Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3641-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-3641-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 May 2022
Model description paper |
| 09 May 2022
| 09 May 2022
Blockworlds 0.1.0: a demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models
Richard Scalzo
CORRESPONDING AUTHOR
School of Mathematics and Statistics, The University of Sydney, Darlington, NSW 2008, Australia
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
Mark Lindsay
Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Crawley, WA 6009, Australia
CSIRO Mineral Resources, Kensington, WA 6151, Australia
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
Mark Jessell
Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Crawley, WA 6009, Australia
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
Guillaume Pirot
Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Crawley, WA 6009, Australia
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
Jeremie Giraud
Centre for Exploration Targeting, School of Earth Sciences, The University of Western Australia, Crawley, WA 6009, Australia
RING Team, GeoRessources, Université de Lorraine, 54000, Nancy, France
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
Edward Cripps
Department of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009, Australia
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
Sally Cripps
School of Mathematics and Statistics, The University of Sydney, Darlington, NSW 2008, Australia
CSIRO Data61, Eveleigh, NSW 2015, Australia
ARC Industrial Transformation and Training Centre in Data Analytics for Resources and the Environment (DARE), Australia
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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, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
This paper addresses numerical challenges in reasoning about geological models constrained by...
