A Unified Approach to Describing Flow Dynamics in Geothermal Energy Production Systems
Geothermal energy is typically produced by a collection of wells which drain a reservoir. Engineers’ experience and reservoir monitoring data are employed to properly determine the wells in operation and their production rate. However, identifying the optimal well configuration which contributes the...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Materials Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4605/15/1/55 |
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| Summary: | Geothermal energy is typically produced by a collection of wells which drain a reservoir. Engineers’ experience and reservoir monitoring data are employed to properly determine the wells in operation and their production rate. However, identifying the optimal well configuration which contributes the most to the geothermal power produced at the system outlet is very complex since the extracted fluid’s energy is attenuated when traveling through the production wells and the surface network toward the delivery point. Undoubtedly, a reliable optimizer focusing on a unified system would greatly improve its management regarding both energy production and sustainability. In this work, a mathematical model is proposed, which fully describes flow in the joined production system, by coupling the reservoir, wellbore and ground pipeline network flow dynamics. The reservoir IPR (inflow performance relationship) curves are combined with the pipeline network’s hydraulic/thermal behavior, to estimate the geothermal fluid’s pressure, flow and temperature at the delivery point. Every design detail, such as the well geometry, subsurface heat loss and pressure/heat loss along the ground pipeline network, is accounted for. Subsequently, an optimizer identifies the choking that needs to be imposed at each wellhead, so that the geothermal fluids produced account for the minimum mass rate for a given heat load, thus contributing to the sustainability of the geothermal system. The model can be calibrated using history matching to further improve the estimation accuracy. Optimal conditions can be recalculated every time a change takes place in the subsurface system, the surface network or the production constraints. |
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| ISSN: | 2673-4605 |