Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/198403
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Characterizing the Influence of Fracture Density on Network Scale Transport |
Autor: | Sherman, Thomas; Hyman, Jeffrey; Dentz, Marco CSIC ORCID ; Bolster, Diogo | Palabras clave: | CTRW DFN Transport Fracture networks |
Fecha de publicación: | 21-dic-2019 | Editor: | American Geophysical Union | Citación: | Journal of Geophysical Research - Part B - Solid Earth | Resumen: | The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow‐velocity regions. These large tortuosity, slow‐velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems. | Versión del editor: | https://doi.org/10.1029/2019JB018547 | URI: | http://hdl.handle.net/10261/198403 | DOI: | 10.1029/2019JB018547 |
Aparece en las colecciones: | (IDAEA) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
Characterizing the Influence of Fracture Density on Network Scale Transport.pdf | Artículo principal | 6,43 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
19
checked on 12-abr-2024
WEB OF SCIENCETM
Citations
19
checked on 27-feb-2024
Page view(s)
190
checked on 19-abr-2024
Download(s)
351
checked on 19-abr-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.