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 CladdingFuel Rod Spent Fuel Canister Bedrock Bentonite Repository Tunnel

Nuclear Waste Disposal Performance Assessment Inhalation Ingestion Irradiation ENGINEERED BARRIER BIOSPHERE CLIMATE GEOSPHERE EVENTS: Intrusion Seismic Volcanic

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 Stochastic Continuum Discrete Fracture Channel Network

Stochastic Continuum 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 a r = 1.2 m 2 /m 3 rock Structural model –Deterministic zones only Repository –945 canisters x 34 realizations

Stochastic Continuum: Travel Paths Elevation, from south Travel Time, yr

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 1-D Pipe Network Flow Area Fracture Network

Discrete Fracture 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 –a r = f (area between fracture traces) Repository –50 to 90% of 81 canisters x 10 realizations

Discrete Fracture Network: Travel Paths

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 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 –a r = 1.2 m 2 /m 3 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 a r –Allows for preferential paths and dispersion –Includes diffusion/sorption in matrix, flow within Rock Disadvantages: –Conductance is scale dependent

Application Summary

Simulation Summary

Performance Measures Travel time: canister to biosphere t w = q w /  f [yr] Canister Flux: Darcy flux at canisters q w [m/yr] F-factor: Retardation vs. Advection F = (d w a r ) / q w [yr/m]

Performance measures: Medians (yr) (m/yr) (yr/m)

Performance measures: Variances (yr) (m/yr) (yr/m)

Discussion Median performance measures and exit locations similar (Controlled by premises of BC, major zones) For DFN, F-factor variance greater than t w variance (variability of a r 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 a r

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)