Sustainable Reservoir Management: Simulating Water Flooding to Optimize Oil Recovery in Heterogeneous Reservoirs Through the Evaluation of Relative Permeability Models

Atif Ismail, Farshid Torabi (), Saman Azadbakht, Faysal Ahammad, Qamar Yasin, David A. Wood and Erfan Mohammadian
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Atif Ismail: Energy Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada
Farshid Torabi: Energy Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada
Saman Azadbakht: Energy Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada
Faysal Ahammad: Energy Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada
Qamar Yasin: National Key Laboratory of Continental Shale Oil, Northeast Petroleum University, Daqing 163318, China
David A. Wood: DWA Energy Limited, Lincoln LN6, UK
Erfan Mohammadian: National Key Laboratory of Continental Shale Oil, Northeast Petroleum University, Daqing 163318, China

Sustainability, 2025, vol. 17, issue 6, 1-23

Abstract: The relative permeability of a fluid plays a vital role in numerical simulation studies of multiphase flow. Several empirical models are used to estimate relative permeability, but these models are often inaccurate due to differences in the assumptions under which it is formulated. A specific model of relative permeability can significantly impact the results of a simulation, so it is essential to select the most appropriate model. This study incorporates the numerical simulation of water flooding into several well-known classical and non-linear predictive models of relative permeability. Based on the comparison of classical predictive models, the results reveal that the predictions from the classical models were more closely aligned with experimental data during the pre-water injection phase. However, after the water injection, the models overestimated the average reservoir pressure. Due to this limitation, all classical models were unable to match water-cut data accurately. In contrast, the proposed non-linear model demonstrated superior performance in matching the water-cut data. Compared to classical models, it accurately predicted water cut and reservoir performance. The proposed model developed for sandstone reservoirs was able to predict k rw (the relative permeability of water) and k ro (the relative permeability of oil) with low errors ( RMSE = 0.028 and 0.01, respectively). The R 2 values of the proposed model for k ro and k rw were 0.97 and 0.98, indicating excellent agreement with the experimental results. The proposed model also demonstrated a significant improvement in the accuracy of simulation data matching after water injection. Additionally, this model provides flexibility in parameter tuning and a solid foundation for relative permeability model development. By improving relative permeability modeling, this study enhances water flooding simulations for more efficient resource utilization and reduced environmental impact. This new approach improves the selection and development of appropriate models for numerical simulations of water flooding in sandstone reservoirs thereby enhancing predictions of reservoir performance.

Keywords: relative permeability; water flooding; static modeling; numerical simulation; oil reservoir performance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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