DFN.lab: software platform for Discrete Fracture Network models. - INSU - Institut national des sciences de l'Univers Access content directly
Conference Poster Year : 2019

DFN.lab: software platform for Discrete Fracture Network models.


DFN.lab is a modular computational suite to deal with three-dimensional discrete fracture networks (DFN) models from DFN generation to simulation and analysis of connectivity, flow, mechanical and transport properties. DFN.lab is developed by the Fractory, a joint laboratory between the French institute for scientific research (CNRS), the university of Rennes and Itasca Consultants s.a.s., to study the behavior of multiscale fractured media for various research topics including safety assessment for long-term nuclear waste storage, geothermal applications, mining, etc. DFN.lab can generate and compute flow and solute or heat transport on large DFNs containing millions of fractures. Core modules are developed in C++ for high performances and a Python API is provided for easy use. The main originality of DFN.lab is in its capacity to deal with multiscale heterogeneities at both the fracture and network scales. For each fracture, the hydraulic properties (transmissivity and aperture) can vary locally either deterministically, or statistically according to correlated random fields. A “sealing” algorithm was developed to model fracture patches that are clogged by mineralization. A graph algorithm was developed to derive the connectivity of open patches at the network scale. At the network scale, thanks to its computing capacities, DFN.lab can deal with fracture sizes ranging over more than 3 orders of magnitude. Another originality of DFN.lab is in its DFN generation modules, where genetic generation models [Davy et al., 2013; Davy et al., 2010] have been developed as an alternative to the classical Poisson (e.g., randomly distributed) models bootstrapped on statistical descriptions of the fracture properties (size, position, orientation). For the same distribution of fracture sizes, orientations and transmissivities, genetic models behave significantly differently from Poisson’s models [Maillot et al., 2016]. Example applications of this suite for nuclear waste repository, solute transport and heat transport will be presented. Davy, P., R. Le Goc, and C. Darcel (2013), JGR, 118(4), 1393-1407. Davy, P., R. Le Goc, C. Darcel, O. Bour, J. R. de Dreuzy, and R. Munier (2010), JGR, 115(B10). Maillot, J., P. Davy, R. Le Goc, C. Darcel, and J.-R. De Dreuzy (2016), WRR, 52(11).


Fichier principal
Vignette du fichier
LeGocetal.DFN.lab-print.pdf (1.78 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

insu-02402555 , version 1 (14-09-2021)


  • HAL Id : insu-02402555 , version 1


Romain Le Goc, Benoît Pinier, Caroline Darcel, Etienne Lavoine, Diane Doolaeghe, et al.. DFN.lab: software platform for Discrete Fracture Network models.. American Geophysical Union Fall Meeting 2019, Dec 2019, San Francisco, United States. , pp.H41H-1778, 2019. ⟨insu-02402555⟩
332 View
76 Download


Gmail Facebook X LinkedIn More