Modeling, simulation, and optimization of geothermal energy production from hot sedimentary aquifers
DOI: https://doi.org/10.1007/s10596-020-09989-8
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10622
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10622
Blank, Laura; Meneses Rioseco, Ernesto; Caiazzo, Alfonso; Wilbrandt, Ulrich, 2020: Modeling, simulation, and optimization of geothermal energy production from hot sedimentary aquifers. In: Computational Geosciences, Band 25, 1: 67 - 104, DOI: 10.1007/s10596-020-09989-8.
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Geothermal district heating development has been gaining momentum in Europe with numerous deep geothermal
installations and projects currently under development. With the increasing density of geothermal wells, questions related
to the optimal and sustainable reservoir exploitation become more and more important. A quantitative understanding of
the complex thermo-hydraulic interaction between tightly deployed geothermal wells in heterogeneous temperature and
permeability fields is key for a maximum sustainable use of geothermal resources. Motivated by the geological settings of
the Upper Jurassic aquifer in the Greater Munich region, we develop a computational model based on finite element analysis
and gradient-free optimization to simulate groundwater flow and heat transport in hot sedimentary aquifers, and numerically
investigate the optimal positioning and spacing of multi-well systems. Based on our numerical simulations, net energy
production from deep geothermal reservoirs in sedimentary basins by smart geothermal multi-well arrangements provides
significant amounts of energy to meet heat demand in highly urbanized regions. Our results show that taking into account
heterogeneous permeability structures and a variable reservoir temperature may drastically affect the results in the optimal
configuration. We demonstrate that the proposed numerical framework is able to efficiently handle generic geometrical and
geological configurations, and can be thus flexibly used in the context of multi-variable optimization problems. Hence,
this numerical framework can be used to assess the extractable geothermal energy from heterogeneous deep geothermal
reservoirs by the optimized deployment of smart multi-well systems.