by Miguel Angelo Mena Póvoa, Samuel Oliveira Da Silva, Celmar Guimarães da Silva, presented at CGVCVIP 2023, June 2023.
Petroleum engineers usually create a set of hundreds of models of a given oil reservoir under analysis to represent its uncertainties. Assisted optimization approaches may help engineers to select a subset of these models (a.k.a. representative models, or RMs for short), which is used in computational flow simulations in replacement of the original set, aiming to reduce the total simulation runtime without changing the quality of these results. Despite the power of visualization techniques to help people to understand multidimensional datasets like the ones provided in this scenario, we noted a few efforts that use these techniques to help petroleum engineers to assist the selection of RMs. In this context, our research aims to test the hypothesis that it is possible to improve how interactive visualization resources are currently used to aid decision-making regarding the selection of RMs, mainly in the presence of multiple sets of RMs or multiple variables (obtained from running model simulations). This work presents our first steps towards this goal: (a) literature review and (b) definition of visualization prototypes that aim to help the analysis of RMs regarding the values of the variables provided by simulation outputs, and the risk curves associated with these variables. As preliminary results, we present our proposed interactive visualizations and briefly point out the design rationale behind these prototypes.