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Title: Capacity assessment and co-optimization of CO2 storage and enhanced oil recovery in residual oil zones

Journal Article · · Journal of Petroleum Science and Engineering
ORCiD logo [1]; ORCiD logo [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
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Residual oil zones (ROZs) are increasingly being commercially exploited using CO2-enhanced oil recovery (CO2-EOR) 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-alternatinggas 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.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE Office of Fossil Energy (FE)
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1558978
Alternate ID(s):
OSTI ID: 1557015
Report Number(s):
LA-UR-19-24764
Journal Information:
Journal of Petroleum Science and Engineering, Vol. 182, Issue C; ISSN 0920-4105
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 13 works
Citation information provided by
Web of Science

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