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Geothermal assessment of the Pisa plain, Italy: Coupled thermal and hydraulic modeling

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  • Feng, Guanhong
  • Xu, Tianfu
  • Gherardi, Fabrizio
  • Jiang, Zhenjiao
  • Bellani, Stefano

Abstract

This paper explores the possibility of a development project with a geothermal well doublet in the Pisa plain, Italy. The performance of the system has been evaluated with a 3-dimensional field-scale numerical model that simulates the evolution of temperature and pressure conditions in the aquifer, under different exploitation scenarios. Coupled groundwater flow and thermal transport processes in the reservoir are considered together with non-Darcy fluid flow in the wellbores, and heat exchange between boreholes and surrounding rock formations. Calculations are performed with a parallelized version of the wellbore-reservoir simulator T2Well. This code allows for the efficient modeling of coupled hydraulic-thermal processes over a domain about 40 km2 wide and 1.5 km thick. Simulation results indicate that the energy of the reservoir is sufficient for the designed extraction rate (between 80 and 150 m3/h), but also suitable for much larger rates, up to 250 m3/h. Although aimed at assessing the long-term performance of a specific system, this modeling approach could be profitably applied for the design of similar projects elsewhere.

Suggested Citation

  • Feng, Guanhong & Xu, Tianfu & Gherardi, Fabrizio & Jiang, Zhenjiao & Bellani, Stefano, 2017. "Geothermal assessment of the Pisa plain, Italy: Coupled thermal and hydraulic modeling," Renewable Energy, Elsevier, vol. 111(C), pages 416-427.
    • Handle: RePEc:eee:renene:v:111:y:2017:i:c:p:416-427
    DOI: 10.1016/j.renene.2017.04.034
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    Citations

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    Cited by:

    1. Bo Feng & Hao Ren & Yabin Yang & Zhenpeng Cui & Jichu Zhao, 2023. "Comparative Analysis of Heating Efficiency of a Single-Well Geothermal System in the Cold Region of Northeast China," Energies, MDPI, vol. 16(4), pages 1-16, February.
    2. Liu, Guihong & Zhao, Zhihong & Xu, Haoran & Zhang, Jinping & Kong, Xiangjun & Yuan, Lijuan, 2022. "A robust assessment method of recoverable geothermal energy considering optimal development parameters," Renewable Energy, Elsevier, vol. 201(P1), pages 426-440.
    3. Martina Gizzi & Federico Vagnon & Glenda Taddia & Stefano Lo Russo, 2023. "A Review of Groundwater Heat Pump Systems in the Italian Framework: Technological Potential and Environmental Limits," Energies, MDPI, vol. 16(12), pages 1-13, June.
    4. 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.
    5. Moore, Kayla R. & Holländer, Hartmut M., 2020. "Feasibility of low-temperature geothermal systems: Considerations of thermal anomalies, geochemistry, and local assets," Applied Energy, Elsevier, vol. 275(C).
    6. Alessandro Sbrana & Paola Marianelli & Giuseppe Pasquini & Paolo Costantini & Francesco Palmieri & Valentina Ciani & Michele Sbrana, 2018. "The Integration of 3D Modeling and Simulation to Determine the Energy Potential of Low-Temperature Geothermal Systems in the Pisa (Italy) Sedimentary Plain," Energies, MDPI, vol. 11(6), pages 1-20, June.
    7. Meleddu, Marta & Pulina, Manuela, 2018. "Public spending on renewable energy in Italian regions," Renewable Energy, Elsevier, vol. 115(C), pages 1086-1098.
    8. Liang, Xu & Xu, Tianfu & Feng, Bo & Jiang, Zhenjiao, 2018. "Optimization of heat extraction strategies in fault-controlled hydro-geothermal reservoirs," Energy, Elsevier, vol. 164(C), pages 853-870.
    9. 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).
    10. Feng, Guanhong & Xu, Tianfu & Zhao, Yue'an & Gherardi, Fabrizio, 2022. "Heat mining from super-hot horizons of the Larderello geothermal field, Italy," Renewable Energy, Elsevier, vol. 197(C), pages 371-383.
    11. 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.
    12. 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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