Characterisation and Modeling of Discontinuous Rock Mass: Geostatistical Interpretation of Seismic Response to Fracture Occurrence, Discrete Fracture Network Modeling and Stability Predictions for Underground Excavations
Geometric and mechanical characterisation of rock discontinuities is an essential constituent in deriving a reliable assessment of overall properties of crystalline rock mass. The knowledge about the occurrence, size, geometry pattern and intensity of joints/fractures is necessary to predict the performance of fractured rock as a fractured reservoir, or an underground transport and storage facility.
This study has a main focus on the characterisation and description of discontinuities and their impact on mechanical and hydraulic behavior of discontinuous crystalline rock mass. The study is divided into two main topics: (i) determining joint geometry from seismic attributes induced during pressurization of a geothermal reservoir, (ii) stochastic fracture modeling and probabilistic predictions of stability for underground excavations.
The orientation of the major joint sets within the Hot Dry Rock geothermal reservoir at Soultz-sous-Forêts in France is inferred from studying the spatial variation of the seismic estimates of shear displacement and stress drop during water injection into the reservoir. The variation pattern of the seismic source attributes obtained from variogram function proves to correlate with fracture dip angle along vertical plane and with fracture set azimuth in horizontal plane. The study shows that using water injection-induced seismicity offers a potential to make inferences about the possible fluid flow paths in the reservoir far from the injection well.
The stochastic fracture models are designed for making predictions of the CLAB 2 rock cavern's stability located on the southeast coast of Sweden and aimed to serve as interim storage facility for spent nuclear fuel. The generated fracture networks incorporate fracture size, orientations, intensity, spatial variation pattern and fracture termination mode. The properties of the networks are represented by the best-match probability functions. The predictions of the occurrence and stability status of keyblocks are made. The predictions are presented as probability density functions and the appropriateness of the distributional parameters for further tunnel support design is discussed. Also, the sensitivity of the block predictions to uncertainty in estimating the properties of the stochastic fracture network is investigated by statistic factorial designs. The study not only demonstrates the advantages of the probabilistic predictions over the deterministic approaches but also their interpretational complexity.
stochastic fracture network