The assessment of geological repositories for hazardous materials requires the modelling of coupled phenomena involving mechanical and fluid transport processes. In many poromechanical simulations, material parameters such as the elastic stiffness or the permeability are assumed constant. However, the porous fabric of rocks exhibits complex heterogeneous microstructures, which can experience micromechanical cracking. The evaluation of the effects of the excavation damage zone on the fluid transport phenomenon is therefore of crucial importance for a proper account of the potential contaminant transport. This contribution addresses the application of an off-line two-scale finite element approach to evaluate the material degradation caused by excavation. The use of mechanical simulations as a basis for reproducing the experimental permeability evolution by computational homogenization of degraded RVEs (Representative Volume Elements) is assessed for an excavation scenario.

1 Introduction

The mechanical behaviour of fluid-saturated porous media described by Biot's theory of poroelasticity (Biot 1941) has been investigated for many types of geomaterials (Selvadurai 2007, Schanz 2009). In many instances, the assumption is made that the material properties such as porosity and permeability remain unchanged during the coupled interaction. However, a number of experimental contributions have identified the potential effect of deviatoric stress states in particular on the permeability of porous media (Zoback & Byerlee 1975). When assessing geological storage of hazardous wastes, such permeability alterations have to be incorporated in simulations as they may strongly affect the pore fluid pressure dissipation in the Excavation Damage Zone (EDZ). Such aspects have been the subject of intensive research over the past decade, based on macroscopic models using either closed-form relationships coupling the mechanical stress state and the permeability, see for instance (Rutqvist et al. 2009) and references therein; or more recently with combined FEM-DEM (Finite Element Method combined with Discrete Element Method) approaches (Lisjak et al. 2014).

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