Journal
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
Volume 182, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.petrol.2019.106342
Keywords
Residual oil zones; CO2 storage; Enhanced oil recovery; Capacity assessment; Optimization
Categories
Funding
- US Department of Energy through the Los Alamos National Laboratory
- National Nuclear Security Administration of U.S. Department of Energy [89233218CNA000001]
- U.S. Department of Energy's (DOE) Office of Fossil Energy's Coal Research program
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Residual oil zones (ROZs) are increasingly being commercially exploited using CO2-enhanced oil recovery (CO2EOR) method. In this study, CO2 storage potential, long-term CO2 fate and oil recovery potential in ROZs are characterized based on a reservoir model for Goldsmith-Landreth San Andres Unit in the Permian Basin. The effects of CO2 injection rates, well patterns (five-spot and line-drive), well spacings, injection modes (continuous CO2 injection and water-alternating-gas injection) on the CO2 retention in the reservoir and the oil production are investigated. After the preliminary assessment of CO2 storage and EOR potentials in ROZs, we next develop a novel approach based on a newly developed optimization algorithm-Stochastic Simplex Approximate Gradient (StoSAG) and predictive empirical models constructed using machine learning technique to co-optimize CO2 storage and oil recovery in ROZs. The performance of co-optimization of CO2 storage and oil recovery is compared with the performance of optimization of only CO2 storage.
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