DarSIA image analysis of FluidFlower International Benchmark dataset.
A. Preliminaries:
The FluidFlower International Benchmark dataset can be found at: Kris Eikehaug et al., The International FluidFlower benchmark study dataset (2023), https://zenodo.org/record/7510589#.Y9pKo3bMKQ4
Once donwloaded, it can be analyzed using the code included in this repository, allowing to reproduce the results in: Martin A. Fernø et al., Room-scale CO2 injections in a physical reservoir model with faults (2023), https://arxiv.org/abs/2301.06397
In order to run the analysis, one has to download and install DarSIA: Jakub W. Both et al., DarSIA v1.0 (2023),
For an introduction to DarSIA, we refer to: Jan M. Nordbotten et al., DarSIA: An open-source Python toolbox for two-scale image processing of dynamics in porous media (2023), https://arxiv.org/abs/2301.05455
B. Instructions:
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In the main directory of the repo, run: 'python setup.py develop'.
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Update the file 'image_analysis/data.json'. Follow the instructions listed in the template.
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Run './run.sh', producing intermediate results as cache, and storing all main results in the results folder specified in 'data.json'. These include in particular those required for the sparse data analysis. In addition some spatia;l maps are created on coarser meshed with 1cm grid size.