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Performance evaluation of enhanced geothermal system (EGS): Surrogate models, sensitivity study and ranking key parameters

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  • Asai, Pranay
  • Panja, Palash
  • McLennan, John
  • Moore, Joseph

Abstract

Designing an efficient system to extract heat from an enhanced geothermal system (EGS) requires proper understanding of the behavior of the reservoir over a long period. Five key parameters namely well spacing, fracture spacing, well inclination angle, injection temperature and injection rate are considered in this study for a doublet well system. To study and evaluate the performance of an EGS, second order surrogate models for ‘produced water temperature’, at certain time intervals are developed as a function of these five factors. The in-situ properties of a candidate reservoir for designing the simulations are taken from the FORGE site, Utah. Simulations are designed using ‘Box-Behnken’ design of experiments techniques to minimize the number of simulations. The models are trained and tested with the simulated results. Fitness of the models is calculated by estimating the errors using the coefficient of determination (R2) and the normalized root mean square error (NRMSE). These surrogate models are used to study the sensitivity of the aforementioned factors on the temperature of the produced water and the heat recovery over a time period of 30 years. Finally, the hierarchy of factors, as they impact the total heat recovery are represented as a tornado plot.

Suggested Citation

  • Asai, Pranay & Panja, Palash & McLennan, John & Moore, Joseph, 2018. "Performance evaluation of enhanced geothermal system (EGS): Surrogate models, sensitivity study and ranking key parameters," Renewable Energy, Elsevier, vol. 122(C), pages 184-195.
    • Handle: RePEc:eee:renene:v:122:y:2018:i:c:p:184-195
    DOI: 10.1016/j.renene.2018.01.098
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    Cited by:

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    3. Asai, Pranay & Panja, Palash & McLennan, John & Moore, Joseph, 2019. "Efficient workflow for simulation of multifractured enhanced geothermal systems (EGS)," Renewable Energy, Elsevier, vol. 131(C), pages 763-777.
    4. Pollack, Ahinoam & Mukerji, Tapan, 2019. "Accounting for subsurface uncertainty in enhanced geothermal systems to make more robust techno-economic decisions," Applied Energy, Elsevier, vol. 254(C).
    5. Asai, Pranay & Panja, Palash & McLennan, John & Deo, Milind, 2019. "Effect of different flow schemes on heat recovery from Enhanced Geothermal Systems (EGS)," Energy, Elsevier, vol. 175(C), pages 667-676.
    6. Ma, Yuanyuan & Li, Shibin & Zhang, Ligang & Liu, Songze & Liu, Zhaoyi & Li, Hao & Shi, Erxiu & Liu, Xuemei & Liu, Hongliang, 2020. "Analysis on the heat extraction performance of multi-well injection enhanced geothermal system based on leaf-like bifurcated fracture networks," Energy, Elsevier, vol. 213(C).
    7. Asai, Pranay & Podgorney, Robert & McLennan, John & Deo, Milind & Moore, Joseph, 2022. "Analytical model for fluid flow distribution in an Enhanced Geothermal Systems (EGS)," Renewable Energy, Elsevier, vol. 193(C), pages 821-831.
    8. 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.
    9. Gong, Facheng & Guo, Tiankui & Sun, Wei & Li, Zhaomin & Yang, Bin & Chen, Yimei & Qu, Zhanqing, 2020. "Evaluation of geothermal energy extraction in Enhanced Geothermal System (EGS) with multiple fracturing horizontal wells (MFHW)," Renewable Energy, Elsevier, vol. 151(C), pages 1339-1351.
    10. Zhou, Luming & Zhu, Zhende & Xie, Xinghua & Hu, Yunjin, 2022. "Coupled thermal–hydraulic–mechanical model for an enhanced geothermal system and numerical analysis of its heat mining performance," Renewable Energy, Elsevier, vol. 181(C), pages 1440-1458.
    11. Linkai Li & Xiao Guo & Ming Zhou & Gang Xiang & Ning Zhang & Yue Wang & Shengyuan Wang & Arnold Landjobo Pagou, 2021. "The Investigation of Fracture Networks on Heat Extraction Performance for an Enhanced Geothermal System," Energies, MDPI, vol. 14(6), pages 1-18, March.
    12. Qiao, Mingzheng & Jing, Zefeng & Feng, Chenchen & Li, Minghui & Chen, Cheng & Zou, Xupeng & Zhou, Yujuan, 2024. "Review on heat extraction systems of hot dry rock: Classifications, benefits, limitations, research status and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 196(C).
    13. Chen, Guodong & Jiao, Jiu Jimmy & Jiang, Chuanyin & Luo, Xin, 2024. "Surrogate-assisted level-based learning evolutionary search for geothermal heat extraction optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    14. Anna Wachowicz-Pyzik & Anna Sowiżdżał & Leszek Pająk & Paweł Ziółkowski & Janusz Badur, 2020. "Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)," Energies, MDPI, vol. 13(9), pages 1-20, May.
    15. Wang, Nanzhe & Chang, Haibin & Kong, Xiang-Zhao & Zhang, Dongxiao, 2023. "Deep learning based closed-loop well control optimization of geothermal reservoir with uncertain permeability," Renewable Energy, Elsevier, vol. 211(C), pages 379-394.
    16. Salimzadeh, S. & Grandahl, M. & Medetbekova, M. & Nick, H.M., 2019. "A novel radial jet drilling stimulation technique for enhancing heat recovery from fractured geothermal reservoirs," Renewable Energy, Elsevier, vol. 139(C), pages 395-409.
    17. Zhang, Yu & Zhang, Yanjun & Zhou, Ling & Lei, Zhihong & Guo, Liangliang & Zhou, Jian, 2022. "Reservoir stimulation design and evaluation of heat exploitation of a two-horizontal-well enhanced geothermal system (EGS) in the Zhacang geothermal field, Northwest China," Renewable Energy, Elsevier, vol. 183(C), pages 330-350.
    18. Zheng, Jun & Li, Peng & Dou, Bin & Fan, Tao & Tian, Hong & Lai, Xiaotian, 2022. "Impact research of well layout schemes and fracture parameters on heat production performance of enhanced geothermal system considering water cooling effect," Energy, Elsevier, vol. 255(C).
    19. Lin, David T.W. & Hsieh, Jui Ching & Shih, Bo Yen, 2019. "The optimization of geothermal extraction based on supercritical CO2 porous heat transfer model," Renewable Energy, Elsevier, vol. 143(C), pages 1162-1171.
    20. Zheng, Shuai & Li, Sanbai & Zhang, Dongxiao, 2021. "Fluid and heat flow in enhanced geothermal systems considering fracture geometrical and topological complexities: An extended embedded discrete fracture model," Renewable Energy, Elsevier, vol. 179(C), pages 163-178.
    21. Xu, Tianfu & Liang, Xu & Xia, Yi & Jiang, Zhenjiao & Gherardi, Fabrizio, 2022. "Performance evaluation of the Habanero enhanced geothermal system, Australia: Optimization based on tracer and induced micro-seismicity data," Renewable Energy, Elsevier, vol. 181(C), pages 1197-1208.
    22. Zhang, Jie & Xie, Jingxuan, 2020. "Effect of reservoir’s permeability and porosity on the performance of cellular development model for enhanced geothermal system," Renewable Energy, Elsevier, vol. 148(C), pages 824-838.
    23. 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).
    24. 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).
    25. Moussa, Tamer & Dehghanpour, Hassan, 2022. "Evaluating geothermal energy production from suspended oil and gas wells by using data mining," Renewable Energy, Elsevier, vol. 196(C), pages 1294-1307.

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