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A new well pattern of cluster-layout for deep geothermal reservoirs: Case study from the Dezhou geothermal field, China

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  • Liu, Guihong
  • Wang, Guiling
  • Zhao, Zhihong
  • Ma, Feng

Abstract

A well pattern of cluster-layout is proposed to reduce the risk of thermal breakthrough at production wells, as well as to improve the convenience of surface management. Its performance in the heterogeneous porous geothermal reservoir models based on the Dezhou geothermal field, China is systematically examined using the coupled thermal-hydraulic numerical modeling. In order to compare the performance of different well patterns, three assessment parameters including thermal breakthrough time and water table of production wells and recovery efficiency of geothermal energy in the licensed region are defined. The results showed that the well pattern of cluster-layout has the higher recovery efficiency of geothermal energy compared with other well patterns of tramrail-layout and checkers-board-layout for most simulations. Effects of anisotropy and correlation length of reservoir permeability on the performance of different well patterns are examined. Flow channeling appears along the direction of high permeability, and thus the injection-production direction should avoid to be parallel with that direction. With increasing correlation length, the possibility of flow channels appearing in the licensed region increases and the fate of production wells declines. When the difference of correlation lengths between different directions increases, the induced anisotropy of reservoir permeability increases but the recovery efficiency decreases.

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  • Liu, Guihong & Wang, Guiling & Zhao, Zhihong & Ma, Feng, 2020. "A new well pattern of cluster-layout for deep geothermal reservoirs: Case study from the Dezhou geothermal field, China," Renewable Energy, Elsevier, vol. 155(C), pages 484-499.
    • Handle: RePEc:eee:renene:v:155:y:2020:i:c:p:484-499
    DOI: 10.1016/j.renene.2020.03.156
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    1. Quinao, Jaime Jose D. & Zarrouk, Sadiq J., 2018. "Geothermal resource assessment using Experimental Design and Response Surface Methods: The Ngatamariki geothermal field, New Zealand," Renewable Energy, Elsevier, vol. 116(PA), pages 324-334.
    2. Wang, Guiling & Liu, Guihong & Zhao, Zhihong & Liu, Yanguang & Pu, Hai, 2019. "A robust numerical method for modeling multiple wells in city-scale geothermal field based on simplified one-dimensional well model," Renewable Energy, Elsevier, vol. 139(C), pages 873-894.
    3. Willems, C.J.L. & M. Nick, H., 2019. "Towards optimisation of geothermal heat recovery: An example from the West Netherlands Basin," Applied Energy, Elsevier, vol. 247(C), pages 582-593.
    4. Aliyu, Musa D. & Chen, Hua-Peng, 2017. "Sensitivity analysis of deep geothermal reservoir: Effect of reservoir parameters on production temperature," Energy, Elsevier, vol. 129(C), pages 101-113.
    5. Zhang, Wei & Qu, Zhanqing & Guo, Tiankui & Wang, Zhiyuan, 2019. "Study of the enhanced geothermal system (EGS) heat mining from variably fractured hot dry rock under thermal stress," Renewable Energy, Elsevier, vol. 143(C), pages 855-871.
    6. Zhang, Chao & Jiang, Guangzheng & Jia, Xiaofeng & Li, Shengtao & Zhang, Shengsheng & Hu, Di & Hu, Shengbiao & Wang, Yibo, 2019. "Parametric study of the production performance of an enhanced geothermal system: A case study at the Qiabuqia geothermal area, northeast Tibetan plateau," Renewable Energy, Elsevier, vol. 132(C), pages 959-978.
    7. Willems, Cees J.L. & Nick, Hamidreza M. & Weltje, Gert Jan & Bruhn, David F., 2017. "An evaluation of interferences in heat production from low enthalpy geothermal doublets systems," Energy, Elsevier, vol. 135(C), pages 500-512.
    8. Liu, Jian & Cheng, Wen-Long & Nian, Yong-Le, 2018. "The stratigraphic and operating parameters influence on economic analysis for enhanced geothermal double wells utilization system," Energy, Elsevier, vol. 159(C), pages 264-276.
    9. Chen, Mingjie & Tompson, Andrew F.B. & Mellors, Robert J. & Abdalla, Osman, 2015. "An efficient optimization of well placement and control for a geothermal prospect under geological uncertainty," Applied Energy, Elsevier, vol. 137(C), pages 352-363.
    10. Liu, Guihong & Pu, Hai & Zhao, Zhihong & Liu, Yanguang, 2019. "Coupled thermo-hydro-mechanical modeling on well pairs in heterogeneous porous geothermal reservoirs," Energy, Elsevier, vol. 171(C), pages 631-653.
    11. Chen, Jiliang & Jiang, Fangming, 2015. "Designing multi-well layout for enhanced geothermal system to better exploit hot dry rock geothermal energy," Renewable Energy, Elsevier, vol. 74(C), pages 37-48.
    12. Babaei, Masoud & Nick, Hamidreza M., 2019. "Performance of low-enthalpy geothermal systems: Interplay of spatially correlated heterogeneity and well-doublet spacings," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    13. Saeid, Sanaz & Al-Khoury, Rafid & Nick, Hamidreza M. & Hicks, Michael A., 2015. "A prototype design model for deep low-enthalpy hydrothermal systems," Renewable Energy, Elsevier, vol. 77(C), pages 408-422.
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    Cited by:

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    5. Xu, Fuqiang & Shi, Yu & Song, Xianzhi & Wu, Wei & Song, Guofeng & Li, Shuang, 2024. "Experimental characterization of damage during geothermal production of hot dry rocks: Comprehensive effects of the damage-elastic deformation on conductivity evolution," Energy, Elsevier, vol. 294(C).
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    7. Li, Shengtao & Wen, Dongguang & Feng, Bo & Li, Fengyu & Yue, Dongdong & Zhang, Qiuxia & Wang, Junzhao & Feng, Zhaolong, 2023. "Numerical optimization of geothermal energy extraction from deep karst reservoir in North China," Renewable Energy, Elsevier, vol. 202(C), pages 1071-1085.

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