IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i17p6162-d897032.html
   My bibliography  Save this article

UNet–Based Temperature Simulation of Hot Dry Rock in the Gonghe Basin

Author

Listed:
  • Wanli Gao

    (State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
    College of Geoscience and Survey Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Jingtao Zhao

    (State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
    College of Geoscience and Survey Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Suping Peng

    (State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
    College of Geoscience and Survey Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China)

Abstract

Hot dry rock (HDR) geothermal energy, as a clean and renewable energy, has potential value in meeting the rapid demand of the social economy. Predicting the temperature distribution of a subsurface target zone is a fundamental issue for the exploration and evaluation of hot dry rock. Numerical finite–element simulation is currently the mainstream method used to study the variation in underground temperature fields. However, it has difficulty in dealing with multiple geological elements of deep and complex hot dry rock models. A Unity networking for hot dry rock temperature (HDRT–UNet) is proposed in this study that incorporates the matrix rock temperature field equation for relating the three parameters of density, specific heat capacity and thermal conductivity. According to the numerical geological structures and rock parameters of cap rocks, faults and magma intrusions, a new dataset simulated by the finite element method was created for training the HDRT–UNet. The temperature simulation results in the Gonghe basin show that the predicted temperatures within faults and granites were higher than their surrounding rocks, while a lower thermal conductivity of the cap rocks caused the temperature of overlying strata to be smaller than their surrounding temperature field. The simulation results also prove that our proposed HDRT–UNet can provide a certain evolutionary knowledge for the prediction and development of geothermal reserves.

Suggested Citation

  • Wanli Gao & Jingtao Zhao & Suping Peng, 2022. "UNet–Based Temperature Simulation of Hot Dry Rock in the Gonghe Basin," Energies, MDPI, vol. 15(17), pages 1-17, August.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6162-:d:897032
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/17/6162/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/17/6162/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Younas, Umair & Khan, B. & Ali, S.M. & Arshad, C.M. & Farid, U. & Zeb, Kamran & Rehman, Fahad & Mehmood, Yasir & Vaccaro, A., 2016. "Pakistan geothermal renewable energy potential for electric power generation: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 398-413.
    2. Mahmoodpour, Saeed & Singh, Mrityunjay & Bär, Kristian & Sass, Ingo, 2022. "Thermo-hydro-mechanical modeling of an enhanced geothermal system in a fractured reservoir using carbon dioxide as heat transmission fluid- A sensitivity investigation," Energy, Elsevier, vol. 254(PB).
    3. Li, Min & Lai, Alvin C.K., 2015. "Review of analytical models for heat transfer by vertical ground heat exchangers (GHEs): A perspective of time and space scales," Applied Energy, Elsevier, vol. 151(C), pages 178-191.
    4. Feng, Zijun & Zhao, Yangsheng & Zhou, Anchao & Zhang, Ning, 2012. "Development program of hot dry rock geothermal resource in the Yangbajing Basin of China," Renewable Energy, Elsevier, vol. 39(1), pages 490-495.
    5. Gang, Wenjie & Wang, Jinbo & Wang, Shengwei, 2014. "Performance analysis of hybrid ground source heat pump systems based on ANN predictive control," Applied Energy, Elsevier, vol. 136(C), pages 1138-1144.
    6. Zeng, Yu-Chao & Wu, Neng-You & Su, Zheng & Wang, Xiao-Xing & Hu, Jian, 2013. "Numerical simulation of heat production potential from hot dry rock by water circulating through a novel single vertical fracture at Desert Peak geothermal field," Energy, Elsevier, vol. 63(C), pages 268-282.
    7. Song, Xianzhi & Shi, Yu & Li, Gensheng & Yang, Ruiyue & Wang, Gaosheng & Zheng, Rui & Li, Jiacheng & Lyu, Zehao, 2018. "Numerical simulation of heat extraction performance in enhanced geothermal system with multilateral wells," Applied Energy, Elsevier, vol. 218(C), pages 325-337.
    8. Mahmoodpour, Saeed & Singh, Mrityunjay & Turan, Aysegul & Bär, Kristian & Sass, Ingo, 2022. "Simulations and global sensitivity analysis of the thermo-hydraulic-mechanical processes in a fractured geothermal reservoir," Energy, Elsevier, vol. 247(C).
    9. Yang, Weifei & Xiao, Changlai & Zhang, Zhihao & Liang, Xiujuan, 2022. "Identification of the formation temperature field of the southern Songliao Basin, China based on a deep belief network," Renewable Energy, Elsevier, vol. 182(C), pages 32-42.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei, Xin & Feng, Zi-jun & Zhao, Yang-sheng, 2019. "Numerical simulation of thermo-hydro-mechanical coupling effect in mining fault-mode hot dry rock geothermal energy," Renewable Energy, Elsevier, vol. 139(C), pages 120-135.
    2. Xiang Gao & Tailu Li & Yao Zhang & Xiangfei Kong & Nan Meng, 2022. "A Review of Simulation Models of Heat Extraction for a Geothermal Reservoir in an Enhanced Geothermal System," Energies, MDPI, vol. 15(19), pages 1-23, September.
    3. Zhai, Haizhen & Jin, Guangrong & Liu, Lihua & Su, Zheng & Zeng, Yuchao & Liu, Jie & Li, Guangyu & Feng, Chuangji & Wu, Nengyou, 2023. "Parametric study of the geothermal exploitation performance from a HDR reservoir through multilateral horizontal wells: The Qiabuqia geothermal area, Gonghe Basin," Energy, Elsevier, vol. 275(C).
    4. Yu Wang & Tianfu Xu & Yuxiang Cheng & Guanhong Feng, 2022. "Prospects for Power Generation of the Doublet Supercritical Geothermal System in Reykjanes Geothermal Field, Iceland," Energies, MDPI, vol. 15(22), pages 1-15, November.
    5. Zeng, Yuchao & Tang, Liansheng & Wu, Nengyou & Cao, Yifei, 2017. "Analysis of influencing factors of production performance of enhanced geothermal system: A case study at Yangbajing geothermal field," Energy, Elsevier, vol. 127(C), pages 218-235.
    6. Saeed Mahmoodpour & Mrityunjay Singh & Ramin Mahyapour & Sri Kalyan Tangirala & Kristian Bär & Ingo Sass, 2022. "Numerical Simulation of Thermo-Hydro-Mechanical Processes at Soultz-sous-Forêts," Energies, MDPI, vol. 15(24), pages 1-21, December.
    7. Cao, Meng & Sharma, Mukul M., 2023. "Effect of fracture geometry, topology and connectivity on energy recovery from enhanced geothermal systems," Energy, Elsevier, vol. 282(C).
    8. Ding, Junfeng & Wang, Shimin, 2018. "2D modeling of well array operating enhanced geothermal system," Energy, Elsevier, vol. 162(C), pages 918-932.
    9. 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.
    10. Ikeda, Shintaro & Choi, Wonjun & Ooka, Ryozo, 2017. "Optimization method for multiple heat source operation including ground source heat pump considering dynamic variation in ground temperature," Applied Energy, Elsevier, vol. 193(C), pages 466-478.
    11. Ma, Yuanyuan & Li, Shibin & Zhang, Ligang & Liu, Songze & Liu, Zhaoyi & Li, Hao & Shi, Erxiu & Zhang, Haijun, 2020. "Numerical simulation study on the heat extraction performance of multi-well injection enhanced geothermal system," Renewable Energy, Elsevier, vol. 151(C), pages 782-795.
    12. Yin, Weitao & Zhao, Yangsheng & Feng, Zijun, 2020. "Experimental research on the permeability of fractured-subsequently-filled granite under high temperature-high pressure and the application to HDR geothermal mining," Renewable Energy, Elsevier, vol. 153(C), pages 499-508.
    13. Yu, Likui & Wu, Xiaotian & Hassan, N.M.S. & Wang, Yadan & Ma, Weiwu & Liu, Gang, 2020. "Modified zipper fracturing in enhanced geothermal system reservoir and heat extraction optimization via orthogonal design," Renewable Energy, Elsevier, vol. 161(C), pages 373-385.
    14. Zhao, Yangsheng & Feng, Zijun & Feng, Zengchao & Yang, Dong & Liang, Weiguo, 2015. "THM (Thermo-hydro-mechanical) coupled mathematical model of fractured media and numerical simulation of a 3D enhanced geothermal system at 573 K and buried depth 6000–7000 M," Energy, Elsevier, vol. 82(C), pages 193-205.
    15. 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).
    16. Li, Xinxin & Li, Chengyu & Gong, Wenping & Zhang, Yanjie & Wang, Junchao, 2023. "Probabilistic analysis of heat extraction performance in enhanced geothermal system based on a DFN-based modeling scheme," Energy, Elsevier, vol. 263(PC).
    17. Lei, Zhihong & Zhang, Yanjun & Yu, Ziwang & Hu, Zhongjun & Li, Liangzhen & Zhang, Senqi & Fu, Lei & Zhou, Ling & Xie, Yangyang, 2019. "Exploratory research into the enhanced geothermal system power generation project: The Qiabuqia geothermal field, Northwest China," Renewable Energy, Elsevier, vol. 139(C), pages 52-70.
    18. Hongying Tan & Hejuan Liu & Xilin Shi & Hongling Ma & Xiaosong Qiu & Yintong Guo & Shengnan Ban, 2023. "Mechanical and Acoustic Response of Low-Permeability Sandstone under Multilevel Cyclic Loading-Unloading Stress Paths," Energies, MDPI, vol. 16(19), pages 1-18, September.
    19. Xu, Tianfu & Yuan, Yilong & Jia, Xiaofeng & Lei, Yude & Li, Shengtao & Feng, Bo & Hou, Zhaoyun & Jiang, Zhenjiao, 2018. "Prospects of power generation from an enhanced geothermal system by water circulation through two horizontal wells: A case study in the Gonghe Basin, Qinghai Province, China," Energy, Elsevier, vol. 148(C), pages 196-207.
    20. Yin, Weitao & Zhao, Yangsheng & Feng, Zijun, 2019. "Experimental research on the rupture characteristics of fractures subsequently filled by magma and hydrothermal fluid in hot dry rock," Renewable Energy, Elsevier, vol. 139(C), pages 71-79.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6162-:d:897032. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.