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Alternative Modeling Approaches for Flow & Transport in Fractured Rock Douglas D. Walker, DE&S Jan-Olof Selroos, SKB Supported by Swedish Nuclear Fuel and Waste Management Co. (SKB) Presentation Overview • Context and Objectives of the Alternative Models Project • The hypothetical Aberg Repository • 3 alternative conceptual models of heterogeneity • Performance measures • Results and Conclusions Deep Geologic Disposal of Nuclear Waste Cladding Fuel Rod Spent Fuel Canister Bentonite Bedrock Repository Tunnel Nuclear Waste Disposal Performance Assessment Inhalation Ingestion Irradiation CLIMATE ENGINEERED BARRIER EVENTS: Intrusion Seismic Volcanic BIOSPHERE GEOSPHERE Uncertainty in Subsurface Hydrology • Uncertainty vs. variability • Uncertainty in: – process physics – measurement characterization of heterogeneity – upscaled representation in models The Alternative Models Project • Nuclear waste disposal performance assessment uncertainty analysis • Compare alternative representations of flow / transport in fractured rocks • Explicit definition of – test problem premises – performance measures and summary statistics Aberg Repository Aberg Site and Data • Hydrogeologic Setting: – Inland recharge, discharge to Baltic – Fractured granitic rocks – Large-scale fracture zones (deterministic) • Data: – 53 Boreholes (hydraulic/tracer tests, chem) – geophysics, fracture trace maps – Äspö Hard Rock Laboratory • Regional model / boundary conditions Aberg: Deterministic Fracture Zones and Repository Alternative Conceptual Models Channel Network Stochastic Continuum Discrete Fracture Stochastic Continuum • Effective porous medium (Darcy’s Law) • Spatially correlated RV + deterministic zones • Finite Difference flow model • Advective particle tracking Stochastic Continuum: Application • Conductivity distribution – 3m K tests 25m, Lognormal + variogram – Rock & Conductor distributions – homogeneous ar = 1.2 m2/m3 rock • Structural model – Deterministic zones only • Repository – 945 canisters x 34 realizations Stochastic Continuum: Travel Paths Travel Time, yr Elevation, from south Stochastic Continuum • Advantages: – hydraulic tests are volume averages – method / software well-established • Disadvantages: – Scale dependence of K in fractured media poorly understood – Preferential paths not represented at scales below block size Discrete Fracture Network Fracture Network Flow Area 1-D Pipe Network Discrete Fracture • Fracture simulation with observed frequency, size and orientation • Deterministic zones • 1-D Pipe / Finite Element flow solution • Pathway analysis for transport Discrete Fracture Network: Application • Fracture Distribution – Deterministic Zones and Canister fractures – Lognormal, with 20 R 1000m in region and 0.2 R 20m at repository – Lognormal transmissivity – ar = f (area between fracture traces) • Repository – 50 to 90% of 81 canisters x 10 realizations Discrete Fracture Network: Travel Paths Realization 9 West Block 3 Block 4 Block 6 Top View Discrete Fracture Network • Advantages: – Represents the conductive structures (Realism) – Allows for preferential paths • Disadvantages: – Data demand – Computational demand – Matrix permeability may be important Flow Channeling Areas with stagnant water (access by diffusion only) Channels with mobile water Fracture surfaces in contact with each other Channel Network • Channel simulation with observed frequency and conductance distribution • Deterministic zones • 3-D Finite Difference flow solution • Particle tracking with total mixing at intersections Channel Network Intersections Channel Network: Application • Conductance Distribution – 3m K tests 30m, Lognormal – Rock, Conductor, & EDZ distributions – ar = 1.2 m2/m3 in Zones, 1/10 in Rock • Structural model – Deterministic zones • Repository – 229 cans x 30 real x median (200 particles) Channel Network: Travel Paths Channel Network • Advantages: – Represents observed channels within fracture planes, directly assigns ar – Allows for preferential paths and dispersion – Includes diffusion/sorption in matrix, flow within Rock • Disadvantages: – Conductance is scale dependent Application Summary SC CN DFN Zones logK= logK= LogN by zone 1.6 LogN by zone 0.8 Constant by zone 0 Rock logK= logK= LogN by region 1.6 LogN by zone 0.8 Flowwetted surface Homogen. Homogen. by Zones, Rock, EDZ Trunc. LogN Radii 0.2<R<20m 20<R<1000m LogN logT=9e-7 Heterogen, a function of radius and connection Simulation Summary Canisters Realization EDZ SC CN DFN 945 locations Median of 200 released at 229 locations 50 to 90% of 81 locations 34 30 10 Below resolution 10 K of rock mass canister fractures T = 1e-9 Performance Measures • Travel time: canister to biosphere tw = qw/f [yr] • Canister Flux: Darcy flux at canisters qw [m/yr] • F-factor: Retardation vs. Advection F = (dw ar) / qw [yr/m] Performance measures: Medians 7 6 5 4 SC DFN CN 3 2 1 0 Log Travel -Log Time Canister (yr) Flux (m/yr) Log Ffactor (yr/m) Performance measures: Variances 1.2 1 0.8 0.6 SC DFN CN 0.4 0.2 0 Log Travel Log Time Canister Flux (yr) (m/yr) Log Ffactor (yr/m) Discussion • Median performance measures and exit locations similar (Controlled by premises of BC, major zones) • For DFN, F-factor variance greater than tw variance (variability of ar impacts PA) • SC variances greatest, but differences in studies complicate comparison Discussion II • Modeling study differences: – # particles released SC = one / canister DFN = one / canister subset CN = median of 200 / canister subset – # canisters with pathways 100% in SC and CN; 50 to 90% in DFN – Not evaluated: team experience, Sensitivity of inference to data • SC and CN boundary flow, DFN low Conclusions For this site and these performance measures: • Problem premises constrain the results • Uncertainties regarding conceptual models of flow / transport in fractured rocks have limited effect on PA • Chief benefit of DFN / CN is to examine effects of ar Acknowledgements SC Modeling Study: H.Widén (Kemakta), D. Walker (DE&S) DFN Modeling Study: W Dershowitz, S Follin, T Eiben, J Andersson (GA) CN Modeling Study: B. Gylling, L. Moreno, I. Neretnieks (KTH) Swedish Nuclear Fuel and Waste Management Co. A. Ström, J-O. Selroos (SKB)