Legacy product - no abstract available

Map shows the location of all publicly accessible gravity stations in Australia.

<p>Crustal thickness, continental lithosphere thinning factor and residual continental crustal thickness have been determined for the South Australian and Antarctic conjugate rifted margins and adjacent oceanic regions using gravity inversion incorporating a lithosphere thermal gravity anomaly correction using the method of Greenhalgh & Kusznir (2007) and Chappell & Kusznir (2008). Satellite derived gravity anomaly data (Smith & Sandwell 1997), bathymetry data (Gebco 2003), sediment thickness data provided by Geoscience Australia and ocean isochron data (Mueller et al. 2003) have been used to derive the mantle residual gravity anomaly which is then inverted in the 3D spectral domain to give Moho depth. The region of investigation is contained within the coordinate limits 30&#176 - 70&#176S and 85&#176 - 175&#176E. Gravity inversion has been carried out for both thick and thin sediment thickness map grids provided by Geoscience Australia. <p>The results of the gravity inversion are shown in the form of: (i) maps of crustal basement thickness, Moho depth,continental lithosphere thinning factor and residual continental crustal thickness; and (ii) crustal cross-sections showing predicted Moho depth, and thicknesses of residual continental crust, volcanic addition and sediment for the South Australian and conjugate Antarctic continental margins. 32 regional 2D cross-sections have been constructed; 16 for each conjugate margin. <p>Thinning factor estimates determined from crustal thinning from gravity inversion require a volcanic addition correction. Parameterisations of volcanic addition as a function of lithosphere thinning factor (1-1/ß) appropriate to magma-poor, normal and volcanic margins have been used in the gravity inversion. The sensitivity of predicted crustal thickness and lithosphere thinning factor from the gravity inversion to volcanic addition is shown in map form. Cross sections and maps have been determined using volcanic addition models appropriate to both magma poor and normal rifted continental margins. <p>Sensitivity tests of the gravity inversion results to reference crustal thickness have been carried out. Calibration against seismic refraction observations of Moho depth suggest that the reference crustal thickness is between 40 - 42.5 km on the S. Australian margin and between 37.5 - 40 km on the Antarctic conjugate margin. <p>Gravity inversion tests have also been carried out to examine the sensitivity of predicted crustal thickness and lithosphere thinning factor to breakup age and the age of the oldest oceanic isochrons used to condition the lithosphere thermal model. The preferred age of continental breakup used in the gravity inversion is 84 Ma. The preferred age of the oldest oceanic isochron used to condition the oceanic component of the lithosphere thermal model is 44 Ma and is chosen to avoid using the oldest isochrons against the ocean-continent transition which contain errors in both age and location, and which may prejudice the determination of ocean-continent transition using gravity inversion. <p>Sensitivity tests for sediment density and crustal basement density have also been carried out.

No abstract available

Obtaining reliable predictions of the subsurface will provide a critical advantage for explorers seeking mineral deposits at depth and beneath cover. A common approach in achieving this goal is to use deterministic property-based inversion of potential field data to predict a 3D subsurface distribution of physical properties that explain measured gravity or magnetic data. Including all prior geological knowledge as constraints on the inversion ensures that the recovered predictions are consistent with both the geophysical data and the geological knowledge. Physical property models recovered from such geologically-constrained inversion of gravity and magnetic data provide a more reliable prediction of the subsurface than can be obtained without constraints. The non-uniqueness of inversions of potential field data mandates careful and consistent parameterization of the problem to ensure realistic solutions.

Map shows the gravity coverage over Australia of publicly accessible gravity data. Each coloured area indicates the station spacing and survey reliability.

Legacy product - no abstract available

Extended abstract for the 21st International Geophysical Conference and Exhibition, Sydney, 2010

Legacy product - no abstract available

Inverse modelling of gravity/ or magnetic data is an essential component in geoscience research. Various numerical techniques in solving inverse problem for potential field data have been evolved over many years. However, the non-uniqueness in inverse solution and uncertainty in model building exercise still remain elusive. It is widely believed that additional information as soft constraint may ease the situation. This encourages pondering about joint inversion of gravity and magnetic data. Unfortunately, it often turns out that the constraints of joint inversion of gravity and magnetic data no longer becomes soft and it becomes more difficult to obtain optimal solution that would honour both the data set, which are two mutually competitive members. To circumvent such problem we propose of choosing Pareto optimal solution from the solution space. Between two competitive members such solution guarantees to make one member better off without making other member worse off. We consider L2-norm measure of fit between observed and computed data. We use particle swarm optimization (PSO), a global optimization technique to minimize the misfit between observed and computed data. We determine the Pareto front and hence the Pareto optimal solution from the cluster solutions in the solution space. Applications of the method on synthetic and field cases are presented.