Visual Ensemble Analysis of Fluid Flow in Porous Media across Simulation Codes and Experiment

TL;DR

This paper presents a visual analysis framework for comparing multiple fluid flow simulations in porous media, integrating machine learning-based similarity metrics and interactive visualization techniques to enhance understanding and validation against experimental data.

Contribution

It introduces a novel visualization approach combining machine learning metrics and multi-view visualization for ensemble simulation comparison in porous media.

Findings

Improved ranking of simulations relative to experimental data

Identification of gravity fingers in simulations

Effective visualization of spatio-temporal flow dynamics

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 CO2 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 relation between the different simulations. We test different metrics and find that a fine-tuned machine-learning based 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. 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.