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Embedded discrete fracture network method for numerical estimation of long-term performance of CO2-EGS under THM coupled framework

Author

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  • Liao, Jianxing
  • Hu, Ke
  • Mehmood, Faisal
  • Xu, Bin
  • Teng, Yuhang
  • Wang, Hong
  • Hou, Zhengmeng
  • Xie, Yachen

Abstract

In enhanced geothermal system (EGS), the artificial fracture networks created by hydraulic fracturing provide highly conductive channel for heat extraction. Very complicated thermo-hydro-mechanical (THM) coupled processes will be involved during cold CO2 injection into the hot fractured reservoir. In this work, a new THM coupled approach is proposed for simulating the long-term performance of CO2-EGS based on embedded discrete fracture networks (DFNs). Due to significant temperature difference between the injection fluid and surrounding, the heat flow in fractures is governed by local thermal non-equilibrium theory. The THM coupling process is achieved by coupling the mechanical simulator FLAC3D and hydraulic-thermal simulator TOUGH2MP. The feasibility of proposed approach is verified and validated through comparing it with analytical solution and other method. The CO2 injection into a reservoir with stochastically generated DFNs is simulated for a period of 20 years, to study the flow behavior, fracture deformation, and thermal performance. The channeling flow is observed by streamlines of fluid and heat flow. The thermal stress due to temperature drop will enhance the fracture width, further decreasing the injection pressure, which shows the significance of incorporating the THM coupling effect in such high temperature reservoirs. This approach also enriches the tools for CO2-EGS simulation.

Suggested Citation

  • Liao, Jianxing & Hu, Ke & Mehmood, Faisal & Xu, Bin & Teng, Yuhang & Wang, Hong & Hou, Zhengmeng & Xie, Yachen, 2023. "Embedded discrete fracture network method for numerical estimation of long-term performance of CO2-EGS under THM coupled framework," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s036054422302128x
    DOI: 10.1016/j.energy.2023.128734
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    References listed on IDEAS

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    1. Feng, Runhai & Nasser, Saleh, 2024. "Stochastic inversion of fracture networks using the reversible jump Markov chain Monte Carlo algorithm," Energy, Elsevier, vol. 301(C).

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    Keywords

    Embedded DFN; CO2-EGS; THM coupling; Thermal performance;
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