Characterization of the highly fractured zone at the Grimsel Test Site based on hydraulic tomography

Abstract

Abstract. In this study, we infer the structural and hydraulic properties of the highly fractured zone at the Grimsel Test Site in Switzerland using a stochastic inversion method. The fractured rock is modeled directly as a discrete fracture network (DFN) within an impermeable rock matrix. Cross-hole transient pressure signals recorded from constant-rate injection tests at different intervals provide the basis for the (herein presented) first field application of the inversion. The experimental setup is realized by a multi-packer system. The geological mapping of the structures intercepted by boreholes as well as data from previous studies that were undertaken as part of the In Situ Stimulation and Circulation (ISC) experiments facilitate the setup of the site-dependent conceptual and forward model. The inversion results show that two preferential flow paths between the two boreholes can be distinguished: one is dominated by fractures with large hydraulic apertures, whereas the other path consists mainly of fractures with a smaller aperture. The probability of fractures linking both flow paths increases the closer we get to the second injection borehole. These results are in accordance with the findings of other studies conducted at the site during the ISC measurement campaign and add new insights into the highly fractured zone at this prominent study site.

Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured‐Porous Field Site

“…This was also shown by Fischer et al (2020) for a karstic and fractured aquifer, where the inferred transmissivities of fracture and matrix differ by several orders of magnitude. However, for an almost impermeable rock matrix (e.g., in most crystalline rocks), where hydraulic connections are exclusively maintained by the fractures, the classical DFN inversion (without matrix flow) can be sufficient (Ringel et al, 2021(Ringel et al, , 2022. If, on the other hand, the permeability contrast between matrix and fractures is very small, for example, due to only partially open fractures or high fracture surface roughness, the heterogeneities can be assumed continuous, so that the travel time inversion is advantageous due to its simplicity and computational efficiency.…”

“…where σ is the data variance estimated by Gibbs sampling, as in previous works (Ringel et al, 2019(Ringel et al, , 2022. The posterior distribution of the DFN parameters is evaluated by generating samples from the distribution according to Markov chain Monte Carlo (MCMC) methods.…”

“…Additionally, parameter updates can be applied that adjust position, length, or hydraulic conductivity of the fractures. More information about this DFN inversion approach can be found in Ringel et al (2022).…”

“…Further insights into the properties of fracture networks can be gained by implementing a DFN model for the inversion. The hydraulic properties of a predefined DFN structure (Klepikova et al, 2014(Klepikova et al, , 2020, the structural properties (Somogyvári et al, 2019), or structural and hydraulic properties of DFNs (Fischer et al, 2020;Ringel et al, 2022) can be estimated. Typically, the contribution of the matrix to the flow is neglected in the DFN model, but the approach can infer individual (discrete) fractures based on the HT data.…”

Fracture Network Characterization in Reservoirs by Joint Inversion of Microseismicity and Thermal Breakthrough Data: Method Development and Verification

“…For this, the input parameter of orientation (s) needs to be replaced by dip angle and strike, and the fracture length (l) needs to be replaced by length and width assuming the shape of fracture features, for example, a plane rectangle. The rjMCMC approach for fracture network updating is also applicable to the characterization of 3D fracture parameters (Equations 10 and 11) (Ringel et al, 2022). The effect of the inversion framework was demonstrated by applying heat as tracer.…”