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Coupled Numerical and Analytical Simulation on Delft Campus Geothermal Well

Yuan CHEN, Guillaume RONGIER, James Robert MULLINS, Denis VOSKOV, Alexandros DANIILIDIS

Key words
DUGS, numerical simulation, reservoir heterogeneity, geological uncertainty
Conference
Stanford Geothermal Workshop
Year
2025
Session
Modeling
Language
English
Paper number
Chen1

Full text

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Abstract

With the growing interest in geothermal energy as a green, local solution, accurate representation of geological uncertainty is critical. The Delft campus geothermal project aims to provide clean heating for the campus buildings and surrounding parts of the city. In this work, we evaluate the thermal response of the geothermal system under a range of potential subsurface uncertainties using numerical and analytical methods. An initial ensemble of geological models combining data collected during the drilling campaign combined with regional studies was generated to capture a wide range of geological uncertainty. Subsequently, we perform a static analysis on the heterogeneity level of all geological models. Then the geological models are dynamically simulated in the open-source software Delft Advanced Research Terra Simulator (open-DARTS). This work demonstrates that, there can be a significant variation in our assessment of the lifetime of the geothermal system and the extent of the cold plume front with subtle variations in subsurface heterogeneity. Additionally, our study reveals that the majority of geological models exhibit injection well BHP values below the government (SodM) regulations. Furthermore, there is a potentially hydraulic connection between the reservoir layers and the layers above the reservoir due to the loss of initial borehole which are openly abandoned. We design a coupled analytical radial flow and numerical simulations framework to estimate the risk of water losses and the cold front propagation at the layers above the target reservoir. We find that the geological uncertainties especially the permeability and thickness can prominently affect the prediction of water losses and cold front propagation at the upper layers.

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