Enhancing visualization approaches to support decision-making in the data assimilation steps of petroleum reservoir development and management processes

• Grant number: 24/00048-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2024
• End date: December 31, 2024
• Field of knowledge: Engineering - Mechanical Engineering
• Agreement: Equinor (former Statoil)
• Principal Investigator: Denis José Schiozer
• Grantee: Gabriel José Pereira
• Host Institution: Faculdade de Engenharia Mecânica (FEM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Company: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Mecânica (FEM)
• Associated research grant: 17/15736-3 - Engineering Research Centre in Reservoir and Production Management, AP.PCPE

Abstract

The goal of this project is to enhance and validate visualization approaches that support the tasks of petroleum analysts related to data assimilation processes. This project is a continuation of a work package from the Phase 1 of EPIC, whose main results were published in the paper of Turato et al. (2022).Given a set of models which the analysts suppose that appropriately represents a given reservoir, a data assimilation process may refine this set and discard models that do not honor the history data of the reservoir, given an error tolerance level. Petroleum analysts may use visualizations to analyze the partial results of an iterative data assimilation process and make decisions, such as accepting the models selected in an iteration of this process or refining the model set.In the Phase 1 of EPIC, Turato et al. (2022) developed a visualization prototype (NQDS Heatmap) that visualizes data from one iteration of a data assimilation process at a time. It provides three interactive, heatmap-based views of the values of a misfit measure (NQDS) regarding the following independent variables: reservoir models, wells, and dynamic attributes. An evaluation of this prototype revealed positive opinions of a small set of analysts about the potential of the tool, which may be used to complement other data assimilation approaches, and pointed out some opportunities for improvement.In this project, our methodology starts with studies about petroleum engineering, the main steps of the UNISIM's 12-steps methodology, and Webviz. After that, the student will do the integration of NQDS Heatmap with Webviz; this step includes analyzing the compatibility between the technologies used by both programs, and understanding how to inform the input data (and in which format) through Webviz for the prototype. Next, the student will classify (with the support of EPIC analysts) the enhancements that should be done in the prototype. These improvements include: (a) attending to suggestions made by reservoir engineers (see Turato et al. (2022)), such as an improved layout of controls, configurable color scales, and reordering and filtering resources they identified as useful for decision-making in data assimilation; (b) a better overview of data assimilation datasets, including more misfit measures and more iterations in the same visualization; and (c) the connection of these visualizations to spatial visualizations of the models of a reservoir, so that engineers can identify not only which models do not present the historical behavior, but also where these models fail on representing their reservoir. A subset of these tasks will be selected to be executed during the 12 months of this work package. A more formal evaluation of the prototype is also planned.