Discrete fracture network (DFN) models provide a natural analysis framework for rock conditions where flow is predominately through a series of connected discrete features. Mechanistic models to predict the structural patterns of networks are generally intractable due to inherent uncertainties (e.g. deformation history) and as such fracture characterisation typically involves empirical descriptions of fracture statistics for location, intensity, orientation, size, aperture etc. from analyses of field data. These DFN models are used to make probabilistic predictions of likely flow or solute transport conditions for a range of applications in underground resource and construction projects. However, there are many instances when the volumes in which predictions are most valuable are close to data sources. For example, in the disposal of hazardous materials such as radioactive waste, accurate predictions of flow-rates and network connectivity around disposal areas are required for long-term safety evaluation. The problem at hand is thus: how can probabilistic predictions be conditioned on local-scale measurements? This presentation demonstrates conditioning of a DFN model based on the current structural and hydraulic characterisation of the Demonstration Area at the ONKALO underground research facility. The conditioned realisations honour (to a required level of similarity) the locations, orientations and trace lengths of fractures mapped on the surfaces of the nearby ONKALO tunnels and pilot drillholes. Other data used as constraints include measurements from hydraulic injection tests performed in pilot drillholes and inflows to the subsequently reamed experimental deposition holes. Numerical simulations using this suite of conditioned DFN models provides a series of prediction-outcome exercises detailing the reliability of the DFN model to make local-scale predictions of measured geometric and hydraulic properties of the fracture system; and provides an understanding of the reduction in uncertainty in model predictions for conditioned DFN models honouring different aspects of this data.

SKB and several other waste management organisations have established the international SKB Task Force on Modelling of Groundwater Flow and Transport of Solutes (TF GWFTS) to support and interpret field experiments. An important objective of the task force is to develop, test and improve tools for conceptual understanding and simulating groundwater flow and transport of solutes in fractured rocks. Work is organised in collaborative modelling tasks. This study considers Task 9, which focuses on realistic modelling of coupled matrix diffusion and sorption in heterogeneous crystalline rock matrix at depth. This is done by inverse and predictive modelling of different in-situ transport experiments. The ultimate aim is to develop models that in a more realistic way represent retention in fractured rock. The Long-Term Diffusion and Sorption Experiment (LTDE-SD) was an in-situ radionuclide tracer test performed at the Äspö Hard Rock Laboratory at a depth of about 410 m below sea level. It is one of few recent in-situ studies focusing on tracer transport in the stagnant pore water of the crystalline rock matrix. The experimental results indicated a possible deeper penetration of tracers into the rock matrix than expected and the shape of the penetration profiles were not according to theory. Posiva’s REPRO (rock matrix REtention PROperties) experimental programme has been performed at the ONKALO rock characterisation facility in Finland. The two REPRO experiments considered were the Water Phase Diffusion Experiment, addressing matrix diffusion in gneiss around a single borehole interval, and the Through Diffusion Experiment, which is performed between sections of three boreholes. These three experiments provided an opportunity to improve the conceptual understanding of solute transport in fractured rock and to increase the realism in solute transport modelling, with the ultimate goal of improving safety assessments of deep geological disposal for nuclear waste. Of additional interest is the collective work performed by the task force to conceptually understand and interpret the field experiments, and at the same time increase the realism in solute transport modelling. This study would not have been possible without the support from the waste management organisations and the work by the multiple modelling teams.