Multi-Objective Optimization of Geothermal Systems
Optimizing Well Placement and Control to Balance Economic Returns and Reservoir Longevity
M. Devos (TU Delft - Civil Engineering & Geosciences)
A. Daniilidis – Mentor (TU Delft - Reservoir Engineering)
C. Wallmeier – Mentor (TU Delft - Reservoir Engineering)
D.V. Voskov – Mentor (TU Delft - Reservoir Engineering)
Oleg Volkov – Mentor (Stanford University)
Guillaume Rongier – Graduation committee member (TU Delft - Applied Geology)
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Abstract
Conduction-dominated geothermal systems are essential for decarbonizing the built environment, particularly in densely populated areas with high heating demand. Geothermal development in the West Netherlands Basin (WNB) has accelerated but still remains largely uncoordinated, following a "first-come, first-served" model which results in suboptimal subsurface resource utilization.
This study presents a multi-objective optimization approach for geothermal field development that simultaneously considers economic performance and reservoir longevity. The framework applies the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify Pareto-optimal configurations for well placement and operational control. Objective functions, Net Present Value (NPV) and system lifetime, are evaluated through fully coupled geothermal reservoir simulations using the Delft Advanced Research Terra Simulator (DARTS). The framework incorporates constraint-aware optimization with regulatory compliance, enabling simultaneous optimization of spatial configuration and flow rates through capacity-dependent rate allocation.
The approach is developed and validated on a small-scale synthetic model before application to a realistic corner-point geometry model of the WNB incorporating heterogeneous fluvial architecture. Multiple well configurations (10, 12, and 20 doublets) are systematically evaluated across different geological realizations.
Results demonstrate that NSGA-II effectively identifies diverse Pareto-optimal solutions spanning NPV ranges of 0.8-1.6 billion euros and system lifetimes of 35-100 years. The analysis reveals that total injection capacity directly correlates with economic performance, with higher well-count configurations achieving superior NPV through increased heat extraction capacity. The optimization consistently reveals a distinctive spatial strategy where injection wells are positioned in the thickest reservoir regions with high-permeability zones, while producers balance maximizing distance from injectors with targeting high-temperature, high-permeability areas.
This framework provides quantitative evidence that coordinated planning strategies yield superior performance compared to the current "first-come, first-served" strategies. By applying multi-objective optimization to geothermal planning, the study advocates for the move towards coordinated, regional-scale planning strategies that enable more sustainable and economically superior use of subsurface resources.