual) events. It is concluded that both magnitude and frequency of combined-flow bed shear stresses must be considered when characterising the benthic environment. The regionalisation outputs of the Australian continental shelf presented in this study are expected to be of benefit to quantifying exposure of seabed habitats on the continental shelf to oceanographic processes in future habitat classification schemes for marine planning and policy procedures.

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.

Stacking velocities for surveys 1001 (Shell Petrel) and 1053 (Esso R74A) over the Bremer and Denmark Sub-basins were analysed for depth and time.

Integration of disparate sets of geophysical data, such as Bouguer gravity, magnetotelluric and seismic travel time data for a robust interpretation of architectural settings of the subsurface is carried out. At the outset, the layered 2D model space is appropriately gridded. A spline node layer boundary parameterisation with a sigmoid basis function is used to relate local 1D layered model parameterisation to the 2D model space. Joint 1D inversion of seismic travel time and magnetotelluric data is carried out at the spline nodes using empirical relationships between seismic velocity and resistivity. The two objective functions corresponding to each of the input data types are combined through a weighting factor, the appropriate value of which is determined using the L-curve technique. The particle swarm optimization scheme is used as a robust optimiser for the layer depths and property values. The inverted velocity model is transformed to a density model using a second empirical rock property relationship. A 2D inversion of Bouguer gravity data is then carried out producing adjustments to the depths for the layer boundaries. This completes the initialisation phase of the procedure. A second iterative phase during which only the depths to the layer boundaries are modified is carried out to build a coherent model which is consistent with all three kinds of data. This involves re-inverting jointly the seismic travel time and magnetotelluric data, where parameters corresponding to the rock properties are kept unaltered, but the depth to the layer interfaces are updated. The method is trialled with a synthetic situation and is implemented to interpret the architectural settings of newly discovered Millungera basin of North Queensland, Australia.

The inversion analyses presented in our paper and now extended in this Reply were ultimately only one part of the AEM system selection process for the BHMAR project. Both Derivative and Inversion analyses are in their nature theoretical, and it is impossible, in a theoretical analysis, to capture all of the aspects relevant for real surveys with little margin for error in political time frames. In reality, neither the Derivative nor Inversion analysis provided the degree of certainty required (by the project manager and client) to ascertain whether any of the candidate AEM systems were able to map the key managed aquifer recharge targets recognized in the study area. Consequently, a decision was made to acquire data over a test line with the 2 systems (SkyTEM and TEMPEST) that performed best in the Derivative and Inversion analysis studies. This approach was vindicated with quite distinctive and very different performance observed between these two systems, especially when compared with borehole and ground geophysical and hydrogeological data over known targets. Data were inverted both with contractors' software and with reference software common to all systems and the results were compared. Ultimately, it was the test line, particularly in the near-surface (top 20metres), thatmade the SkyTEM system stand out as the best system for the particular targets in the project area. SkyTEM mapped the key multi-layered hydrostratigraphy and water quality variability in the key aquifer that defined the key MAR targets, although the TEMPEST system had a superior performance at depths exceeding 100metres. Importantly, the SkyTEM system also mapped numerous, subtle fault-offsets in the shallow near-surface. These structures were critical to mapping recharge and inter-aquifer leakage pathways. Further analysis has demonstrated that selection of the most appropriate AEM system and inversion can result in order of magnitude differences in estimates of potential groundwater resources. The acquisition of SkyTEM data was an outstanding success, demonstrating the capability of AEM systems to provide high-resolution data for the rapid mapping and assessment of groundwater and strategic aquifer storages in Australia's complex and highly salinized floodplain environments. The SkyTEM data were used successfully to identify 14 major new groundwater targets and multiple MAR targets, and these have been validated by an extensive drilling program (Lawrie et al., 2012a-e). Increasingly, the demand from clients for higher certainty in project decision making, and quantifying errors, will see development of new system comparative analysis approaches such as the Inversion analysis approach documented in our initial paper. Ultimately, system fly-offs are likely in high-profile projects where budgets permit.

The subsurface of the Earth is a complex system, one that we are yet to fully understand and model. It is hence impossible to automate the process of mapping and modelling, and the input of user experience and knowledge ('prior knowledge') is required to produce meaningful and useful outputs. This form of solution does not lend itself to a simple programmatic approach. However, by taking advantage of advances in computer technology and the application of numerical methods for modeling complex environments, we can do much to improve upon past results. Introduction As Australia's national geoscience organisation, Geoscience Australia (GA) plays an important role in the creation and delivery of fundamental geoscientific information. Studies are carried out at a wide range of scales, from a continental perspective to highly detailed local site investigations. In most situations, direct geological observations are supplemented by the inferences that can be made from geophysical measurements. Observations of the Earth's gravity and magnetic fields contain signals from subsurface materials, and extensive holdings of these measurements are commonly used to help create 3D subsurface models. With sparse hard constraints and incomplete, insufficient, noisy observations, knowledge workers or experts continue to play an important role in providing implicit prior constraints on any system to model this volume. The interface to these people becomes an important part of any set of tools for performing geological modeling of gravity and magnetic data. Users constantly demand a better experience and better outcomes when modeling the subsurface. Some of their recurring requests are for: * A simpler, more intuitive user-experience * Higher resolution * Models with larger extents * Faster processing * Inclusion of a greater number of geological and rock property constraints * Estimates of the uncertainty in the outcomes * Improved 3D visualisation * Tracking of input provenance and subsequent processing that is carried out * Organised management of 3D models Integration of the elements is a key consideration when developing solutions, as users are loathe to adopt procedures that become more involved and more difficult to understand and to piece together. Today, developments to produce world-class solutions typically take place across multiple agencies, involving many people, and at locations spread around the globe. This in itself is a challenge! We have focused our efforts on the following: * The management and delivery of rock properties * Spherical and Cartesian coordinate gravity and magnetic modelling software * Use of High Performance Computing (HPC) facilities * Use of a virtual globe application for 3D visualisation

To perform a realistic 3D inversion of gravity data covering a significant proportion of the surface of the Earth, it is necessary to take into account the curvature of the Earth. We have developed an algorithm for inverting gravity data in spherical coordinates and have demonstrated this using data covering the continental mass of Australia and surrounding ocean areas. The density structures evident in the crust and uppermost mantle of the resultant 3D inversion model are in broad agreement with knowledge of the geological features for the region and with variations in the depth to the Moho that are present in the AusMoho model.