Locating Geothermal Resources: Insights from 3D Stress and Flow Models at the Upper Rhine Graben Scale

Abstract

To be exploited, geothermal resources require heat, fluid, and permeability. These favourable geothermal conditions are strongly linked to the specific geodynamic context and the main physical transport processes, notably stresses and fluid circulations, which impact heat-driving processes. The physical conditions favouring the setup of geothermal resources can be searched for in predictive models, thus giving estimates on the so-called “favourable areas.” Numerical models could allow an integrated evaluation of the physical processes with adapted time and space scales and considering 3D effects. Supported by geological, geophysical, and geochemical exploration methods, they constitute a useful tool to shed light on the dynamic context of the geothermal resource setup and may provide answers to the challenging task of geothermal exploration. The Upper Rhine Graben (URG) is a data-rich geothermal system where deep fluid circulations occurring in the regional fault network are the probable origin of local thermal anomalies. Here, we present a current overview of our team’s efforts to integrate the impacts of the key physics as well as key factors controlling the geothermal anomalies in a fault-controlled geological setting in 3D physically consistent models at the regional scale. The study relies on the building of the first 3D numerical flow (using the discrete-continuum method) and mechanical models (using the distinct element method) at the URG scale. First, the key role of the regional fault network is taken into account using a discrete numerical approach. The geometry building is focused on the conceptualization of the 3D fault zone network based on structural interpretation and generic geological concepts and is consistent with the geological knowledge. This DFN (discrete fracture network) model is declined in two separate models (3D flow and stress) at the URG scale. Then, based on the main characteristics of the geothermal anomalies and the link with the physics considered, criteria are identified that enable the elaboration of indicators to use the results of the simulation and identify geothermally favourable areas. Then, considering the strong link between the stress, fluid flow, and geothermal resources, a cross-analysis of the results is realized to delineate favourable areas for geothermal resources. The results are compared with the existing thermal data at the URG scale and compared with knowledge gained through numerous studies. The good agreement between the delineated favourable areas and the locations of local thermal anomalies (especially the main one close to Soultz-sous-Forêts) demonstrates the key role of the regional fault network as well as stress and fluid flow on the setup of geothermal resources. Moreover, the very encouraging results underline the potential of the first 3D flow and 3D stress models at the URG scale to locate geothermal resources and offer new research opportunities.

Integration of Geophysical and Geospatial Techniques to Evaluate Geothermal Energy at Siwa Oasis, Western Desert, Egypt

“…Dense lineament zones with high permeability allow hard rock zones to recharge in geothermal energy, so horizons with high fracture densities are ideal for geothermal energy production [49]. Numerous geothermal systems have high fault and fracture densities (FFD) [50,51], and the beneficial geothermal wells are correlated with permeable faults at depth [52]. This study extracted lineament data from SRTM/DEM and high-resolution imagery using visual interpretation techniques, on-screen digitizing, and on-screen interpretation of an eight-direction summed hill-shade that was generated using the DEM.…”

Integration of Well Logging and Remote Sensing Data for Detecting Potential Geothermal Sites along the Gulf of Suez, Egypt

“…Therefore, regions of high fracture density can greatly serve as the best horizon for geothermal energy [49]. Lineament density, so-called fault and fracture density (FFD), is a vital variable since many geothermal systems are associated with high densities of faults and fractures [50,51] and productive geothermal wells are associated with permeable faults at depth [52]. Lineaments extraction in this study was performed through visual interpretation and on-screen digitizing of accentuated topography imaged in an eight-direction summed hill-shade generated from the SRTM DEM and very high-resolution imagery on Google Earth Pro.…”