Rashidifard, Mahtab1,3, Giraud, Dr Jérémie1,3, Lindsay, A/Prof Mark1,3, Jessell, Prof Mark1,3, Ogarko, Dr Vitaliy1,2
1Centre for Exploration Targeting, University Of Western Australia, 35 Stirling Highway, WA Crawley 6009, Perth, Australia, 2International Centre for Radio Astronomy Research (ICRAR), University Of Western Australia, 35 Stirling Highway, WA Crawley 6009, Perth, Australia, 3Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Perth, Australia
Geological boundary parametrization of the subsurface that is consistent with geological and geophysical observations is the goal of 3D geological modelling. Several approaches have been
developed for geometric inversion and joint inversion of geophysical data sets. Recovering the geological boundary of units using the level-set gravity inversion method has been studied in recent
years with the focus on inversion for different numbers and shapes of the buried bodies.
We choose to focus on constraining 3D gravity inversion with sparse 2D lower-uncertainty data from seismic images within the modelling area which accounts for the uncertainty of the sparse data to make more reliable geological prediction.
We use a level-set approach to recover the geometry of geological bodies at depth. It is not limited by the number and shape of proposed geological units and is thus appropriate for gravity inversion of the geologically complex Yamarna terrane in the Yilgarn craton, Western Australia. The study focuses on the eastern zone of the area which is mostly composed of greenstones and meta-granitic rocks. As for mineral exploration, Au targets and their near-surface components are small in dimension, thus highresolution models are required for exploration purposes. However, high-resolution data are sparsely distributed within the study area. In this study, 2D seismic sections have been used for constraining the surface evolution of rock unit boundaries during the 3D gravity geometric inversion.
The proposed work is the first we know of that implements a level-set inversion method for data sets with different spatial coverage. Our results indicate that unit boundaries from gravity inversion can be very well constrained when lower-uncertainty, lower coverage data are available. Our approach avoids bias along with the interpretation and uncertainty of the sparse data is also taken into account, showing that the final model is consistent with all available data sets.
Our results suggest that the proposed method has the potential to bring the state of the art a step further towards building a 3D geological model which is consistent with available geological and geophysical data sets. As uncertainty plays an important role in geoscientific data and modelling, geometry inversion of gravity data in this study accounts for uncertainty, meaning that sparse and ill-defined parameters are allowed to vary during the inversion within a predefined threshold limit. The proposed method has resulted in a reduction in ill-posedness of the gravity inversion problem by creating a model with consistency to all high-resolution seismic sections sparsely distributed within the model.
We acknowledge the support of the MinEx CRC and the Loop: Enabling Stochastic 3D Geological Modelling (LP170100985) consortia. The work has been supported by the Mineral Exploration Cooperative Research Centre whose activities are funded by the Australian Government’s Cooperative Research Centre Programme. This is MinEx CRC Document 2020/43.
I completed my undergraduate and masters in petroleum exploration engineering. I started my Ph.D. at UWA (CET) as a minexCRC student focusing on data fusion methodologies for integrated inversion of geological and geophysical data. This presentation is part of my PhD project for integrating seismic and gravity with different coverage.