IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i24p8357-d700273.html
   My bibliography  Save this article

Big Data Analysis and Research on Fracturing Construction Parameters of Shale Gas Horizontal Wells—A Case Study of Horizontal Wells in Fuling Demonstration Area, China

Author

Listed:
  • Minxuan Li

    (School of Petroleum Engineering, Yangtze University, Wuhan 430100, China)

  • Liang Cheng

    (School of Petroleum Engineering, Yangtze University, Wuhan 430100, China)

  • Dehua Liu

    (School of Petroleum Engineering, Yangtze University, Wuhan 430100, China)

  • Jiani Hu

    (School of Petroleum Engineering, Yangtze University, Wuhan 430100, China)

  • Wei Zhang

    (Sinopec Jianghan Oilfield Research Institute of Petroleum Engineering, Wuhan 430035, China)

  • Kuidong Li

    (Sinopec Jianghan Oilfield Research Institute of Petroleum Engineering, Wuhan 430035, China)

  • Jialin Xiao

    (Sinopec Jianghan Oilfield Research Institute of Petroleum Engineering, Wuhan 430035, China)

  • Xiaojun Wang

    (Sinopec Jianghan Oilfield Research Institute of Petroleum Engineering, Wuhan 430035, China)

  • Feng Zhang

    (Sinopec Jianghan Oilfield Research Institute of Petroleum Engineering, Wuhan 430035, China)

Abstract

With the rapid development of computer science and technology, the Chinese petroleum industry has ushered in the era of big data. In this study, by collecting fracturing data from 303 horizontal wells in the Fuling Shale Gas Demonstration Area in China, a series of big data analysis studies was conducted using Pearson’s correlation coefficient, the unweighted pair group with arithmetic means method, and the graphical plate method to determine which is best. The fracturing parameters were determined through a series of big data analysis studies. The big data analysis process is divided into three main steps. The first is data preprocessing to screen out eligible, high-yielding wells. The second is a fracturing parameter correlation clustering analysis to determine the reasonableness of the parameters. The third is a big data panel method analysis of specific fracturing construction parameters to determine the optimal parameter range. The analyses revealed that the current amount of 100 mesh sand in the Fuling area is unreasonable; further, there are different preferred areas for different fracturing construction parameters. We have combined different fracturing parameter schemes by preferring areas. This analysis process is expected to provide new ideas regarding fracturing scheme design for engineers working on the frontline.

Suggested Citation

  • Minxuan Li & Liang Cheng & Dehua Liu & Jiani Hu & Wei Zhang & Kuidong Li & Jialin Xiao & Xiaojun Wang & Feng Zhang, 2021. "Big Data Analysis and Research on Fracturing Construction Parameters of Shale Gas Horizontal Wells—A Case Study of Horizontal Wells in Fuling Demonstration Area, China," Energies, MDPI, vol. 14(24), pages 1-17, December.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8357-:d:700273
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/24/8357/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/24/8357/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chao Tang & Xiaofan Chen & Zhimin Du & Ping Yue & Jiabao Wei, 2018. "Numerical Simulation Study on Seepage Theory of a Multi-Section Fractured Horizontal Well in Shale Gas Reservoirs Based on Multi-Scale Flow Mechanisms," Energies, MDPI, vol. 11(9), pages 1-20, September.
    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. Long Ren & Wendong Wang & Yuliang Su & Mingqiang Chen & Cheng Jing & Nan Zhang & Yanlong He & Jian Sun, 2018. "Multiporosity and Multiscale Flow Characteristics of a Stimulated Reservoir Volume (SRV)-Fractured Horizontal Well in a Tight Oil Reservoir," Energies, MDPI, vol. 11(10), pages 1-14, October.
    2. Kyoungsu Kim & Jonggeun Choe, 2019. "Hydraulic Fracture Design with a Proxy Model for Unconventional Shale Gas Reservoir with Considering Feasibility Study," Energies, MDPI, vol. 12(2), pages 1-12, January.
    3. Tang, Chao & Zhou, Wen & Chen, Zhangxin & Wei, Jiabao, 2023. "Numerical simulation of CO2 sequestration in shale gas reservoirs at reservoir scale coupled with enhanced gas recovery," Energy, Elsevier, vol. 277(C).
    4. Honghua Tao & Liehui Zhang & Qiguo Liu & Qi Deng & Man Luo & Yulong Zhao, 2018. "An Analytical Flow Model for Heterogeneous Multi-Fractured Systems in Shale Gas Reservoirs," Energies, MDPI, vol. 11(12), pages 1-19, December.
    5. Jianchao Cai & Zhien Zhang & Qinjun Kang & Harpreet Singh, 2019. "Recent Advances in Flow and Transport Properties of Unconventional Reservoirs," Energies, MDPI, vol. 12(10), pages 1-5, May.

    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:14:y:2021:i:24:p:8357-:d:700273. 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.