Proxy Model Development for the Optimization of Water Alternating CO 2 Gas for Enhanced Oil Recovery

D Aqnan Marusaha Matthew, Ashkan Jahanbani Ghahfarokhi (), Cuthbert Shang Wui Ng and Menad Nait Amar
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D Aqnan Marusaha Matthew: Department of Geoscience and Petroleum, Norwegian University of Science and Technology, 7031 Trondheim, Norway
Ashkan Jahanbani Ghahfarokhi: Department of Geoscience and Petroleum, Norwegian University of Science and Technology, 7031 Trondheim, Norway
Cuthbert Shang Wui Ng: Department of Geoscience and Petroleum, Norwegian University of Science and Technology, 7031 Trondheim, Norway
Menad Nait Amar: Departement Etudes Thermodynamiques, Division Laboratoires, Sonatrach, Boumerdes 35000, Algeria

Energies, 2023, vol. 16, issue 8, 1-19

Abstract: Optimization studies are an important task in reservoir engineering practices such as production optimization and EOR (Enhanced Oil Recovery) assessments. However, they are extensive studies with many simulations that require huge computational effort and resources. In terms of EOR, CO 2 injection is one of the most common methods employed due to a high recovery potential and environmental benefits. To assess the feasibility of CO 2 -EOR projects, a reservoir design study must be conducted before optimization is performed. Some studies have demonstrated the advantages of employing proxy models to perform this task in terms of saving huge amounts of computer memory space and time. In this study, proxy models were developed to solve a multi-objective optimization problem using NSGA-II (Non-dominated Sorting Genetic Algorithm II) in two selected reservoir models. The study was performed for a CO 2 -WAG (Water Alternating Gas) application, where gas and water injection rates and half-cycle lengths were assessed to maximize the oil recovery and CO 2 stored in the reservoir. One model represents a simple geological model (the Egg Model), while the other represents a complex model (the Gullfaks Model). In this study, the good performance of the proxy models generated accurate results that could be improved by increasing the amount of sampling and segmenting the behavior of the reservoir model (depending on the complexity of the reservoir model). The developed proxies have an average error of less than 2% (compared with simulation results) and are concluded to be robust based on the blind test results. It has also been found that to reach the maximum oil recovery using CO 2 -WAG, the maximum gas injection rate with the minimum water injection rate is required. However, this configuration may result in a reduction in the total CO 2 stored in the reservoir.

Keywords: proxy model; CO 2 -WAG; optimization study; NSGA-II; CO 2 storage (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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