Installation of open-loop geothermal heat pump (GSHP) systems for heating and cooling of buildings requires detailed planning in order to maximize management efficiency and minimize unwanted impacts. Failure to do so can induce a decline in public acceptance of these systems.
Groundwater modeling is essential for extracting management and impact salient information from site data, quantifying the repercussions of data insufficiency, and providing a basis for effective acquisition of further data. We exemplify a workflow for use in heterogeneous hydrogeological environments using a synthetic model based on a real-world setting. Simulation employs the MODFLOW 6 Groundwater Energy (GWE) model. The simulator is parameterized with stochastic hydraulic property fields based on nonstationary variograms. This type of parameterization can express hydrogeological conditions that prevail in complex aquifers such as those that exist near rivers, or are affected by faulting/fracturing. The numerical burden of assimilating borehole head and thermal data in order to quantify and reduce uncertainties of predicted GSHP efficiency and impact is minimal, as this is implemented using data space inversion (DSI). This eliminates the need for history-match-adjudicated parameter adjustment, while associating realistic uncertainties with management-critical predictions. Use of DSI offers the additional benefit of allowing rapid assessment of the ability of as yet unacquired data to reduce the uncertainties of key system performance and impact predictions, at the same time as it allows continuous assimilation of new data that emerges through GSHP operation.
Despite its outward complexity, this approach to open-loop GSHP system management is relatively easy to implement and incurs only a minimal numerical burden.