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Comparative study on heat extraction from Soultz-sous-Forêts geothermal field using supercritical carbon dioxide and water as the working fluid

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  • Singh, Mrityunjay
  • Mahmoodpour, Saeed
  • Ershadnia, Reza
  • Soltanian, Mohamad Reza
  • Sass, Ingo

Abstract

Energy extraction from the deep subsurface requires engineering using a working fluid circulation in well doublet. This study developed a field-scale hydro-thermal model to examine the heat extraction potential from Soultz-sous-Forêts with CO2 and water as the working fluid. A better understanding of the heat extraction mechanism is established by considering the reservoir response and the wellbore heat exchange. Sensitivity analyses are performed for different injection temperatures and flow rates for 50 years. Results show that the wellbore effect is multiple times higher than the reservoir response to the production temperature. Furthermore, lowering the injection temperature eventuates to a smaller temperature reduction at the subsurface, enhancing the overall heat extraction potential with a minor impact on thermal breakthrough. The cold region developed around the injection wellbore may affect the production fluid temperature due to its proximity to the production wellbore near the top of the reservoir. To reach higher heat extraction efficiency, it is essential to use sufficient wellbore spacing. CO2 can be used as working fluid for over 50 years as it does not show significant thermal breakthrough and temperature plume evolution in the reservoir under studied conditions. CO2 shows lower temperature reduction for all injection rates and temperatures for 50 years of operation.

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  • Singh, Mrityunjay & Mahmoodpour, Saeed & Ershadnia, Reza & Soltanian, Mohamad Reza & Sass, Ingo, 2023. "Comparative study on heat extraction from Soultz-sous-Forêts geothermal field using supercritical carbon dioxide and water as the working fluid," Energy, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:energy:v:266:y:2023:i:c:s0360544222032741
    DOI: 10.1016/j.energy.2022.126388
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    References listed on IDEAS

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    1. Justin Ezekiel & Diya Kumbhat & Anozie Ebigbo & Benjamin M. Adams & Martin O. Saar, 2021. "Sensitivity of Reservoir and Operational Parameters on the Energy Extraction Performance of Combined CO 2 -EGR–CPG Systems," Energies, MDPI, vol. 14(19), pages 1-21, September.
    2. 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).
    3. Adams, Benjamin M. & Kuehn, Thomas H. & Bielicki, Jeffrey M. & Randolph, Jimmy B. & Saar, Martin O., 2014. "On the importance of the thermosiphon effect in CPG (CO2 plume geothermal) power systems," Energy, Elsevier, vol. 69(C), pages 409-418.
    4. Luo, Feng & Xu, Rui-Na & Jiang, Pei-Xue, 2014. "Numerical investigation of fluid flow and heat transfer in a doublet enhanced geothermal system with CO2 as the working fluid (CO2–EGS)," Energy, Elsevier, vol. 64(C), pages 307-322.
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    3. Wentao Zhao & Yilong Yuan & Tieya Jing & Chenghao Zhong & Shoucheng Wei & Yulong Yin & Deyuan Zhao & Haowei Yuan & Jin Zheng & Shaomin Wang, 2023. "Heat Production Performance from an Enhanced Geothermal System (EGS) Using CO 2 as the Working Fluid," Energies, MDPI, vol. 16(20), pages 1-16, October.
    4. Kexun Wang & Tishi Huang & Wenke Zhang & Zhiqiang Zhang & Xueqing Ma & Leyao Zhang, 2023. "An Analysis of the Heat Transfer Characteristics of Medium-Shallow Borehole Ground Heat Exchangers with Various Working Fluids," Sustainability, MDPI, vol. 15(16), pages 1-21, August.
    5. Zeming Ji & Chang He & Yingying Sun & Xiaokun Yue & Hongxu Fang & Xiaoqing Lu & Siyuan Liu & Weifeng Lyu, 2023. "Molecular Dynamics Simulation of CO 2 Storage in Reservoir Pores with a Dead-End," Energies, MDPI, vol. 16(21), pages 1-18, October.
    6. Tomasz Topór & Małgorzata Słota-Valim & Rafał Kudrewicz, 2023. "Assessing the Geothermal Potential of Selected Depleted Oil and Gas Reservoirs Based on Geological Modeling and Machine Learning Tools," Energies, MDPI, vol. 16(13), pages 1-19, July.

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