Chemical Plugging Optimization for Channeling Control During CO2 Flooding Using Multi-Surrogate Collaborative Prescreening

During CO2 flooding, unfavorable mobility ratios and interlayer heterogeneity can induce preferential flow through high-permeability intervals, leaving central low-permeability intervals insufficiently swept and rich in remaining oil. To address the strong coupling among composite chemical-plugging parameters and the high computational cost of CMG-STARS simulations for individual candidate strategies, this study proposes an adaptive heterogeneous ensemble surrogate-assisted differential-evolution method (AHES-DE). The method integrates radial basis function, inverse-distance weighting, and ridge-linear surrogate models, whose predictions are dynamically weighted according to leave-one-out cross-validation errors. Explorer, Exploiter, and Robust roles are used for global search, local exploitation, and prediction-risk control, respectively, with differential-evolution offspring generation embedded in the Exploiter role. A stratified one-injector–four-producer conceptual model with a 21 × 21 × 6 grid was used to establish a numerical evaluation workflow comprising CO2 injection, preferential-channel development, composite chemical plugging, and subsequent displacement. Mobile chemical concentration, adsorbed preformed particle gel (PPG) mass density, water-phase resistance factor, oil saturation at a common termination time, and net economic value (NEV) were used to evaluate treatment performance. Under an equal budget of 150 high-fidelity CMG-STARS evaluations per method, the reported single-seed final best-so-far NEVs were 2.45405 × 109 CNY for AHES-DE, 2.44888 × 109 CNY for differential evolution (DE), and 2.44698 × 109 CNY for Latin hypercube sampling (LHS). The layer-resolved responses indicate more pronounced chemical transport, retention, and resistance development in the upper and lower preferential intervals, while the oil saturation in the central low-permeability interval decreased further after treatment, indicating that flow redistribution facilitated remaining-oil mobilization. A realistic geological model was further used to assess the engineering consistency of the identified flow-control mechanism.

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Processes
Published
2026-08-25
DOI
https://doi.org/10.3390/pr14172716
Primary Topic
Enhanced Oil Recovery Techniques
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article
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Chemical Plugging Optimization for Channeling Control During CO2 Flooding Using Multi-Surrogate Collaborative Prescreening

Xu Xiang, Qinghao Sun, Lijuan Huang, Xu Luo et al.
Processes
Enhanced Oil Recovery Techniques
article

Chemical Plugging Optimization for Channeling Control During CO2 Flooding Using Multi-Surrogate Collaborative Prescreening

Xu Xiang, Qinghao Sun, Lijuan Huang, Xu Luo, Jingwei Huang, Yitong Zhou, Hui Zhao, Zongfa Li
article en

Abstract

During CO2 flooding, unfavorable mobility ratios and interlayer heterogeneity can induce preferential flow through high-permeability intervals, leaving central low-permeability intervals insufficiently swept and rich in remaining oil. To address the strong coupling among composite chemical-plugging parameters and the high computational cost of CMG-STARS simulations for individual candidate strategies, this study proposes an adaptive heterogeneous ensemble surrogate-assisted differential-evolution method (AHES-DE). The method integrates radial basis function, inverse-distance weighting, and ridge-linear surrogate models, whose predictions are dynamically weighted according to leave-one-out cross-validation errors. Explorer, Exploiter, and Robust roles are used for global search, local exploitation, and prediction-risk control, respectively, with differential-evolution offspring generation embedded in the Exploiter role. A stratified one-injector–four-producer conceptual model with a 21 × 21 × 6 grid was used to establish a numerical evaluation workflow comprising CO2 injection, preferential-channel development, composite chemical plugging, and subsequent displacement. Mobile chemical concentration, adsorbed preformed particle gel (PPG) mass density, water-phase resistance factor, oil saturation at a common termination time, and net economic value (NEV) were used to evaluate treatment performance. Under an equal budget of 150 high-fidelity CMG-STARS evaluations per method, the reported single-seed final best-so-far NEVs were 2.45405 × 109 CNY for AHES-DE, 2.44888 × 109 CNY for differential evolution (DE), and 2.44698 × 109 CNY for Latin hypercube sampling (LHS). The layer-resolved responses indicate more pronounced chemical transport, retention, and resistance development in the upper and lower preferential intervals, while the oil saturation in the central low-permeability interval decreased further after treatment, indicating that flow redistribution facilitated remaining-oil mobilization. A realistic geological model was further used to assess the engineering consistency of the identified flow-control mechanism.

ProcessesVol. 14(17)
Yangtze University (CN), China University of Geosciences (CN), National Institute of Clean and Low-Carbon Energy (CN)
Clean water and sanitation
Openalex Percentile: Top 13%
Enhanced Oil Recovery Techniques
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