Author(s): Sunghyun Kim
Mentor(s): Shahrzad Roshankhah
Institution U of U
The interaction between hydraulic fractures (HF) and natural fractures (NF) during fluid injection is a crucial factor influencing the evolution of fracture networks in naturally fractured rock formations. This interaction directly impacts the efficiency of geological resource extraction by determining the complexity and connectivity of the resulting fracture network. Traditional hydraulic fracturing models, however, are often based on assumptions of homogeneity, isotropy, linear elasticity, and impermeability, which limit their ability to accurately predict fracture behavior in real-world heterogeneous, anisotropic, and permeable rock formations. Consequently, these models fall short when applied to complex subsurface environments where natural fractures play a significant role. To address these limitations, this study employs two-dimensional digital image correlation (2D-DIC) as a novel method to quantitatively assess HF-NF interactions in a controlled laboratory setting. The 2D-DIC technique enables high-resolution, full-field displacement and strain measurements, capturing fracture propagation paths in synthetic rock specimens that include pre-existing fractures. By analyzing images taken before and after fluid-induced fractures, 2D-DIC provides precise insights into how fracture networks evolve under stress conditions similar to those found in the subsurface. This method is particularly effective in characterizing HF-NF interactions with various orientations, spacings, apertures, and bonding strengths, allowing for a detailed understanding of how these factors influence fracture behavior. The results of this study advance the understanding of fracture network dynamics in complex geological formations. This improved knowledge supports the development of predictive models that more accurately reflect real-world fracture behavior, leading to optimized hydraulic fracturing strategies that enhance resource recovery efficiency while minimizing environmental impact. Insights gained from 2D-DIC analyses thus contribute to more sustainable energy extraction practices and better management of environmental resources across diverse geosystems.