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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

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  • 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
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    References listed on IDEAS

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    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.
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