Depth-Dependent Scaling of Fracture Patterns Inferred from Borehole Images in GPK3 and GPK4 Wells at Soultz-sous-Forêts Geothermal Site

Abstract

Engineering Enhanced Geothermal System (EGS) requires a proper understanding of the fracture network properties from small to large scales in order to create a reliable geological model for reservoir simulations. As deterministic identification of all fractures in a reservoir is practically impossible, stochastic approaches known as Discrete Fracture Networks (DFN) are used. This consists of parametrizing a statistical realization of fracture networks constrained by direct observations from borehole images and/or outcrop data, if available. DFN models can be used to study the thermo-hydro-mechanical (THM) properties of fractured rocks and to simulate the processes associated within: I) fluid circulation, II) flow and heat production as well as III) seismic response to hydraulic stimulations. Fractal DFNs are based on multiscale fracture network characteristics and are constrained by the scaling properties of fracture network attributes such as length (or size) and spatial distribution. The dual power-law model is a mathematical representation of fractures that parametrize fractal DFNs with two scaling exponents: 1) scaling of spatial distribution using two-point correlation dimension of fracture centers in three dimensions and 2) power-law exponent of fracture length distribution. Direct measurements of fracture length exponents from borehole images or cores are an unresolved challenge and the resolution of geophysical investigations is not sufficient to image the natural fracture networks. In contrast, the spatial distribution of fractures may be precisely characterized using borehole image logs and cores. Currently, the depth-dependence of spatial clustering of fracture patterns in earth’s crust is not fully understood, although it may be required to anticipate deep reservoir conditions from shallower datasets. Here, we study such a depth dependency by using the two-point correlation dimension of fractures along the boreholes as a reliable estimate of the fractal dimension. We investigate the data stemming from two deep boreholes, GPK3 and GPK4, drilled into the crystalline basement rocks at the Soultz-sous-Forêts geothermal site. Recent analyses unraveled no systematic variation of fractal dimension with depth in any of the boreholes at the one standard deviation level of uncertainty. This conclusion may support the hypothesis of generating fracture network models with only a single correlation dimension using the stereological relationships in reservoirs up to 5 km depth in crystalline basements.