Abstract
We study the question of how visual analysis can support the comparison of spatio-temporal ensemble data of liquid and gas flow in porous media. To this end, we focus on a case study, in which nine different research groups concurrently simulated the process of injecting CO\(_2\) into the subsurface. We explore different data aggregation and interactive visualization approaches to compare and analyze these nine simulations. In terms of data aggregation, one key component is the choice of similarity metrics that define the relationship between different simulations. We test different metrics and find that using the machine-learning model “S4” (tailored to the present study) as metric provides the best visualization results. Based on that, we propose different visualization methods. For overviewing the data, we use dimensionality reduction methods that allow us to plot and compare the different simulations in a scatterplot. To show details about the spatio-temporal data of each individual simulation, we employ a space-time cube volume rendering. All views support linking and brushing interaction to allow users to select and highlight subsets of the data simultaneously across multiple views. We use the resulting interactive, multi-view visual analysis tool to explore the nine simulations and also to compare them to data from experimental setups. Our main findings include new insights into ranking of simulation results with respect to experimental data, and the development of gravity fingers in simulations.
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Data availability
The datasets which are used in this manuscript, mainly the benchmark study results, are available in the Fluidflower repositories, https://github.com/fluidflower. The code repository is available at https://github.com/rbnbr/VisualSpatioTempEnsembleAnalysis.
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Acknowledgements
Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2075 - 390740016 and Project Number 327154368 - SFB 1313. Partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 251654672 - TRR 161, project A08. We acknowledge the support by the Stuttgart Center for Simulation Science (SimTech). Parts of this work have been done in the context of CEDAS, the Center for Data Science at the University of Bergen.
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Open Access funding enabled and organized by Projekt DEAL. Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC2075 - 390740016 and Project Number 327154368 - SFB 1313. Partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 251654672 - TRR 161, project A08.
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All authors contributed to the conceptual design of our work, and made substantial contributions in writing and revising this manuscript. The implementation of the concepts, data preparation, analysis, and writing of the first draft were performed by RB. All authors read and approved the final manuscript.
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Bauer, R., Ngo, Q.Q., Reina, G. et al. Visual Ensemble Analysis of Fluid Flow in Porous Media Across Simulation Codes and Experiment. Transp Porous Med 151, 1003–1031 (2024). https://doi.org/10.1007/s11242-023-02019-y
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DOI: https://doi.org/10.1007/s11242-023-02019-y