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Towards optimisation of geothermal heat recovery: An example from the West Netherlands Basin

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  • Willems, C.J.L.
  • M. Nick, H.

Abstract

The Netherlands experienced the fastest European expansion of geothermal energy exploitation in the past decade. The first Dutch geothermal sites proved that Hot Sedimentary Aquifers exploitation can play an important role in a future low-carbon energy mix. In this study, we estimate that with the expansion rate of the past four years, geothermal heat production from Lower Cretaceous Hot Sedimentary Aquifers could cover up to 20% of the heat demand in the province of Zuid-Holland by 2050. Although this is a significant amount, we show in this study that only 1% of the potentially recoverable heat will be recovered by 2050. This is because of inefficient doublet deployment on a ‘first-come, first served’ basis with operational parameters that focus on objectives of small decentralised heat grid demands. Instead, similar to the common-practise approach in the hydrocarbon industry, a regional coordinated ‘masterplan’ approach could be used to increase heat recovery. Utilising numerical simulations for flow and heat transfer in the subsurface, we showed that the heat recovery efficiency could be increased by tens of percentages with such coordinated doublet deployment. Based on calculations of the Levelized Costs Of Heat for both deployment strategies, we also show that current financial support schemes do not favour heat recovery optimisation. This study emphasises that although Hot Sedimentary Aquifer resources have the potential to cover a significant part of our energy demand, a radical change in financial support schemes and legislation are required to unlock their true potential.

Suggested Citation

  • Willems, C.J.L. & M. Nick, H., 2019. "Towards optimisation of geothermal heat recovery: An example from the West Netherlands Basin," Applied Energy, Elsevier, vol. 247(C), pages 582-593.
  • Handle: RePEc:eee:appene:v:247:y:2019:i:c:p:582-593
    DOI: 10.1016/j.apenergy.2019.04.083
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    References listed on IDEAS

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    2. Babaei, Masoud & Nick, Hamidreza M., 2019. "Performance of low-enthalpy geothermal systems: Interplay of spatially correlated heterogeneity and well-doublet spacings," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Wang, Yang & Voskov, Denis & Khait, Mark & Saeid, Sanaz & Bruhn, David, 2021. "Influential factors on the development of a low-enthalpy geothermal reservoir: A sensitivity study of a realistic field," Renewable Energy, Elsevier, vol. 179(C), pages 641-651.
    4. 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.
    5. Xufeng Yan & Kangsheng Xue & Xiaobo Liu & Xiaolou Chi, 2023. "A Novel Numerical Method for Geothermal Reservoirs Embedded with Fracture Networks and Parameter Optimization for Power Generation," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    6. Liu, Guihong & Wang, Guiling & Zhao, Zhihong & Ma, Feng, 2020. "A new well pattern of cluster-layout for deep geothermal reservoirs: Case study from the Dezhou geothermal field, China," Renewable Energy, Elsevier, vol. 155(C), pages 484-499.
    7. Guillem Piris & Ignasi Herms & Albert Griera & Montse Colomer & Georgina Arnó & Enrique Gomez-Rivas, 2021. "3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models," Energies, MDPI, vol. 14(21), pages 1-21, November.
    8. Vaccari, Marco & Pannocchia, Gabriele & Tognotti, Leonardo & Paci, Marco & Bonciani, Roberto, 2020. "A rigorous simulation model of geothermal power plants for emission control," Applied Energy, Elsevier, vol. 263(C).
    9. Jahanbani Veshareh, Moein & Thaysen, Eike Marie & Nick, Hamidreza M., 2022. "Feasibility of hydrogen storage in depleted hydrocarbon chalk reservoirs: Assessment of biochemical and chemical effects," Applied Energy, Elsevier, vol. 323(C).
    10. 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).
    11. 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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