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http://bura.brunel.ac.uk/handle/2438/33038| Title: | Effectiveness of Electrokinetic EOR on Gas Condensate Banking Treatment—Proxy Modelling and Optimization |
| Authors: | Ikpeka, PM Duru, UI Onwukwe, S Ohia, NP Ugwu, J |
| Keywords: | gas condensate reservoirs;electrokinetic EOR;genetic algorithm;proxy modelling;EK-EOR;natural gas reservoir |
| Issue Date: | 18-Mar-2026 |
| Publisher: | MDPI |
| Citation: | Ikpeka, P.M. et al. (2026) 'Effectiveness of Electrokinetic EOR on Gas Condensate Banking Treatment—Proxy Modelling and Optimization', Gases, 6 (1), 16, pp. 1–18. doi: 10.3390/gases6010016. |
| Abstract: | Gas condensate banking can significantly reduce near-well gas productivity by as much as ~60% in tight gas reservoirs. Existing treatment techniques are resource demanding and could alter the reservoir structure permanently. This study investigates the effectiveness of enhanced electrokinetic oil recovery (EK-EOR) as a low-impact alternative for treating condensate banks. Using compositional reservoir simulation (CMG GEM), the influence of key reservoir and operational parameters—porosity, permeability, producer well location (i, j), injection rate, and injection pressure—on cumulative gas production (CGP) was examined. A Box–Behnken design of experiments was employed to generate 62 simulation runs, and a proxy model was developed to approximate full-field responses. Statistical validation showed strong model fidelity (R2 = 0.99, AAPE = 2.2%). The proxy was then optimized using a genetic algorithm (GA) to identify conditions that maximize gas recovery. Results indicate that lower injection rates and lower injection pressures maximize CGP through enhanced electro-osmotic flow and reduced water blocking, achieving a peak cumulative gas of 4.06 × 108 ft3. A secondary optimum at high injection pressure could be attributed to re-pressurization and partial re-vaporization of condensate near the wellbore. Reservoir quality also exerted a strong control: higher permeability and moderate porosity favoured gas yield, while optimal producer placement near the reservoir boundary increased drainage efficiency. This study demonstrates a systematic optimization framework combining design of experiments, proxy modelling, and evolutionary algorithms to evaluate EK-EOR performance. |
| Description: | Data Availability Statement: The data presented in this study are openly available in [https://doi.org/10.1002/ese3.70356]. |
| URI: | https://bura.brunel.ac.uk/handle/2438/33038 |
| DOI: | https://doi.org/10.3390/gases6010016 |
| Other Identifiers: | ORCiD: Princewill M. Ikpeka https://orcid.org/0000-0002-1174-1491 ORCiD: Ugochukwu I. Duru https://orcid.org/0000-0001-7920-8047 ORCiD: Stanley Onwukwe https://orcid.org/0000-0002-0924-5608 ORCiD: Nnaemeka P. Ohia https://orcid.org/0000-0002-4219-7062 ORCiD: Johnson Ugwu https://orcid.org/0000-0003-4023-2343 |
| Appears in Collections: | Department of Social and Political Sciences Research Papers * |
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