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Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations

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  • Tapia, John Frederick D.
  • Lee, Jui-Yuan
  • Ooi, Raymond E.H.
  • Foo, Dominic C.Y.
  • Tan, Raymond R.

Abstract

Carbon capture and storage (CCS) is an important technology option for reducing CO2 emissions into the atmosphere. The most commercially viable way to deploy CCS on a large scale is via coupling with enhanced oil recovery (EOR) operations. These operations allow the reduction of CO2 emissions through geological sequestration, coupled with generation of additional revenues through increased oil production as a result from CO2 re-injection through EOR. EOR also enables both CO2 utilization and storage (CCUS) as a carbon management strategy with long CO2 storage life. In practice, planning EOR operations takes into account mass balance and temporal aspects of a given site. When multiple oil reservoirs are involved, it is necessary to allocate the available CO2 supply and schedule suitable timing for EOR operations for these reservoirs. CO2 allocation and scheduling are thus important aspects in maximizing the economic benefits that arise from EOR operations. In this work, a mixed integer linear programming (MILP) model is developed to address CO2 allocation and scheduling issues for EOR operations. A discrete-time optimization approach is developed to consider both economic discounting and reservoir depletion. Two illustrative case studies are solved to illustrate the model.

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  • Tapia, John Frederick D. & Lee, Jui-Yuan & Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2016. "Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations," Applied Energy, Elsevier, vol. 184(C), pages 337-345.
    • Handle: RePEc:eee:appene:v:184:y:2016:i:c:p:337-345
    DOI: 10.1016/j.apenergy.2016.09.093
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    13. Vulin, Domagoj & Muhasilović, Lejla & Arnaut, Maja, 2020. "Possibilities for CCUS in medium temperature geothermal reservoir," Energy, Elsevier, vol. 200(C).
    14. Roussanaly, S. & Aasen, A. & Anantharaman, R. & Danielsen, B. & Jakobsen, J. & Heme-De-Lacotte, L. & Neji, G. & Sødal, A. & Wahl, P.E. & Vrana, T.K. & Dreux, R., 2019. "Offshore power generation with carbon capture and storage to decarbonise mainland electricity and offshore oil and gas installations: A techno-economic analysis," Applied Energy, Elsevier, vol. 233, pages 478-494.
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    17. Adnan, Muflih A. & Kibria, Md Golam, 2020. "Comparative techno-economic and life-cycle assessment of power-to-methanol synthesis pathways," Applied Energy, Elsevier, vol. 278(C).
    18. Chen, Bailian & Harp, Dylan R. & Lin, Youzuo & Keating, Elizabeth H. & Pawar, Rajesh J., 2018. "Geologic CO2 sequestration monitoring design: A machine learning and uncertainty quantification based approach," Applied Energy, Elsevier, vol. 225(C), pages 332-345.
    19. Calderón, Andrés J. & Pekney, Natalie J., 2020. "Optimization of enhanced oil recovery operations in unconventional reservoirs," Applied Energy, Elsevier, vol. 258(C).
    20. Ampomah, W. & Balch, R.S. & Cather, M. & Will, R. & Gunda, D. & Dai, Z. & Soltanian, M.R., 2017. "Optimum design of CO2 storage and oil recovery under geological uncertainty," Applied Energy, Elsevier, vol. 195(C), pages 80-92.

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