Fracture Characterization and Stochastic Modeling of the Granitic Basement in the HDR Soultz Project (France)

Abstract

The quantification and modeling of fluid flow in fractured rocks are extensively studied to solve and predict numerous economic and environmental problems (hydrothermalism, geothermy, storage, etc.). Discontinuities such as faults and fractures are potential sites for fluid circulation and have important implications on the hydraulic properties of rocks. The matrix permeability of igneous rocks is generally small and, consequently, the global permeability is mostly controlled by the fault and fracture networks. Therefore, the quantification of the fractured rock hydraulic properties strongly depends on the knowledge of the geometrical parameters of the fractures (orientation, extension, aperture, density) and of the final 3D modeling of the fracture network organization.
In the specific case of the Soultz-Sous-Forêts geothermal reservoir, a new method of statistical analysis of fault and fracture networks is proposed to accurately model the actual 3D structure of the reservoir (Sausse et al., 2009; Dezayes et al., 2009). The statistical characterization of the fractures and faults was realized via reinterpretation of the entire database of U.B.I. images available at Soultz. 1800 fractures were determined along the three deep Soultz well paths and grouped into main conjugate fractures sets. These fractures have a mean N-S orientation and a mean dip of 70°, which is consistent with the Oligocene N-S extension responsible for the formation of the French Rhine graben. A power-law type correlation between the geometric parameters of fractures is proposed in Equation 1:
L = k . W^D (1)
where W and L are fracture width and length, respectively, k is the coefficient characteristic of the facies, and D is the fractal dimension of the fracture set. These parameters were used to determine the volumetric density of fractures (number of fractures/m3) at the well scale. Finally, this density and the statistics of fracture properties were used to constrain stochastic simulations of a discrete fracture network (DFN) in the geothermal reservoir.