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Parametric study of the production performance of an enhanced geothermal system: A case study at the Qiabuqia geothermal area, northeast Tibetan plateau

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  • Zhang, Chao
  • Jiang, Guangzheng
  • Jia, Xiaofeng
  • Li, Shengtao
  • Zhang, Shengsheng
  • Hu, Di
  • Hu, Shengbiao
  • Wang, Yibo

Abstract

Enhanced Geothermal System (EGS) is an essential approach to entrap heat from deep hot dry rock (HDR), a low-carbon and renewable energy. Understanding the long-term productivity performance of the EGS and its sensitivity to different reservoir parameters can help to achieve efficiently the optimized exploitation of a designated reservoir. The Qiabuqia geothermal area, located in the northeastern margin of the Gonghe basin, Tibetan Plateau, is one of the areas that have the greatest HDR geothermal resources exploration and development potential in China so far. Based on the geological data of the GR1 borehole at the Qiabuqia geothermal area, northeast Tibetan plateau, a 3D thermo-hydraulic coupled numerical model is established in this study with the method of finite element to assess the heat production potential. The mathematical model presented in this study is validated by the analytical solution of a single fracture model. By varying several key reservoir parameters (e.g. thermal conductivity, permeability, porosity, injection mass flow rate, injection fluid temperature, and lateral well spacing), the sensitivity analysis of the long-term production temperature and electric power rate evolution is implemented. The simulation results indicate that in the basal granitic reservoir with a depth of 2900 m–3400 m and a corresponding initial temperature of 160 °C–180 °C, the temperature produced and effective electric power can maintain at 173.4 °C and 2.48 MW for the first 7 years of simulation under the combination of 50 kg/s of injection flow rate, 60 °C of the injection fluid temperature and a 300 m of lateral well spacing. At the end of the 40-year operation period, the outlet temperature decrease to 162.8 °C, as well as a drop of 9.7% in the electric power. Sensitivity analysis with the method of ‘One Factor At a time’ suggests that the permeability is the parameter that affects the production temperature and energy extraction the most compared with the thermal conductivity and porosity. For a specified geothermal field with a known distribution of permeability, thermal conductivity and porosity, the injection mass flow rate has the most significant effect on the electric power output, followed by the injection temperature and the lateral well spacing. The results from the complete factorial experimental design simulation suggest the electric power performance of the reservoir can be increased by a reasonable multi-parameter combination. For a doublet well extraction system, based on the Qiabuqia geothermal area, a combination of 70 kg/s injection flow rate, 60 °C injection temperature, and 500 m lateral well spacing can attain an effective electric power output of 3.47–3.50 MW. Thus, this study compares the different heat mining performance potential under various reservoir parameters and their combinations through the aforementioned sensitivity analysis and can greatly promote the establishment and development of EGS program in the Qiabuqia geothermal area in the future.

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  • 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.
    • Handle: RePEc:eee:renene:v:132:y:2019:i:c:p:959-978
    DOI: 10.1016/j.renene.2018.08.061
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    7. Aliyu, Musa D. & Finkbeiner, Thomas & Chen, Hua-Peng & Archer, Rosalind A., 2023. "A three-dimensional investigation of the thermoelastic effect in an enhanced geothermal system reservoir," Energy, Elsevier, vol. 262(PA).
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    11. Guilin Zhu & Linyou Zhang & Zhihui Deng & Qingda Feng & Zhaoxuan Niu & Wenhao Xu, 2023. "Three-Dimensional Geological Modeling and Resource Estimation of Hot Dry Rock in the Gonghe Basin, Qinghai Province," Energies, MDPI, vol. 16(16), pages 1-16, August.
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    17. Wang, Jiacheng & Zhao, Zhihong & Liu, Guihong & Xu, Haoran, 2022. "A robust optimization approach of well placement for doublet in heterogeneous geothermal reservoirs using random forest technique and genetic algorithm," Energy, Elsevier, vol. 254(PC).
    18. Hashemian, Nasim & Noorpoor, Alireza, 2022. "A geothermal-biomass powered multi-generation plant with freshwater and hydrogen generation options: Thermo-economic-environmental appraisals and multi-criteria optimization," Renewable Energy, Elsevier, vol. 198(C), pages 254-266.
    19. Xue, Zhenqian & Zhang, Kai & Zhang, Chi & Ma, Haoming & Chen, Zhangxin, 2023. "Comparative data-driven enhanced geothermal systems forecasting models: A case study of Qiabuqia field in China," Energy, Elsevier, vol. 280(C).
    20. Guo, Tiankui & Tang, Songjun & Sun, Jiang & Gong, Facheng & Liu, Xiaoqiang & Qu, Zhanqing & Zhang, Wei, 2020. "A coupled thermal-hydraulic-mechanical modeling and evaluation of geothermal extraction in the enhanced geothermal system based on analytic hierarchy process and fuzzy comprehensive evaluation," Applied Energy, Elsevier, vol. 258(C).

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