A numerical study on the thermo-mechanical response of deformable fractured systems to advective-diffusive heat transport

Geothermal energy applications involve heat circulation in naturally fractured reservoirs, which are in general difficult to characterize due to the multiscale complexity of the fracture network and therefore the flow. In this context, numerical modeling is key to forecast the performance of geothermal energy applications under a number of scenarios. Numerical modeling is challenging because fractures represent the main pathway for flow and advective transport, but diffusive thermal exchange with the host rock controls the geothermal performance - the two processes occurring on very different length and time scales. Moreover, the host rock cooling provokes thermal contraction which tends to increase the fracture aperture, with direct effects on the flow and the advective transport. Quantify these processes is crucial but in general computational demanding when dealing with large reservoirs with hundreds of thousands of fractures.

In this study we present a novel methodology to simulate thermo-mechanical (TM) heat transport. The method is based on the particle tracking approach in Discrete Fracture Networks (DFN) and it has been implemented in the DFN.Lab software platform. The contribution of the host rock matrix in terms of diffusive heat exchange and thermal contraction/expansion is analytically evaluated, which directly impacts the fracture aperture and therefore the advective heat transfer. The methodology enables investigating the reservoir behavior and optimizing the geothermal performance while keeping the computational effort within reasonable values. Results from simulations of cold fluid injection show that rock contraction accelerates the advective transport resulting in a faster recovery of cold fluid at the outlet. We analyze systems of fractures with different characteristics (density, aperture, geometrical patterns, ...) and we identify the parameters that mostly impact the TM response.