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Optimum design of CO2 storage and oil recovery under geological uncertainty


  • Ampomah, W.
  • Balch, R.S.
  • Cather, M.
  • Will, R.
  • Gunda, D.
  • Dai, Z.
  • Soltanian, M.R.


This paper presents an integrated numerical framework to co-optimize EOR and CO2 storage performance under uncertainty in the Farnsworth Unit (FWU) oil field in Ochiltree County, Texas. The framework includes a field-scale compositional reservoir multiphase flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. Equation of state parameters were tuned to achieve field measured fluid properties and subsequently used to predict the minimum miscible pressure (MMP).

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:195:y:2017:i:c:p:80-92
    DOI: 10.1016/j.apenergy.2017.03.017

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    References listed on IDEAS

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    Cited by:

    1. Zhang, Xiaowen & Liu, Helei & Liang, Zhiwu & Idem, Raphael & Tontiwachwuthikul, Paitoon & Jaber Al-Marri, Mohammed & Benamor, Abdelbaki, 2018. "Reducing energy consumption of CO2 desorption in CO2-loaded aqueous amine solution using Al2O3/HZSM-5 bifunctional catalysts," Applied Energy, Elsevier, vol. 229(C), pages 562-576.
    2. Chen, Bailian & Pawar, Rajesh J., 2019. "Characterization of CO2 storage and enhanced oil recovery in residual oil zones," Energy, Elsevier, vol. 183(C), pages 291-304.
    3. Ali Goudarzi & Seyyed A. Hosseini & Diana Sava & Jean†Philippe Nicot, 2018. "Simulation and 4D seismic studies of pressure management and CO2 plume control by means of brine extraction and monitoring at the Devine Test Site, South Texas, USA," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 8(1), pages 185-204, February.
    4. Dai, Zhenxue & Zhang, Ye & Bielicki, Jeffrey & Amooie, Mohammad Amin & Zhang, Mingkan & Yang, Changbing & Zou, Youqin & Ampomah, William & Xiao, Ting & Jia, Wei & Middleton, Richard & Zhang, Wen & Sun, 2018. "Heterogeneity-assisted carbon dioxide storage in marine sediments," Applied Energy, Elsevier, vol. 225(C), pages 876-883.
    5. 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.
    6. Wang, Xiao & van ’t Veld, Klaas & Marcy, Peter & Huzurbazar, Snehalata & Alvarado, Vladimir, 2018. "Economic co-optimization of oil recovery and CO2 sequestration," Applied Energy, Elsevier, vol. 222(C), pages 132-147.
    7. Jiang, Jieyun & Rui, Zhenhua & Hazlett, Randy & Lu, Jun, 2019. "An integrated technical-economic model for evaluating CO2 enhanced oil recovery development," Applied Energy, Elsevier, vol. 247(C), pages 190-211.
    8. Turgay Ertekin & Qian Sun, 2019. "Artificial Intelligence Applications in Reservoir Engineering: A Status Check," Energies, MDPI, Open Access Journal, vol. 12(15), pages 1-22, July.
    9. Zhou, Xiang & Yuan, Qingwang & Rui, Zhenhua & Wang, Hanyi & Feng, Jianwei & Zhang, Liehui & Zeng, Fanhua, 2019. "Feasibility study of CO2 huff 'n' puff process to enhance heavy oil recovery via long core experiments," Applied Energy, Elsevier, vol. 236(C), pages 526-539.
    10. Mohamad Reza Soltanian & Mohammad Amin Amooie & David Cole & David Graham & Susan Pfiffner & Tommy Phelps & Joachim Moortgat, 2018. "Transport of perfluorocarbon tracers in the Cranfield Geological Carbon Sequestration Project," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 8(4), pages 650-671, August.


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