Anomalous transport in disordered fracture networks: Spatial Markov model for dispersion with variable injection modes

•Injection modes have major impact on anomalous transport in DFNs.•Evolution of the Lagrangian velocity distribution is governed by injection modes.•Spatial velocity Markov model for variable injection modes.•Equivalence between spatial Markov model and Boltzmann equation. We investigate tracer tran...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Advances in water resources 2017-08, Vol.106 (C), p.80-94
Hauptverfasser: Kang, Peter K., Dentz, Marco, Le Borgne, Tanguy, Lee, Seunghak, Juanes, Ruben
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•Injection modes have major impact on anomalous transport in DFNs.•Evolution of the Lagrangian velocity distribution is governed by injection modes.•Spatial velocity Markov model for variable injection modes.•Equivalence between spatial Markov model and Boltzmann equation. We investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that—even if the Eulerian fluid velocity is steady—the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes.
ISSN:0309-1708
1872-9657
DOI:10.1016/j.advwatres.2017.03.024