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Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study

Author

Listed:
  • Jin Zhao

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
    Department of Energy and Petroleum Engineering, University of North Dakota, Grand Forks, ND 58202, USA)

  • Lu Jin

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • Xue Yu

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • Nicholas A. Azzolina

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • Xincheng Wan

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • Steven A. Smith

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • Nicholas W. Bosshart

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • James A. Sorensen

    (Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA)

  • Kegang Ling

    (Department of Energy and Petroleum Engineering, University of North Dakota, Grand Forks, ND 58202, USA)

Abstract

Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO 2 , rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.

Suggested Citation

  • Jin Zhao & Lu Jin & Xue Yu & Nicholas A. Azzolina & Xincheng Wan & Steven A. Smith & Nicholas W. Bosshart & James A. Sorensen & Kegang Ling, 2024. "Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study," Energies, MDPI, vol. 17(17), pages 1-32, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4200-:d:1462142
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    References listed on IDEAS

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    1. Lei Li & Xue Zhang & Jiahui Liu & Qiuheng Xie & Xiaomei Zhou & Jianyang Zheng & Yuliang Su, 2022. "Research Progress and Prospect of Carbon Dioxide Utilization and Storage Based on Unconventional Oil and Gas Development," Energies, MDPI, vol. 15(24), pages 1-29, December.
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