About the lab

Created in 2018, the Fractory is a joint laboratory between ITASCA Consultants SAS, the CNRS, and the university of Rennes, dedicated to the modeling of environmental systems for risk assessment and improvement of geological resource management methods. Our story relies on a long-term collaboration on various research programs for several industries, including radioactive waste management. Today, our team of engineers, researchers, and students, develop new methodologies and numerical solutions to solve several environmental issues of which:
- Water management in crystalline rocks
- Flooding risks
- Erosion and sediment transport
- Restoration of natural aquatic environments

Featured projects (2)

Project
ENIGMA is an Innovative Training Network funded by the European Commission (https://enigma-itn.eu/). The ENIGMA ITN ( European training Network for in situ imaGing of dynaMic processes in heterogeneous subsurfAce environments) aims at training a new generation of young researchers in the development of innovative methods for imaging process dynamics in subsurface hydrosystems, in order to enhance understanding and predictive modelling capacities and to transfer these innovations to the economic sector. The 15 young future PhD students will contribute to develop the spatial representation of subsurface heterogeneity, fluxes, chemical reactions and microbial activity, through the integration of data and approaches from geophysics, hydrology, soil physics, and biochemistry. The network ENIGMA gather 21 partners (15 academic and 6 industrial) from 8 European countries. Each of the 15 future PhD students will conduct the research work in 2 or 3 institutions, in collaboration with the industrial partners.
Project
A common platform to assemble various efforts to address to elusive essence of fracturing in rock, focussing on Dicrete Fracture Modelling (DFN)

Featured research (34)

Modeling heat transfer in complex heterogeneous fractured system is key for geothermal energy applications. Discrete fracture network (DFN) modeling is the classical framework to reproduce the advective part of the transport, which is determined by the fracture connectivity and heterogeneity. This approach in general sacrifices the representation of the rock matrix, disregarding both its diffusive heat exchange with the fractures and the effects of its thermo-mechanical deformation on the fracture aperture. Here we propose a new semi-analytic formulation that can be implemented in a DFN simulator with particle tracking approach. The contribution of the rock matrix in terms of diffusive heat exchange and thermal contraction/expansion is analytically evaluated, which respectively impact the advective heat transfer and the fracture aperture variation. The method is proved to be accurate and robust. Results from simulations of cold fluid injection show that rock contraction affects the transmissivity, which accelerates the advective transport resulting in a faster recovery of cold fluid at the outlet. The methodology enables investigating the reservoir behavior and optimizing the geothermal performance while keeping the computational effort within reasonable values. This allows exploring the uncertainty in cases when the in-situ characterization is poor, which is the spirit of the DFN modeling.
Modeling heat transfer in complex heterogeneous fractured system is key for geothermal energy applications. Discrete fracture network (DFN) modeling is the ideal framework to reproduce the advective part of the transport, which is determined by the fracture connectivity and heterogeneity. This approach in general sacrifices the representation of the rock matrix, disregarding both its diffusive heat exchange with the fractures and the effects of its thermo-mechanical deformation on the fracture aperture. Here we propose a new semi-analytic formulation that can be implemented in a DFN simulator with particle tracking approach. The contribution of the rock matrix in terms of diffusive heat exchange and thermal contraction/expansion is analytically evaluated, which respectively impact the advective heat transfer and the fracture aperture variation. The methodology enables investigating the reservoir behavior and optimizing the geothermal performance while keeping the computational effort within reasonable values. This allows exploring the uncertainty in cases when the characterization is poor, which is the spirit of the DFN modeling.
The United States and countries around the world face an increasing demand for energy at the same time that carbon emissions and other environmental issues are facing greater scrutiny. Geothermal energy, generating electricity using the temperature difference between the surface and the sub-surface, is an active topic of research by the US Department of Energy and other agencies around the world. Much of the existing geothermal power generation is based on existing natural hydrothermal system. These hydrothermal schemes rely on abnormally high heat flow and an existing ground water system. The concept of enhanced geothermal systems (EGS) allows geothermal energy to be produced in nearly any land location. EGS reservoirs are often below 3 km in depth and rely on some engineered permeability enhancement to be economical. This paper describes a numerical modeling capability to help better understand the interactive thermal, hydrological, and mechanical effects that control the behavior of an EGS system. A 3D discrete fracture network is explicitly represented and a combination of specialized meshing and explicit solution techniques is used make predictions of the stimulation and production of EGS reservoirs. A comparison is made between a fully-coupled model using the 3DEC software and a complimentary approach using the DFN.lab software.
evaluate the use of graphs as a fast and relevant substitute to DFNs. Graphs reduce the DFNs’ complexity to their connectivity structure by forming an assembly of nodes connected by edges, to which physical properties, like a conductance, can be assigned. Both the graph architecture (either fracture- or intersection- based) and the edge conductance definition, have an impact on the estimation of flow and transport parameters. The intersection graph brings a reliable description of the flow connectivity but with edge redundancy in fractures with a large number of intersections. As a consequence, the expression of the edge conductances should depend on the number of intersections in the fracture plane. We first introduce some of our previous work which propose a reliable expression of the edge conductance in the case of a pair of intersections. For the intersection graph, a correction on the conductance expression is proposed for fractures with a large number of intersections. Both graphs provide very good estimate of the bulk permeability although they tend to slightly overestimate it when the DFN connectivity increases (~×2) certainly due to fractures with large intersection numbers. We address this issue by analyzing flow simulations on a fracture with multiple intersections. We also propose another way to correct the intersection graph, which consists in removing redundant edges. The method drastically simplifies the intersection graph, which is promising in term of computational time. The bulk permeability is overestimated by a factor of 2.3 but independently of the DFN density and connectivity.

Lab head

Philippe Davy
Department
  • UMR CNRS 6118 - Géosciences Rennes

Members (7)

Romain Le Goc
  • Itasca Consultants SAS
Silvia De Simone
  • French National Centre for Scientific Research
Diane Doolaeghe
  • Université de Rennes 1
Benoît Pinier
  • Université de Rennes 1
Etienne Lavoine
  • Itasca Consultants SAS
Quentin Courtois
  • Université de Rennes 1

Alumni (1)

Justine Molron
  • Université de Rennes 1