Preprints
https://doi.org/10.5194/gmd-2021-187
https://doi.org/10.5194/gmd-2021-187

Submitted as: model description paper 17 Aug 2021

Submitted as: model description paper | 17 Aug 2021

Review status: this preprint is currently under review for the journal GMD.

Blockworlds 0.1.0: A demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models

Richard Scalzo1,4, Mark Lindsay2,4, Mark Jessell2,4, Guillaume Pirot2,4, Jeremie Giraud2,4, Edward Cripps3,4, and Sally Cripps1,4 Richard Scalzo et al.
  • 1School of Mathematics and Statistics, The University of Sydney, Darlington, NSW 2008, Australia
  • 2Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Crawley, WA 6009, Australia
  • 3Department of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009, Australia
  • 4ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE)

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.

Richard Scalzo et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-187', Anonymous Referee #1, 20 Sep 2021
  • CEC1: 'Comment on gmd-2021-187', Juan Antonio Añel, 12 Oct 2021
  • RC2: 'Comment on gmd-2021-187', Florian Wellmann, 25 Oct 2021

Richard Scalzo et al.

Model code and software

Blockworlds Richard Scalzo https://doi.org/10.5281/zenodo.5195426

Richard Scalzo et al.

Viewed

Total article views: 458 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
366 86 6 458 3 0
  • HTML: 366
  • PDF: 86
  • XML: 6
  • Total: 458
  • BibTeX: 3
  • EndNote: 0
Views and downloads (calculated since 17 Aug 2021)
Cumulative views and downloads (calculated since 17 Aug 2021)

Viewed (geographical distribution)

Total article views: 378 (including HTML, PDF, and XML) Thereof 378 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 25 Oct 2021
Download
Short summary
This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, does not result in unrealistically large changes to resulting sensor measurements, as occurs presently using several popular modeling packages.