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Numerical Analysis on the Optimization of Hydraulic Fracture Networks

Author

Listed:
  • Zhaobin Zhang

    (Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China)

  • Xiao Li

    (Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China)

  • Weina Yuan

    (School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710064, China)

  • Jianming He

    (Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China)

  • Guanfang Li

    (Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China)

  • Yusong Wu

    (Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China)

Abstract

The clear understanding of hydraulic fracture network complexity and the optimization of fracture network configuration are important to the hydraulic fracturing treatment of shale gas reservoirs. For the prediction of hydraulic fracture network configuration, one of the problems is the accurate representation of natural fractures. In this work, a real natural fracture network is reconstructed from shale samples. Moreover, a virtual fracture system is proposed to simulate the large number of small fractures that are difficult to identify. A numerical model based on the displacement discontinuity method is developed to simulate the fluid-rock coupling system. A dimensionless stress difference that is normalized by rock strength is proposed to quantify the anisotropy of crustal stress. The hydraulic fracturing processes under different stress conditions are simulated. The most complex fracture configurations are obtained when the maximum principle stress direction is perpendicular to the principle natural fracture direction. In contrast, the worst results are obtained when these two directions are parallel to each other. Moreover, the side effects of the unfavorable geological conditions caused by crustal stress anisotropy can be partly suppressed by increasing the viscous effect of the fluid.

Suggested Citation

  • Zhaobin Zhang & Xiao Li & Weina Yuan & Jianming He & Guanfang Li & Yusong Wu, 2015. "Numerical Analysis on the Optimization of Hydraulic Fracture Networks," Energies, MDPI, vol. 8(10), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:12061-12079:d:57652
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    References listed on IDEAS

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    1. Zhaobin Zhang & Xiao Li & Jianming He & Yanfang Wu & Bo Zhang, 2015. "Numerical Analysis on the Stability of Hydraulic Fracture Propagation," Energies, MDPI, vol. 8(9), pages 1-18, September.
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    Cited by:

    1. Lianchong Li & Yingjie Xia & Bo Huang & Liaoyuan Zhang & Ming Li & Aishan Li, 2016. "The Behaviour of Fracture Growth in Sedimentary Rocks: A Numerical Study Based on Hydraulic Fracturing Processes," Energies, MDPI, vol. 9(3), pages 1-28, March.
    2. Hui Gao & Yule Hu & Longchen Duan & Kun Ai, 2019. "An Analytical Solution of the Pseudosteady State Productivity Index for the Fracture Geometry Optimization of Fractured Wells," Energies, MDPI, vol. 12(1), pages 1-22, January.
    3. Wan Cheng & Chunhua Lu & Bo Xiao, 2021. "Perforation Optimization of Intensive-Stage Fracturing in a Horizontal Well Using a Coupled 3D-DDM Fracture Model," Energies, MDPI, vol. 14(9), pages 1-18, April.
    4. Zhaobin Zhang & Xiao Li, 2016. "Numerical Study on the Formation of Shear Fracture Network," Energies, MDPI, vol. 9(4), pages 1-16, April.
    5. Kun Ai & Longchen Duan & Hui Gao & Guangliang Jia, 2018. "Hydraulic Fracturing Treatment Optimization for Low Permeability Reservoirs Based on Unified Fracture Design," Energies, MDPI, vol. 11(7), pages 1-23, July.
    6. Yiyu Lu & Yugang Cheng & Zhaolong Ge & Liang Cheng & Shaojie Zuo & Jianyu Zhong, 2016. "Determination of Fracture Initiation Locations during Cross-Measure Drilling for Hydraulic Fracturing of Coal Seams," Energies, MDPI, vol. 9(5), pages 1-13, May.

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