Characterizing the impact of particle behavior at fracture intersections in three-dimensional discrete fracture networks.

We characterize the influence of different intersection mixing rules for particle tracking simulations on transport properties through three-dimensional discrete fracture networks. It is too computationally burdensome to explicitly resolve all fluid dynamics within a large three-dimensional fracture network. In discrete fracture network (DFN) models, mass transport at fracture intersections is modeled as a subgrid scale process based on a local Péclet number. The two most common mass transfer mixing rules are (1) complete mixing, where diffusion dominates mass transfer, and (2) streamline routing, where mass follows pathlines through an intersection. Although it is accepted that mixing rules impact local mass transfer through single intersections, the effect of the mixing rule on transport at the fracture network scale is still unresolved. Through the use of explicit particle tracking simulations, we study transport through a quasi-two-dimensional lattice network and a three-dimensional network whose fracture radii follow a truncated power-law distribution. We find that the impact of the mixing rule is a function of the initial particle injection condition, the heterogeneity of the velocity field, and the geometry of the network. Furthermore, our particle tracking simulations show that the mixing rule can particularly impact concentrations on secondary flow pathways. We relate these local differences in concentration to reactive transport and show that streamline routing increases the average mixing rate in DFN simulations.

[1]  Georg Kosakowski,et al.  Transport behavior in three‐dimensional fracture intersections , 2003 .

[2]  Diogo Bolster,et al.  Effects of incomplete mixing on reactive transport in flows through heterogeneous porous media , 2017 .

[3]  Satish Karra,et al.  Particle tracking approach for transport in three-dimensional discrete fracture networks , 2015, Computational Geosciences.

[4]  Pierre M. Adler,et al.  Fractures and Fracture Networks , 1999 .

[5]  P. Alam ‘G’ , 2021, Composites Engineering: An A–Z Guide.

[6]  Vladimir Cvetkovic,et al.  Numerical and analytical modeling of advective travel times in realistic three‐dimensional fracture networks , 2011 .

[7]  Adv , 2019, International Journal of Pediatrics and Adolescent Medicine.

[8]  Satish Karra,et al.  PFLOTRAN User Manual A Massively Parallel Reactive Flow and Transport Model for Describing Surface and Subsurface Processes , 2015 .

[9]  X. Sanchez‐Vila,et al.  Representative hydraulic conductivities in saturated groundwater flow , 2006 .

[10]  Jesús Carrera,et al.  A mixing ratios‐based formulation for multicomponent reactive transport , 2007 .

[11]  Satish Karra,et al.  Fracture size and transmissivity correlations: Implications for transport simulations in sparse three‐dimensional discrete fracture networks following a truncated power law distribution of fracture size , 2016 .

[12]  Satish Karra,et al.  Influence of injection mode on transport properties in kilometer‐scale three‐dimensional discrete fracture networks , 2015 .

[13]  Olivier Bour,et al.  Hydraulic properties of two‐dimensional random fracture networks following power law distributions of length and aperture , 2002 .

[14]  A. Zuber,et al.  On the physical meaning of the dispersion equation and its solutions for different initial and boundary conditions , 1978 .

[15]  Natalie C. Washburn,et al.  764 , 2019, Critical Care Medicine.

[16]  Jean-Raynald de Dreuzy,et al.  Influence of spatial correlation of fracture centers on the permeability of two‐dimensional fracture networks following a power law length distribution , 2004 .

[17]  Alberto Guadagnini,et al.  A procedure for the solution of multicomponent reactive transport problems , 2005 .

[18]  Stephen R. Brown,et al.  Fluid flow and mixing in rough-walled fracture intersections , 2006 .

[19]  Vladimir Cvetkovic,et al.  Transport of reactive tracers in rock fractures , 1999, Journal of Fluid Mechanics.

[20]  Andreas Englert,et al.  Mixing, spreading and reaction in heterogeneous media: a brief review. , 2011, Journal of contaminant hydrology.

[21]  John L. Wilson,et al.  A lattice‐gas and lattice Boltzmann study of mixing at continuous fracture Junctions: Importance of boundary conditions , 1997 .

[22]  Brian Berkowitz,et al.  Structure, flow, and generalized conductivity scaling in fracture networks , 1998 .

[23]  J. Philip,et al.  The fluid mechanics of fracture and other junctions , 1988 .

[24]  Laurence C. Hull,et al.  Streamline routing through fracture junctions , 1986 .

[25]  D. Bolster,et al.  Localized Point Mixing Rate Potential in Heterogeneous Velocity Fields , 2015, Transport in Porous Media.

[26]  Jeffrey D. Hyman,et al.  Dispersion and Mixing in Three‐Dimensional Discrete Fracture Networks: Nonlinear Interplay Between Structural and Hydraulic Heterogeneity , 2018 .

[27]  J. Thovert,et al.  Effective permeability of fractured porous media with power-law distribution of fracture sizes. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Jeffrey D. Hyman,et al.  Conforming Delaunay Triangulation of Stochastically Generated Three Dimensional Discrete Fracture Networks: A Feature Rejection Algorithm for Meshing Strategy , 2014, SIAM J. Sci. Comput..

[29]  Peter Jackson,et al.  Multi-scale groundwater flow modeling during temperate climate conditions for the safety assessment of the proposed high-level nuclear waste repository site at Forsmark, Sweden , 2014, Hydrogeology Journal.

[30]  Olivier Bour,et al.  Connectivity of random fault networks following a power law fault length distribution , 1997 .

[31]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[32]  S. P. Neuman,et al.  Trends, prospects and challenges in quantifying flow and transport through fractured rocks , 2005 .

[33]  Satish Karra,et al.  Evaluating the effect of internal aperture variability on transport in kilometer scale discrete fracture networks , 2016 .

[34]  Jean-Raynald de Dreuzy,et al.  Hydraulic properties of two‐dimensional random fracture networks following a power law length distribution: 2. Permeability of networks based on lognormal distribution of apertures , 2001 .

[35]  Jesús Carrera,et al.  Multicomponent reactive transport in multicontinuum media , 2009 .

[36]  F. Schwartz,et al.  A comparison of fracture mixing models, 2. Analysis of simulation trials , 1995 .

[37]  Ruben Juanes,et al.  Anomalous transport on regular fracture networks: Impact of conductivity heterogeneity and mixing at fracture intersections. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  J. Gale,et al.  A Laboratory and Numerical Investigation of Solute Transport in Discontinuous Fracture Systems , 1990 .

[39]  Chem. , 2020, Catalysis from A to Z.

[40]  D. Sornette,et al.  Hierarchical geometry of faulting , 1996 .

[41]  Pierre M. Adler,et al.  Solute transport at fracture intersections , 2002 .

[42]  Vladimir Cvetkovic,et al.  Inference of field‐scale fracture transmissivities in crystalline rock using flow log measurements , 2010 .

[43]  Scott L. Painter,et al.  Stochastic simulation of radionuclide migration in discretely fractured rock near the Äspö Hard Rock Laboratory , 2004 .

[44]  H. S. Viswanathan,et al.  Understanding hydraulic fracturing: a multi-scale problem , 2016, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[45]  Satish Karra,et al.  Effect of advective flow in fractures and matrix diffusion on natural gas production , 2015 .

[46]  J. Long,et al.  From field data to fracture network modeling: An example incorporating spatial structure , 1987 .

[47]  G. Marsily,et al.  Modeling fracture flow with a stochastic discrete fracture network: calibration and validation: 1. The flow model , 1990 .

[48]  Mary C. Hill,et al.  Effects of simplifying fracture network representation on inert chemical migration in fracture‐controlled aquifers , 2009 .

[49]  Carl W. Gable,et al.  Pathline tracing on fully unstructured control-volume grids , 2012, Computational Geosciences.

[50]  N. Odling,et al.  Scaling of fracture systems in geological media , 2001 .

[51]  S Pacala,et al.  Stabilization Wedges: Solving the Climate Problem for the Next 50 Years with Current Technologies , 2004, Science.

[52]  Philippe Davy,et al.  On the Frequency-Length Distribution of the San Andreas Fault System , 1993 .

[53]  Daniel R. Lester,et al.  Continuous Time Random Walks for the Evolution of Lagrangian Velocities , 2016, 1608.02208.

[54]  Vladimir Cvetkovic,et al.  Modeling of flow and mixing in 3D rough-walled rock fracture intersections , 2017 .

[55]  Satish Karra,et al.  dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport , 2015, Comput. Geosci..

[56]  Enrico Barbier,et al.  Geothermal energy technology and current status: an overview , 2002 .

[57]  Paul A. Witherspoon,et al.  Flow interference effects at fracture intersections , 1976 .

[58]  Jean-Raynald de Dreuzy,et al.  Transport and intersection mixing in random fracture networks with power law length distributions , 2001 .

[59]  Stephen R. Brown,et al.  Experimental observation of fluid flow channels in a single fracture , 1998 .

[60]  Géraldine Pichot,et al.  Influence of fracture scale heterogeneity on the flow properties of three-dimensional discrete fracture networks (DFN) , 2012 .

[61]  D. Bolster,et al.  Rock dissolution patterns and geochemical shutdown of $\text{CO}_{2}$ –brine–carbonate reactions during convective mixing in porous media , 2015, Journal of Fluid Mechanics.

[62]  Brian Berkowitz,et al.  Mass transfer at fracture intersections: An evaluation of mixing models , 1994 .

[63]  Brian Berkowitz,et al.  Effects of junction transfer characteristics on transport in fracture networks , 2001 .

[64]  P. Davy,et al.  Percolation parameter and percolation-threshold estimates for three-dimensional random ellipses with widely scattered distributions of eccentricity and size , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[65]  P. Alam ‘L’ , 2021, Composites Engineering: An A–Z Guide.

[66]  Noelle E. Odling,et al.  Scaling and connectivity of joint systems in sandstones from western Norway , 1997 .