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Flexible well patterns and cashflow optimisation on large-scale geothermal field development

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  • Kane, Entela
  • Leeuwenburgh, Olwijn
  • Joosten, Gerard
  • Daniilidis, Alexandros
  • Bruhn, David

Abstract

The Netherlands aims to be CO2 neutral by 2050, aligning with the Paris Agreement. To achieve this, it is crucial to increase the contribution of geothermal energy to renewable energy sources, necessitating large-scale exploitation to speed up the energy transition. Only small-scale (1–2 km) geothermal field developments exist in the Netherlands primarily for heating. Expanding to extensive geothermal fields (>10 km length) requires a strategic approach to well placement and consideration of the economic constraints associated with geothermal projects. The heterogeneity of the subsurface is a critical factor in developing large-scale geothermal reservoirs. This study introduces an innovative approach to optimising well placement based on geological trends, using a well-density function as a proof of concept. Implementing and optimising flexible well patterns for large-scale geothermal developments significantly enhances profitability compared to conventional oil and gas industry methods. Optimised flexible well patterns favour a long-term utilisation of energy recovered, minimise pressure extrema in the reservoir, and improve sweep efficiency. However, their application depends on reservoir operational decisions. The optimisation process ensures economic viability, even with lower heat prices. Broadly, this methodology could be key to scaling up geothermal developments to meet the objectives of the Paris Agreement.

Suggested Citation

  • Kane, Entela & Leeuwenburgh, Olwijn & Joosten, Gerard & Daniilidis, Alexandros & Bruhn, David, 2025. "Flexible well patterns and cashflow optimisation on large-scale geothermal field development," Renewable Energy, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:renene:v:243:y:2025:i:c:s0960148125001569
    DOI: 10.1016/j.renene.2025.122494
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Willems, Cees J.L. & Nick, Hamidreza M. & Weltje, Gert Jan & Bruhn, David F., 2017. "An evaluation of interferences in heat production from low enthalpy geothermal doublets systems," Energy, Elsevier, vol. 135(C), pages 500-512.
    4. Wang, Yang & Voskov, Denis & Khait, Mark & Bruhn, David, 2020. "An efficient numerical simulator for geothermal simulation: A benchmark study," Applied Energy, Elsevier, vol. 264(C).
    5. Stefan C. Endres & Carl Sandrock & Walter W. Focke, 2018. "A simplicial homology algorithm for Lipschitz optimisation," Journal of Global Optimization, Springer, vol. 72(2), pages 181-217, October.
    6. Daniilidis, Alexandros & Alpsoy, Betül & Herber, Rien, 2017. "Impact of technical and economic uncertainties on the economic performance of a deep geothermal heat system," Renewable Energy, Elsevier, vol. 114(PB), pages 805-816.
    7. Chen, Mingjie & Tompson, Andrew F.B. & Mellors, Robert J. & Abdalla, Osman, 2015. "An efficient optimization of well placement and control for a geothermal prospect under geological uncertainty," Applied Energy, Elsevier, vol. 137(C), pages 352-363.
    8. 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.
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