Thermal response test for shallow geothermal applications: a probabilistic analysis approach

Thermal Response Test (TRT) is an onsite test used to characterize the thermal properties of shallow underground, when used as heat storage volume for shallow geothermal application. It is applied by injecting/extracting heat into geothermal closed-loop circuits inserted into the ground. The most common types of closed loop are the borehole heat exchangers (BHE), horizontal ground collectors (HGC), and energy piles (EP). The interpretation method of TRT data is generally based on a regression technique and on the calculation of thermal properties through different models, specific for each closed loop and test conditions. A typical TRT record is a graph joining a series of experimental temperatures of the thermal carrier fluid. The proposed geostatistical approach considers the temperature as a random function non-stationary in time, with a given trend, therefore the record is considered as a 'realization', one of the possible results; the random nature of the test results is transferred to the fluctuations and a variogram modeling can be applied, which may give many information on the TRT behavior. In this paper, a nested probabilistic approach for TRT output interpretation is proposed, which can be applied for interpreting TRT data, independently of the different methodologies and technologies adopted. In the paper, for the sake of simplicity, the probabilistic approach is applied to the 'infinite line source' (ILS) methodology, which is the most commonly used for BHE. The probabilistic approach, based on variogram modeling of temperature residuals, is useful for identifying with robust accuracy the time boundaries (initial time t 0 and the final time t f) inside which makes temperature regression analysis possible. Moreover, variograms are used into the analysis itself to increase estimation precision of thermal parameter calculation (ground conductivity λ g, ground capacity c g, borehole resistance R b). Finally, the probabilistic approach helps keep under control the effect of any cause of result variability. Typical behaviors of power, flows, and temperatures and of their interaction with the specific closed-loop circuit and geo-hydrological system are deepened by variogram analysis of fluctuations

Caratterizzazione dei parametri di un reservoir geotermico tramite la risoluzione del problema inverso e le simulazioni geostatistiche

BTES (borehole thermal energy storage)systems exchange thermal energy by conduction with the surrounding ground through borehole materials. The spatial variability of the geological properties and the space-time variability of hydrogeological conditions affect the real power rate of heat exchangers and, consequently, the amount of energy extracted from / injected into the ground. For this reason, it is not an easy task to identify the underground thermal properties to use when designing. At the current state of technology, Thermal Response Test (TRT) is the in situ test for the characterization of ground thermal properties with the higher degree of accuracy, but it doesn’t fully solve the problem of characterizing the thermal properties of a shallow geothermal reservoir, simply because it characterizes only the neighborhood of the heat exchanger at hand and only for the test duration. Different analytical and numerical models exist for the characterization of shallow geothermal reservoir, but they are still inadequate and not exhaustive: more sophisticated models must be taken into account and a geostatistical approach is needed to tackle natural variability and estimates uncertainty. The approach adopted for reservoir characterization is the “inverse problem”, typical of oil&gas field analysis. Similarly, we create different realizations of thermal properties by direct sequential simulation and we find the best one fitting real production data (fluid temperature along time). The software used to develop heat production simulation is FEFLOW 5.4 (Finite Element subsurface FLOW system). A geostatistical reservoir model has been set up based on literature thermal properties data and spatial variability hypotheses, and a real TRT has been tested. Then we analyzed and used as well two other codes (SA-Geotherm and FV-Geotherm) which are two implementation of the same numerical model of FEFLOW (Al-Khoury model)

Upgrade of the B2G dynamic geothermal heat exchanger model: Optimal location of the ground nodes

In order to optimize the design and operation of a ground source heat pump system, the modeling of the Borehole Heat Exchanger (BHE) and its coupling to the heat pump operation becomes crucial. This becomes key for those systems with on/off operation, where it is important to model the short-term response of the BHE accurately. Furthermore, the modeling of the local variation of the ground temperature near the BHE will be highly influenced by ground thermal properties and the operation of the system. In this context, the novel B2G dynamic model was developed and experimentally validated in previous works for a single U BHE and adapted to a novel coaxial spiral configuration. In order to consider the influence of the soil surrounding the BHE, two ground nodes were initially defined and their position (penetration radii) was calculated for a specific type of soil and operating conditions. This paper presents an upgrade of the B2G model, with a descripton of penetration radii calculation. For this purpose, a comparison between the B2G model and the Infinite Cylindrical Source model was carried out to find the penetration radii that reproduce the ground thermal response with a higher accuracy under the corresponding soil thermal properties and operating conditions