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Modelling fluid flow and water-rock interaction in fractured crust using a Discrete Fracture Network approach Groundwater accounts for around 25% of the world’s fresh water supply. Due to the increasing anthropogenic pressure on shallow aquifers as well as climate change that is impacting global groundwater recharge, there is an increasing need to access deeper groundwater resources, which are frequently hosted in fractured-rock formations. The migration of groundwater (and other types of fluids, in general) in fractured rocks allows the contact between fluids in geochemical disequilibrium with the host rocks (i.e., large geochemical gradients) promoting water-rock reactions inside the fractures. These reactions may influence the permeability and porosity, as well as they may lead to fracture sealing. So, a thorough understanding of the coupled hydro-chemical processing that occur in fractured media is important for applications such as the sustainable exploitation of the afore-mentioned reserves, the protection and remediations of aquifers used for drinking water production or the safety analyses of deep geological repositories for spent nuclear fuel. In fractured rocks, groundwater flows in specific pathways and interacts with the host rock which may lead to the change in the hydro-geochemical conditions. The prediction of these interactions become critical for a proper management of the different applications. Therefore, the understanding and modelling of fluid-fracture interaction is of high scientific and commercial interest. Using the software dfnWorks, it is possible to model the fluid transport using a non-reactive Lagrangian method (particle tracking). In this contribution, we intend to implement geochemical reactions in dfnWorks to quantify the impact of these reactions in the fracture network. In fact, flow of water through Discrete Fracture Networks leads to interaction between water and the minerals occurring in the fracture plane and thus alters the underlying groundwater flow patterns. Thus, using these DFN-based reactive transport simulations, we aim at predicting the effect that chemical reactions have on flow and channeling. Besides presenting a proof-of-concept set of calculations, we will also present preliminary results of a real-case application, where fracture filling is produced as a result of a chemical imbalance.

International audience; 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.

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International audience; In fractured media, fluid flow depends on and induces coupled processes (hydrogeological-mechanical-chemical-biological-thermal) across a wide range of time and length scales. Understanding fluid flow and its coupling with different processes is critical for numerous subsurface applications including petroleum and geothermal reservoir management, environmental remediation, carbon sequestration, and long-term radioactive waste isolation. This session focuses on recent research that provides mechanistic understanding and predictive capability of physical processes in fractured media including coupled flow and geomechanics, non-Fickian transport, colloid and bacterial transport, mixing and reaction, fluid/mineral interactions, and biofilm formation. In particular, we encourage submissions related to (1) experiments and field observations, (2) new theoretical and numerical modeling approaches (direct simulation in single fractures, discrete fracture network modeling, upscaling methodologies, and multi-scale methods), and (3) the integration of data and models for observational interpretation and model validation..