11 citations · 11 across the 2 of their papers we have counts for
3 papers
Finite Volume Neural Network: Modeling Subsurface Contaminant Transport
Timothy Praditia, Matthias Karlbauer, Sebastian Otte +3
Data-driven modeling of spatiotemporal physical processes with general deep learning methods is a highly challenging task. It is further exacerbated by the limited availability of…
Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation
Stefania Scheurer, Aline Schäfer Rodrigues Silva, Farid Mohammadi +4
Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface…
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario
Markus Köppel, Fabian Franzelin, Ilja Kröker +8
A variety of methods is available to quantify uncertainties arising with\-in the modeling of flow and transport in carbon dioxide storage, but there is a lack of thorough compariso…