Cooperative geophysical inversion integrated with 3D geological modelling in the Boulia region, QLD

Reconciling rock unit boundary geometry is crucial for geological and geophysical studies aiming to achieve a comprehensive 3D subsurface model. To create a unified 3D parametrization suitable for both geological modeling and geophysical inversion, an integrated approach utilizing implicit modeling is essential. However, a key challenge lies in encapsulating all pertinent information within the 3D model, ensuring compatibility with the utilized datasets and existing constraints. In this study, we present a workflow that enables the generation of an integrated 3D subsurface model primarily using gravity and reflection seismic datasets. Our approach involves a cooperative geophysical inversion workflow, which incorporates the inverted model from the reflection seismic data while leveraging sparse petrophysical information. Despite advances in integrated modelling, the incorporation of implicit modelling approaches in cooperative inversion workflows remains unexplored. In our gravity inversion process, we employ a generalized level set method to refine the boundaries of rock units in the prior model. We integrate the inverted model, derived from seismic and other sparse petrophysical datasets, to create a comprehensive 3D prior model. To enhance the integration of reflection seismic datasets in the level set inversion, we introduce a weighting uncertainty matrix containing constraint terms. This step refines the model's accuracy and ensures greater consistency. Finally, we search for any missing rock units within inverted model through nucleation investigations. The introduced methodology has undergone successful testing in the Boulia region (Southern Mount Isa, Queensland), utilizing two 2D reflection seismic profiles and regional gravity datasets. This study primarily aims to reconstruct the geometry of major structures within the basement units and the basin at a regional scale. By combining seismic profiles and gravity datasets with constraining information, we are able to create a 3D model of the area that accurately represents distinct rock units and their boundary geometries. Additionally, relevant legacy datasets and prior modeling results from the region have been incorporated and refined, ensuring that the final model aligns with all available knowledge about the area.