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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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    6. 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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