Pressure transient analysis to investigate a coupled fracture corridor and a fault damage zone causing an early thermal breakthrough in the North Alpine Foreland Basin

Abstract

The heterogeneity of the Upper Jurassic carbonate reservoir (Malm reservoir) beneath the North Alpine Foreland Basin has a significant influence on the mass and heat flow processes during geothermal exploitation. Geophysical borehole data revealed that sub-seismic scale fractures and karstified fractures occur at the inflow zones of deep geothermal wells. However, pressure transient analysis (PTA) in some previous studies concluded that it is difficult to detect the influence of sub-seismic scale features, suggesting that radial flow regime is dominant. Accordingly, a regional thermal-hydraulic model adopted the equivalent porous medium (EPM) approach, homogenizing the sub-seismic scale reservoir heterogeneities; however, unable to detect an early thermal breakthrough (ETB) in a geothermal doublet located SE of Munich. We apply PTA on three buildup tests belonging to that doublet following a deterministic approach to constrain the reservoir type by interpreting the pressure derivative (PD) plots constrained by geophysical and geological data. We derive the magnitudes of the reservoir hydraulic parameters by matching the PD plots with the selected interpretation models. We find that clustered fractures have a significant influence on the reservoir hydraulics, evidenced by trough-shaped curves in the PD plots. Linear flow regime interpreted from the interference test between the two wells indicates permeability anisotropy, which may have caused the ETB. Geophysical data interpretations indicate that these fractures correspond to a coupled fault damage zone and a fracture corridor. Finally, we present a fit-for-purpose 2D discrete fracture network model utilizing the PTA results to match our analytically calibrated model. Our study offers a potential hydraulic explanation to the cause of the ETB highlighting the importance of integrating multi-scale/disciplinary data sets to improve the reliability of dynamic reservoir models, based on which, economic-related decisions are made.