Joint Optimization of Well Completions and Controls for CO₂ Enhanced Oil Recovery and Storage

Conference · Sun Aug 30 00:00:00 EDT 2020

DOI:https://doi.org/10.2118/200316-ms· OSTI ID:1825453

Chen, Bailian  ^[1]; Pawar, Rajesh J.  ^[1]

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1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

CO₂ storage through CO₂ enhanced oil recovery (EOR) is considered as one of the technologies to help promote larger scale deployment of CO₂ storage because of associated economic benefits through oil recovery, 45Q tax credits and the utilization of existing infrastructure. The objective of this study is to demonstrate how optimal reservoir management and operation strategies (including well completions and controls) can be used to optimize both CO₂ storage and oil recovery. The optimization problem was focused on jointly estimating the well completions (i.e., fraction of injection/production well perforations in each reservoir layer) and CO₂ injection/oil production controls that maximize the net present value (NPV) in a CO₂ EOR and storage operation. We utilized the newly developed StoSAG algorithm, one of the most efficient optimization algorithms in the reservoir management community, to solve the optimization problem. The performance of joint optimization approach was compared with the performance of well control only optimization approach. In addition, the performance of co-optimization of CO₂ storage and oil recovery approach was compared with the performances of maximization of only CO₂ storage and maximization of only oil recovery approaches. The optimization results showed that a joint optimization of well completions and well controls can achieve an 8.84% higher final NPV than the one obtained from the optimization of only well controls. It was observed that the NPV incremental for joint optimization is mainly due to the fact that the optimal well completions and controls approach results in efficient CO₂ storage and oil production from different reservoir layers depending on the differences in individual layer properties. Comparison of co-optimization (i.e., maximization of NPV) and maximization of only CO₂ storage or only oil recovery showed that the co-optimization and maximization of only oil recovery result in significantly higher final NPV than that obtained through maximization of only CO₂ storage approach while maximization of only CO₂ storage can achieve significantly higher CO₂ storage in the reservoir compared to the other two scenarios. The similar results for co-optimization and maximization of oil production are obtained because of the difference in oil revenue compared to CO₂ storage tax credit. To the best of our knowledge, this is the first study in oil/gas industry and CO₂ storage community to perform joint optimization of well completions and well controls in the fields. We expect that the proposed optimization framework will be a useful and efficient tool for field engineers to optimally manage CO₂ EOR projects to maximize revenue through oil recovery as well as CO₂ storage by taking advantage of the new 45Q tax law.

• Research Organization: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE Office of Fossil Energy (FE)
• DOE Contract Number: 89233218CNA000001
• OSTI ID: 1825453
• Report Number(s): LA-UR-21-25248
• Resource Relation: Conference: SPE Improved Oil Recovery Conference, Virtual, 31 Aug - 4 Sep 2020
• Country of Publication: United States
• Language: English

Related Subjects

Earth Sciences
enhanced recovery
optimization problem
subsurface storage
us government
well completion
optimization strategy
oil production
optimization
open fraction
CO2
Improved and Enhanced Recovery
Storage Reservoir Engineering
Information Management and Systems
CO2 capture and sequestration
Artificial intelligence