Since the mismatch between short- and medium-term energy demand and generation is a crucial challenge of the energy transition in societies that increasingly rely on renewable ¿green¿ energy sources, a new subsurface energy storage concept is being considered in the form of underground thermal energy storage, where excess energy but also waste heat can be stored and used during the months of demand. Underground thermal energy storage can be further divided by storage technology into: i) Aquifer Thermal Energy Storage (ATES), ii) Borehole Thermal Energy Storage (BTES), as well as iii) Pit Thermal Energy Storage (PTES), and iv) Cavern Thermal Energy Storage (CTES). This thesis presents basic concepts of these techniques and summarizes best-practice case studies as well as the specific requirements for successful seasonal storage. Furthermore, it includes a case study for a potential ATES facility in the Vienna Basin. In ATES, heat energy is stored in hot water which is injected into the subsurface and later produced back to the surface to harvest the heat in heat exchangers e.g., for space heating. In order to successfully develop such an ATES operation, one of the most important parameters to consider in well design is the membrane filter index, which is the clogging potential of the infiltration water, and the thermal radius to minimize thermal interference between the wells and the surrounding environment. Furthermore, ATES requires a certain reservoir quality (e.g., net thickness, effective porosity, and permeability) which has to be evaluated similar to conventional hydrocarbon or geothermal reservoir exploration. The Vienna Basin case study focused on these reservoir quality aspects and targeted three potential middle Miocene reservoir horizons in a target area in the central Vienna Basin for which seismic and wire line log data were provided by OMV. The three target horizons included one Badenian and two (lower and upper) Sarmatian units. A particular challenge was the restriction of reliable wire line log data to the central part of the target area, with a limitation of logs in the remaining parts. Porosity values were first recalculated from the available resistivity logs based on an empirical relation provided by OMV, followed by a permeability modelling based on porosity using a porosity ¿ permeability relation provided by OMV as well. The data were then scaled up to match the scale of the reservoir bins. Since all wells with log data concentrate in the center of the modeled reservoir, stochastic simulation was used instead of classical kriging to ensure that the model areas farther from the true well data still provided meaningful results. To further improve the model, a seismic attribute, the root mean square (RMS) of seismic amplitude, was also included in the simulation. The resulting histograms of the entire models show good correlation with the upscaled well data as well as with the true input well data. The porosity and permeability models show good correlation with each other, with the most reliable results obtained for the Sarmatian 2 model, where channels with high porosity and permeability are located predominantly in the southeastern part of the model. Overall, the reservoir modelling shows that particularly the Sarmatian intervals show ATES potential in terms of reservoir quality, although the success of an ATES application will depend on multiple factors beyond reservoir characterization (e.g., heat demand matching, energy costs for pumping, well design).