Advancing oil recovery: Systematic evaluation of EOR techniques from primary to tertiary stages
Author Identifier (ORCID)
Abstract
To enhance oil production efficiency, particularly in mature oil fields, the implementation of enhanced oil recovery (EOR) techniques is crucial for extracting additional crude oil that cannot be recovered by conventional methods. The main objective of this study is to develop and validate an integrated approach to systematically evaluate and select optimal EOR strategies. A study was presented based on reservoir simulation in one of the oil fields of Iraq using Eclipse 2022.4. The model was applied by subdividing the reservoir into 7,500 grid blocks, configured with one producer and four injectors (called 5-spot). During the primary recovery, the natural depletion mechanism resulted in modest oil production, necessitating the initiation of gas injection, which achieved a cumulative recovery of 3.6% by day 171. In the secondary phase, reinjection of the produced gas enhanced the recovery by an additional 6.5%. In tertiary recovery, the technique for order of preference by similarity to ideal solution (TOPSIS) method was used to help screen and rank the best EOR approaches in a systematic manner through a Python-based automation process. The most successful reconversion methods include miscible CO2 flooding, immiscible methane flooding, and the dual surfactant-polymer flooding method, while surfactant-polymer flooding has realized an overall cumulative oil recovery of 32.34% after 5 years. The findings demonstrate the importance of combining new simulation technology with systematic decision-making methods to optimize oil recovery and reservoir sustainability. It can be concluded that this integrated methodology, combining advanced reservoir simulation with the TOPSIS multicriteria decision-making approach, offers a robust and transparent framework for identifying optimal EOR strategies. Specifically, surfactant-polymer flooding demonstrated the most significant enhancement in oil recovery, highlighting the effectiveness of a data-driven systematic evaluation in maximizing hydrocarbon extraction and ensuring reservoir sustainability. The novelty of this research is in combining simulation of reservoirs (Eclipse 2022.4) with a TOPSIS decision-making model on the basis of Python to provide a data-driven, automatic, and transparent framework that advances previous methods of screening and selection of EOR.
Keywords
chemical flooding, CO 2 injection, enhanced oil recovery (EOR), Iraqi oil fields, multicriteria decision making (MCDM), reservoir simulation, surfactant-polymer flooding, technique for order of preference by similarity to ideal solution (TOPSIS) method
Document Type
Journal Article
Date of Publication
8-1-2026
Article Number
04026046
ISSN
07339402
Volume
152
Issue
4
Publication Title
Journal of Energy Engineering
Publisher
American Society of Civil Engineers
School
School of Engineering
Copyright
subscription content
Content Type
Metadata only
Recommended Citation
Rasul, I. F., Khorsheed, O. A., Altaher, A. Z., Arkawaz, M. S. A., Abdurahman, N. A., & Yuan, Y. (2026). Advancing oil recovery: Systematic evaluation of EOR techniques from primary to tertiary stages. Journal of Energy Engineering, 152(4). https://doi.org/10.1061/JLEED9.EYENG-6601