Implementation of a practical CLFDM using the methods developed in Phases 1 and 2

• Grant number: 24/09323-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: August 01, 2024
• End date: July 31, 2028
• Field of knowledge: Engineering - Mechanical Engineering
• Agreement: Equinor (former Statoil)
• Principal Investigator: Denis José Schiozer
• Grantee: Beatriz dos Santos Santana
• Host Institution: Centro de Estudos de Energia e Petróleo (CEPETRO). 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

Although continuous advances in the computational domain were observed in the pastdecades, numerical simulation is still challenging when applied for some kind of fields, duesome characteristics: level of heterogeneity, field size, necessity to use compositionalsimulation, among others. When performing probabilistic procedures that demand high numberof simulation runs, the time spent for model-based decision analysis can become very high,making the application of these procedures unfeasible in practical applications.In order to minimize the risks involved in the project, Schiozer et al. (2019) proposed a12-steps model-based methodology for dealing with uncertainties to assist the decision-makingduring the development and production phase of oil fields (closed-loop field development andmanagement - CLFDM). The methodology involves reservoir simulations, risk analysis, dataassimilation, uncertainty reduction techniques, selection of representative models and selectionof production strategies under uncertainty, in 12 steps that can be repeated as new information isacquired and inserted to the studies. Although a promising process, it can be very time-consuming for practical applications, depending on the complexity of the simulation models andthe number of simulation runs.Some other projects aim to evaluate possible simplifications to be made in the processor in the simulation models to speed-up the decision analysis process, without losing accuracyin the results and without affecting the final decisions. In this project, the main goal is theapplication an improved CLFDM process, using the insights obtained in other research projects,to make CLFDM applicable in practical situations.