Blockworlds 0.1.0: A demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models
Abstract. Parametric geological models such as implicit or kinematic models provide low-dimensional, interpretable representations of 3-D geological structures. Combining these models with geophysical data in a probabilistic joint inversion framework provides an opportunity to directly quantify uncertainty in geological interpretations. For best results, the projection of the geological parameter space onto the finite-resolution discrete basis of the geophysical calculation must be faithful within the power of the data to discriminate. We show that naively exporting voxelised geology as done in commonly used geological modeling tools can easily produce a poor approximation to the true geophysical likelihood, degrading posterior inference for structural parameters. We then demonstrate a numerical forward-modeling scheme for calculating anti-aliased rock properties on regular meshes for use with gravity and magnetic sensors. Finally, we explore anti-aliasing in the context of a kinematic forward model for simple tectonic histories, showing its impact on the structure of the geophysical likelihood for gravity anomaly.
