Characterizing Complex Deformation, Damage, and Fracture in Heterogeneous Shale Using 3D-DIC

Safe drilling and effective fracturing are constant challenges for shale formations. One of the most important influencing factors is the accurate characterization of the deformation and damage caused by inherent lamination and natural fractures. Furthermore, shale formations exhibit fine-scale heterogeneity, which conventional laboratory methods (linear variable differential transformer (LVDT), strain gauges, etc.) cannot distinguish. To overcome these constraints, this research aims to investigate the damage and deformation characteristics of shale samples using three-dimensional digital image correlation (3D-DIC). Under uniaxial and diametrical compression, samples of Wolfcamp, Mancos, and Eagle Ford shale with distinct lamination and natural fractures are evaluated. The 3D-DIC system is utilized for image processing, visualization, and analysis of the shale damage process under varying loads. DIC made quantitative full-field strain maps with load (tension, compression, and shear), showing all the damage process steps and strain localization zones (SLZs). DIC maps are used to quantify damage variables in order to investigate sample damage. Damage variables are used to categorize the damage evolution process of shale specimens into four stages: initial damage, linear elastic, elastic–plastic, and plastic damage. Characterizing shale damage evolution with a strain localization line is more effective because there is more damage there than in the whole sample. Damage variables based on major strain and its standard deviation from the DIC strain map for all tested shale samples follow a similar trend, though diametrical compression variables are greater than uniaxial compression. In both uniaxial and diametrical compression, the Wolfcamp shale was reported to have the highest damage variable, which was measured at 0.37, while the Eagle Ford shale was reported to have the lowest damage variable. This image-based technique is more effective not only for understanding the laminated and naturally fractured rocks but also for predicting the hydraulic fractures that will occur during the stimulation process.