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Optimization of Discontinuous Polymer Flooding Processes for Offshore Oilfields Using a Novel PSO–ICA Algorithm

Author

Listed:
  • Engao Tang

    (State Key Laboratory of Offshore Oil & Gas Exploitation, Beijing 100028, China
    CNOOC Research Institute Limited, Beijing 100028, China)

  • Jian Zhang

    (State Key Laboratory of Offshore Oil & Gas Exploitation, Beijing 100028, China
    CNOOC Research Institute Limited, Beijing 100028, China)

  • Yi Jin

    (State Key Laboratory of Offshore Oil & Gas Exploitation, Beijing 100028, China
    CNOOC Research Institute Limited, Beijing 100028, China)

  • Lezhong Li

    (State Key Laboratory of Offshore Oil & Gas Exploitation, Beijing 100028, China
    CNOOC Research Institute Limited, Beijing 100028, China)

  • Anlong Xia

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

  • Bo Zhu

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

  • Xiaofei Sun

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

Abstract

Recently, discontinuous polymer flooding has been proposed and successfully applied in some offshore oilfields. The performance of discontinuous polymer flooding depends on various operational parameters, such as injection timing, polymer concentrations, and crosslinker concentrations of four types of chemical slugs. Because the number of the operational parameters are large and they are nonlinearly related, the traditional reservoir numerical simulation might not simultaneously obtain the optimal results of these operational parameters. In this study, to simulate the discontinuous polymer flooding processes, a simulation model was built using a commercial reservoir simulator (CMG STARS), in which the mechanisms of the four types of chemical slugs were considered, such as polymer viscosification, adsorption, and degradation. Then, a PSO–ICA algorithm was developed by using the PSO algorithm to improve the exploration ability of the ICA algorithm. The codes were written with MATLAB and linked to CMG STARS to perform optimization processes. Finally, the PSO–ICA algorithm was compared with the ICA and PSO algorithms on benchmark functions to verify its reliability and applied to optimize a discontinuous polymer flooding process in a typical offshore oilfield in Bohai Bay, China. The results showed that the developed PSO–ICA algorithm had lower iteration numbers, higher optimization accuracy, and faster convergence rate than these of PSO and ICA, indicating that it was an effective method for optimizing the operational parameters of discontinuous polymer flooding processes. Compared to the continuous polymer flooding, the discontinuous polymer flooding had a higher oil production rate, a lower water cut, and a lower residual oil saturation. The net present value of the optimal scheme of discontinuous polymer flooding reached 7.49 × 10 8 $, which is an increase of 6% over that of the scheme of continuous polymer flooding. More research including selecting more reasonable parameters of the PSO–ICA algorithm to increase its optimization accuracy and convergence rate, comparing with other available optimization algorithms, and verifying the performance of the optimal scheme of discontinuous polymer flooding in the practical offshore oilfield will be required in the future.

Suggested Citation

  • Engao Tang & Jian Zhang & Yi Jin & Lezhong Li & Anlong Xia & Bo Zhu & Xiaofei Sun, 2024. "Optimization of Discontinuous Polymer Flooding Processes for Offshore Oilfields Using a Novel PSO–ICA Algorithm," Energies, MDPI, vol. 17(8), pages 1-20, April.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1971-:d:1379862
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