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<p>Final radioactive waste disposal in deep crystalline bedrock demands a thorough understanding of flow and transport mechanics in sparsely fractured rock formations. The structural complexity and heterogeneity of crystalline bedrock, and the scarcity of field data for the hydraulic characterization motivates the development of multiple alternative conceptual and numerical models, both to test our understanding and to evaluate prediction uncertainties. Discrete fracture network (DFN) models are widely used in radioactive safety assessment programs in hard crystalline rocks while channel network models offer another representation of flow networks and preferential pathways, in line with indications that flow and transport in deep fractured media are usually dominated by a relatively small number of long preferential pathways. This study applied the channel network modeling approach to understand the hydraulic behavior in a fractured granite system (approximately 450 m deep), at the Äspö Hard Rock Laboratory in Sweden. The channel network model is built from a hydro-structural model of the site including known fracture geometries, with the help of a python scripting library, pychan3d. The study focused particularly on an evaluation of the usefulness of different characterization data to build and calibrate such a channel network model, and to compare this to a calibrated DFN model of the same site. An evolutionary algorithm (CMAES_P implemented in the PEST code) was used to semi-automatically calibrate the channel conductances in the channel network model against the field characterization data (flow rates, drawdowns, and tracer recoveries) in multiple phases. It was observed during the calibration process that some proposed CNM connectivity maps lent themselves to conductance calibration, while others failed to do so. Channel tortuosity and width were then critical to describe transport appropriately in terms of peak arrival and dispersion. The CNM was shown to be more responsive to calibration and to general alterations than a DFN with uniform fracture planes. After calibration, the CNM could match the flow measurements closer than the reference DFN model for the tested characterization phases. The CNM and DFN with the calibrated conductances and fitted geometric parameters were then used to investigate a long-term tracer transport scenario. This comparative study highlights the potential differences and associated uncertainties in the behavior of the two distinct types of models used in the study of crystalline hard rock fractured system.</p>

Performance assessment of nuclear waste disposal in deep crystalline bedrock demands a thorough understanding of the related flow and transport processes. Uncertainties may arise both from the selection of the conceptual model as well as the estimation of the related model parameters. Discrete fracture network (DFN) models are widely used for such modeling while channel network models (CNM) provide an alternative representation, the latter focusing on the fact that flow and transport in deep fractured media often are dominated by a small number of long preferential flow paths. This study applies the principle of channel networks, implemented in the Pychan3d simulator, to analyze the hydraulic and tracer transport behavior in a 450‐m‐deep fractured granite system at the Äspö Hard Rock Laboratory in Sweden, where extensive site characterization data, including hydraulic and tracer test data are available. Semi‐automated calibration of channel conductances to field characterization data (flow rates, drawdowns, and tracer recoveries) is performed using PEST algorithm. It was observed that an optimal CNM connectivity map for channel conductance calibration can only be developed by jointly fitting flow rates, drawdowns and tracer mass recovery values. Results from data‐calibrated CNM when compared to a corresponding calibrated DFN model shows that the CNM calibrates and adapts better than a DFN model with uniform fracture surfaces. This comparative study shows the differences and uncertainties between two models as well as examines the implications of using them for long term model predictions.

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The study of fluid flow mechanics in fractured porous rocks is crucial in the area of oil and gas production industries, enhanced geothermal system (EGS), CO2 sequestration, disposal of nuclear waste in deep geological repositories (DGR), etc. There are usually two types of flows in fractured rockmass setting. The dominant flow occurs through the fractures whereas there is also a slow movement of fluid through the matrix block. The fluid movement between fracture and matrix is often continuous across the fracture. The present study focuses on the development of a numerical model which can simulate the flow behavior through fracture and matrix simultaneously, which is also known as dual permeability model. To simulate this problem, a 3D model is built in COMSOL Multiphysics 4.3a where a cylindrical geometry is made, and a fracture is defined parallel to the axis of the geometry. The asperity of the fracture is defined by a variable ‘a’ which varies along the x-axis, in such a way that increases the value of ‘a’ alters the geometry of fracture and increases the roughness of fracture. Darcy flow physics is used to simulate the situation with known parameters like porosity, permeability, storage coefficient, etc. Pressure is applied as a boundary condition at two ends of the geometry which acts as driving force for fluid to flow through the block. The influence of fracture asperity on the flow behavior is examined by doing the parametric study and the study shows the decrement in the velocity magnitude with an increase in asperity. The formation of dual flow velocity regime, one along the defined fracture and the other along with the matrix, indicates the efficiency of the developed dual-porosity and permeability model.