IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p3413-d810228.html
   My bibliography  Save this article

Optimal Well Control Based on Auto-Adaptive Decision Tree—Maximizing Energy Efficiency in High-Nitrogen Underground Gas Storage

Author

Listed:
  • Edyta Kuk

    (Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland
    Edyta Kuk is currently working with Hitachi Energy, Pawia 7, 31-154 Krakow, Poland.)

  • Jerzy Stopa

    (Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland)

  • Michał Kuk

    (Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland)

  • Damian Janiga

    (Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland)

  • Paweł Wojnarowski

    (Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland)

Abstract

To move the world toward a more sustainable energy future, it is crucial to use the limited hydrocarbon geological resources efficiently and to develop technologies that facilitate this. More rational management of petroleum reservoirs and underground gas storage can be obtained by optimizing well control. This paper presents a novel approach to optimal well control based on the combination of optimal control theory, innovative artificial intelligence methods, and numerical reservoir simulations. In the developed algorithm, well control is based on an auto-adaptive parameterized decision tree. Its parameters are optimized by state-of-the-art machine learning, which uses previous results to determine favorable parameters. During optimization, a numerical reservoir simulator is applied to compute the objective function. The developed solution enables full automation of the wells for optimal control. An exemplary application of the developed solution to optimize underground storage of gas with high nitrogen content confirmed its effectiveness. The total nitrogen content in the gas decreased by 2.4%, increasing energy efficiency without increasing expense, as only well control was modified.

Suggested Citation

  • Edyta Kuk & Jerzy Stopa & Michał Kuk & Damian Janiga & Paweł Wojnarowski, 2022. "Optimal Well Control Based on Auto-Adaptive Decision Tree—Maximizing Energy Efficiency in High-Nitrogen Underground Gas Storage," Energies, MDPI, vol. 15(9), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3413-:d:810228
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/3413/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/9/3413/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Edyta Kuk & Jerzy Stopa & Michał Kuk & Damian Janiga & Paweł Wojnarowski, 2021. "Petroleum Reservoir Control Optimization with the Use of the Auto-Adaptive Decision Trees," Energies, MDPI, vol. 14(18), pages 1-20, September.
    2. Yin, Zhenyuan & Zhang, Shuyu & Koh, Shanice & Linga, Praveen, 2020. "Estimation of the thermal conductivity of a heterogeneous CH4-hydrate bearing sample based on particle swarm optimization," Applied Energy, Elsevier, vol. 271(C).
    3. Michał Kuk & Edyta Kuk & Damian Janiga & Paweł Wojnarowski & Jerzy Stopa, 2020. "Optimization Wells Placement Policy for Enhanced CO 2 Storage Capacity in Mature Oil Reservoirs," Energies, MDPI, vol. 13(16), pages 1-20, August.
    4. Yin, Zhenyuan & Huang, Li & Linga, Praveen, 2019. "Effect of wellbore design on the production behaviour of methane hydrate-bearing sediments induced by depressurization," Applied Energy, Elsevier, vol. 254(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei, Rupeng & Xia, Yongqiang & Wang, Zifei & Li, Qingping & Lv, Xin & Leng, Shudong & Zhang, Lunxiang & Zhang, Yi & Xiao, Bo & Yang, Shengxiong & Yang, Lei & Zhao, Jiafei & Song, Yongchen, 2022. "Long-term numerical simulation of a joint production of gas hydrate and underlying shallow gas through dual horizontal wells in the South China Sea," Applied Energy, Elsevier, vol. 320(C).
    2. Zhang, Jidong & Yin, Zhenyuan & Li, Qingping & Li, Shuaijun & Wang, Yi & Li, Xiao-Sen, 2023. "Comparison of fluid production between excess-gas and excess-water hydrate-bearing sediments under depressurization and its implication on energy recovery," Energy, Elsevier, vol. 282(C).
    3. Kuk, Edyta & Kuk, Michał & Janiga, Damian & Wojnarowski, Paweł & Stopa, Jerzy, 2021. "Smart Optimization of Proactive Control of Petroleum Reservoir," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2021), Hybrid Conference, Zagreb, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Hybrid Conference, Zagreb, Croatia, 9-10 September 2021, pages 297-306, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    4. Wan, Qing-Cui & Yin, Zhenyuan & Gao, Qiang & Si, Hu & Li, Bo & Linga, Praveen, 2022. "Fluid production behavior from water-saturated hydrate-bearing sediments below the quadruple point of CH4 + H2O," Applied Energy, Elsevier, vol. 305(C).
    5. Huang, Li & Yin, Zhenyuan & Wan, Yizhao & Sun, Jianye & Wu, Nengyou & Veluswamy, Hari Prakash, 2020. "Evaluation and comparison of gas production potential of the typical four gas hydrate deposits in Shenhu area, South China sea," Energy, Elsevier, vol. 204(C).
    6. Liu, Zheng & Zheng, Junjie & Wang, Zhiyuan & Gao, Yonghai & Sun, Baojiang & Liao, Youqiang & Linga, Praveen, 2023. "Effect of clay on methane hydrate formation and dissociation in sediment: Implications for energy recovery from clayey-sandy hydrate reservoirs," Applied Energy, Elsevier, vol. 341(C).
    7. Zhang, Tianjun & Wu, Jinyu & Pang, Mingkun & Liu, Rongtao & Zhu, Shipeng & Pan, Hongyu, 2024. "Experimental study on the negative pressure loss generated by the gas influx process around a long borehole," Energy, Elsevier, vol. 296(C).
    8. Li, Nan & Zhang, Jie & Xia, Ming-Ji & Sun, Chang-Yu & Liu, Yan-Sheng & Chen, Guang-Jin, 2021. "Gas production from heterogeneous hydrate-bearing sediments by depressurization in a large-scale simulator," Energy, Elsevier, vol. 234(C).
    9. Zhang, Xuemin & Zhang, Shanling & Yuan, Qing & Liu, Qingqing & Huang, Tingting & Li, Jinping & Wu, Qingbai & Zhang, Peng, 2024. "Gas production from hydrates by CH4-CO2 replacement: Effect of N2 and intermittent heating," Energy, Elsevier, vol. 288(C).
    10. Ouyang, Qian & Zheng, Junjie & Pandey, Jyoti Shanker & von Solms, Nicolas & Linga, Praveen, 2024. "Coupling amino acid injection and slow depressurization with hydrate swapping exploitation: An effective strategy to enhance in-situ CO2 storage in hydrate-bearing sediment," Applied Energy, Elsevier, vol. 366(C).
    11. Yin, Zhenyuan & Zhang, Shuyu & Koh, Shanice & Linga, Praveen, 2020. "Estimation of the thermal conductivity of a heterogeneous CH4-hydrate bearing sample based on particle swarm optimization," Applied Energy, Elsevier, vol. 271(C).
    12. Liao, Youqiang & Zheng, Junjie & Wang, Zhiyuan & Sun, Baojiang & Sun, Xiaohui & Linga, Praveen, 2022. "Modeling and characterizing the thermal and kinetic behavior of methane hydrate dissociation in sandy porous media," Applied Energy, Elsevier, vol. 312(C).
    13. Cao, Xinxin & Sun, Jiaxin & Qin, Fanfan & Ning, Fulong & Mao, Peixiao & Gu, Yuhang & Li, Yanlong & Zhang, Heen & Yu, Yanjiang & Wu, Nengyou, 2023. "Numerical analysis on gas production performance by using a multilateral well system at the first offshore hydrate production test site in the Shenhu area," Energy, Elsevier, vol. 270(C).
    14. Zheng Li & Christine C. Holzammer & Andreas S. Braeuer, 2020. "Analysis of the Dissolution of CH 4 /CO 2 -Mixtures into Liquid Water and the Subsequent Hydrate Formation via In Situ Raman Spectroscopy," Energies, MDPI, vol. 13(4), pages 1-17, February.
    15. Jin, Guangrong & Su, Zheng & Zhai, Haizhen & Feng, Chuangji & Liu, Jie & Peng, Yingyu & Liu, Lihua, 2023. "Enhancement of gas production from hydrate reservoir using a novel deployment of multilateral horizontal well," Energy, Elsevier, vol. 270(C).
    16. Chen, Bingbing & Sun, Huiru & Zheng, Junjie & Yang, Mingjun, 2020. "New insights on water-gas flow and hydrate decomposition behaviors in natural gas hydrates deposits with various saturations," Applied Energy, Elsevier, vol. 259(C).
    17. Ning, Fulong & Chen, Qiang & Sun, Jiaxin & Wu, Xiang & Cui, Guodong & Mao, Peixiao & Li, Yanlong & Liu, Tianle & Jiang, Guosheng & Wu, Nengyou, 2022. "Enhanced gas production of silty clay hydrate reservoirs using multilateral wells and reservoir reformation techniques: Numerical simulations," Energy, Elsevier, vol. 254(PA).
    18. Federico Rossi & Yan Li & Alberto Maria Gambelli, 2021. "Thermodynamic and Kinetic Description of the Main Effects Related to the Memory Effect during Carbon Dioxide Hydrates Formation in a Confined Environment," Sustainability, MDPI, vol. 13(24), pages 1-21, December.
    19. He, Juan & Li, Xiaosen & Chen, Zhaoyang & Huang, Xiaoliang & Shen, Pengfei, 2023. "Effect of heterogeneous hydrate distribution on hydrate production under different hole combinations," Energy, Elsevier, vol. 283(C).
    20. Yan Li & Alberto Maria Gambelli & Federico Rossi, 2022. "Experimental Study on the Effect of SDS and Micron Copper Particles Mixture on Carbon Dioxide Hydrates Formation," Energies, MDPI, vol. 15(18), pages 1-16, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3413-:d:810228. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.