Complex Fluids in Fractured Geological Media for Enhanced Heat Transfer

Abstract

Modeling complex fluid flow and heat transport through fracture networks in low-permeable rocks is fundamental for energy-related applications such as enhanced geothermal systems, which represent a promising clean and renewable energy supply. In this context, the main goal of the project is to characterize the joint effect of complex fluid rheology and medium heterogeneity on heat transport at the scale of the fracture network; this effect has never been investigated and is important to increase the knowledge of coupled flow and heat transport in fractured reservoirs by characterizing the main features that interest industrial applications. While in geological formations the flow is governed by fractures’ transmissivity and connectivity, convection and conduction dominate heat transport in fractures and rock matrix, respectively. In addition, given the complex microstructure of fluids involved in subsurface operations, which typically yields mechanical properties described by a non-linear constitutive law at a continuum scale, it is critical to overcome the adoption of Newtonian rheology, still predominant in the literature, to consider the shear-thinning nature of the most frequently used in reservoir simulation. The project is inspired by previous studies on single fractures, where we characterized how fluid shear-thinning behavior promotes flow localization and strongly affects fracture transmissivity, with inevitable effects on the larger network scale. Relying on these findings a mixed approach using both 2-D lubrication-based and 3-D CFD simulations is proposed here to model coupled shear-thinning flow and heat transport in single fractures. The results on these main components of fracture networks will feed the upscaling scheme, which will be performed by using Machine Learning techniques, thus introducing another element of novelty in this field. Laboratory experiments on single fracture and discrete fracture network simulations are also proposed to validate model results at different scales. To summarize, our research goal is to study the influence of fracture-scale and network-scale heterogeneity on heat transport under shear-thinning flow in a stochastic framework. The analytical, experimental, and numerical expertise developed during the PhD and focused on modeling fracture scale flow heterogeneity for complex fluids within a stochastic framework represents the solid background required for the development of projects on coupled processes in the fracture networks. At the same time, new meta-modeling based on machine-learning techniques for the upscaling will be undertaken at the host institution, while laboratory experiments will be conducted for model validation during the secondment. The scientific outcomes are expected to bring significant progress in modeling deep geothermal operations and the use of engineered fluids in the subsurface.

Team di ricerca UNIBO

Alessandro Lenci; Vittorio Di Federico

Partner di progetto

Stanford University; Universitè de Rennes 1