Richard Lane

Effects of data filtering on inversion of gravity gradient data

Gravity gradiometer data are affected by high-frequency noise originating from the movement of the platform. Lowpass filters are often applied to remove such motion-related noise. The filtering, however, does not discriminate between signal and noise and removes both from frequencies outside the pass band. As a result, the anomalies become wider and their amplitudes become smaller. If this effect is not taken into consideration, interpretation of such data produces source bodies that are deeper and wider than the true sources. In this presentation, we first quantify the errors in the inverted models that result when the low-pass filtering is ignored using a simple parametric example. We then incorporate the low-pass filtering into the forward modeling and sensitivity calculations. This ensures that the forward operator includes both the physics and acquisition system characteristics, and hence, that it is consistent with the data to be inverted. Application to synthetic and field examples demonstrates that such an approach can largely ameliorate the adverse effect of low-pass filtering. We illustrate this result here using a synthetic parametric model, and will discuss the application to 3D problems and field data sets during the presentation.

Stochastic temperature, heat flow and geothermal gradient modeling direct from a 3D map of the Cooper Basin region, Central Australia

Significant volumes of Big Lake Suite granodiorite intrude basement in the Cooper Basin region of central Australia. Thick sedimentary sequences in the Cooper and overlying Eromanga Basins provide a thermal blanketing effect resulting in elevated temperatures at depth. 3D geological maps over the region have been produced from geologically constrained 3D inversions of gravity data. The inverted density models delineate regions of low density within the basement that are interpreted to be granitic bodies. The 3D maps include potential heat sources and thermally insulating cover, the key elements in generating an Enhanced Geothermal System (EGS) play. A region was extracted from the 3D geological map and used as a test-bed for modelling the temperature, heat flow and geothermal gradients. The test region was populated with thermal properties and boundary conditions were approximated. Temperatures were generated on a discretised version of the model within GeoModeller and were solved by explicit finite difference approximation using a Gauss-Seidel iterative scheme. The thermal properties that matched existing bottom hole temperatures and heat flows measurements were applied to the larger 3D map region. An enhancement of the GeoModeller software is to allow the input thermal properties to be specified as distribution functions. Multiple thermal simulations are carried out from the supplied distributions. Statistical methods are used to yield the probability estimates of the temperature and heat flow, reducing the risk of exploring for heat.