CO2 water-alternating-gas injection for enhanced oil recovery: Optimal well controls and half-cycle lengths
Abstract
We report that CO2 water-alternating-gas (WAG) injection is an enhanced oil recovery method designed to improve sweep efficiency during CO2 injection with the injected water to control the mobility of CO2 and to stabilize the gas front. Optimization of CO2 -WAG injection is widely regarded as a viable technique for controlling the CO2 and oil miscible process. Poor recovery from CO2 -WAG injection can be caused by inappropriately designed WAG parameters. In previous study (Chen and Reynolds, 2016), we proposed an algorithm to optimize the well controls which maximize the life-cycle net-present-value (NPV). However, the effect of injection half-cycle lengths for each injector on oil recovery or NPV has not been well investigated. In this paper, an optimization framework based on augmented Lagrangian method and the newly developed stochastic-simplex-approximate-gradient (StoSAG) algorithm is proposed to explore the possibility of simultaneous optimization of the WAG half-cycle lengths together with the well controls. Finally, the proposed framework is demonstrated with three reservoir examples.
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE; TUPREP Research Group Sponsored by Oil companies
- OSTI Identifier:
- 1427390
- Report Number(s):
- LA-UR-18-21036
Journal ID: ISSN 0098-1354
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Computers and Chemical Engineering
- Additional Journal Information:
- Journal Volume: 113; Journal Issue: C; Journal ID: ISSN 0098-1354
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42 ENGINEERING; 97 MATHEMATICS AND COMPUTING; 58 GEOSCIENCES; CO2-WAG; Production optimization; Optimal well controls; Half-cycle length; Enhanced oil recovery; Ensemble-based methods
Citation Formats
Chen, Bailian, and Reynolds, Albert C. CO2 water-alternating-gas injection for enhanced oil recovery: Optimal well controls and half-cycle lengths. United States: N. p., 2018.
Web. doi:10.1016/j.compchemeng.2018.03.006.
Chen, Bailian, & Reynolds, Albert C. CO2 water-alternating-gas injection for enhanced oil recovery: Optimal well controls and half-cycle lengths. United States. https://doi.org/10.1016/j.compchemeng.2018.03.006
Chen, Bailian, and Reynolds, Albert C. Sun .
"CO2 water-alternating-gas injection for enhanced oil recovery: Optimal well controls and half-cycle lengths". United States. https://doi.org/10.1016/j.compchemeng.2018.03.006. https://www.osti.gov/servlets/purl/1427390.
@article{osti_1427390,
title = {CO2 water-alternating-gas injection for enhanced oil recovery: Optimal well controls and half-cycle lengths},
author = {Chen, Bailian and Reynolds, Albert C.},
abstractNote = {We report that CO2 water-alternating-gas (WAG) injection is an enhanced oil recovery method designed to improve sweep efficiency during CO2 injection with the injected water to control the mobility of CO2 and to stabilize the gas front. Optimization of CO2 -WAG injection is widely regarded as a viable technique for controlling the CO2 and oil miscible process. Poor recovery from CO2 -WAG injection can be caused by inappropriately designed WAG parameters. In previous study (Chen and Reynolds, 2016), we proposed an algorithm to optimize the well controls which maximize the life-cycle net-present-value (NPV). However, the effect of injection half-cycle lengths for each injector on oil recovery or NPV has not been well investigated. In this paper, an optimization framework based on augmented Lagrangian method and the newly developed stochastic-simplex-approximate-gradient (StoSAG) algorithm is proposed to explore the possibility of simultaneous optimization of the WAG half-cycle lengths together with the well controls. Finally, the proposed framework is demonstrated with three reservoir examples.},
doi = {10.1016/j.compchemeng.2018.03.006},
journal = {Computers and Chemical Engineering},
number = C,
volume = 113,
place = {United States},
year = {Sun Mar 11 00:00:00 EST 2018},
month = {Sun Mar 11 00:00:00 EST 2018}
}
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