This study numerically investigates contact forces and the contact network in unconfined and confined compression tests on rock-like bonded granular materials using the particle-based discrete element method (DEM). Statistical analysis of contact force magnitudes and polar distributions under varying confining pressures reveals a significant influence of confining pressure on force evolution. Additionally, contact force distribution is closely related to internal structures and external loads. The relationship between contact force and geometrical features of the contact network is analyzed, along with the three-stage evolution of the relationship between force anisotropy and stress ratio, driven by contact network changes. Tensile force chain lengths follow an exponential distribution. Without confinement, tensile force chains remain stable until crack formation, whereas under confinement, they increase in number and length before decreasing due to the occurrence of cracks. Higher confinement results in shorter, fewer tensile force chains. Finally, the number, orientation and force magnitude of new tensile contacts are analyzed to further elucidate tensile contact evolution in bonded granular materials.

Although supercritical CO₂ (SC-CO₂) fracturing has shown promise in oil and gas development with demonstrated potential, its application in shale gas extraction remains in its infancy globally. In this study, fracturing experiments were conducted with water, liquid CO₂ (L-CO₂), and SC-CO₂, as well as SC-CO₂ at varying pump rates. The results reveal that SC-CO₂ fracturing produces a highly complex fracture network characterized by fractures of varying numbers, deflection angles, and tortuosity. Analysis of CO₂ temperature and pressure data showed a sharp drop in injection pressure and temperature at breakdown, followed by fluctuations until injection stopped. Acoustic emission (AE) monitoring demonstrated that energy released during main fracture initiation significantly exceeded that from CO₂ phase transition-driven fracture extension, underscoring the dominant role of main fractures in energy dissipation. Compared to hydraulic fracturing, SC-CO₂ fracturing created a seepage area 2.2 times larger while reducing the breakdown pressure by 37.2%, indicating superior stimulation performance. These findings emphasize the potential of SC-CO₂ to form intricate fracture networks, offering a promising approach for efficient shale gas extraction.

Hydraulic fracturing is a widely employed technique for stimulating unconventional shale gas reservoirs. Supercritical CO₂ (SC-CO₂) has emerged as a promising fracturing fluid due to its unique physicochemical properties. Existing theoretical models for calculating breakdown pressure often fail to accurately predict the outcomes of SC-CO₂ fracturing due to the complex, nonlinear interactions among multiple influencing factors. In this study, we conducted fracturing experiments considering parameters such as fluid type, flow rate, temperature, and confining pressure. A fully connected neural network was then employed to predict breakdown pressure, integrating both our experimental data and published datasets. This approach facilitated the identification of key influencing factors and allowed us to quantify their relative importance. The results demonstrate that SC-CO₂ significantly reduces breakdown pressure compared to traditional water-based fluids. Additionally, breakdown pressure increases with higher confining pressures and elevated flow rates, while it decreases with increasing temperatures. The multi-layer neural network achieved high predictive accuracy, with R, RMSE, and MAE values of 0.9482 (0.9123), 3.424 (4.421), and 2.283 (3.188) for training (testing) sets, respectively. Sensitivity analysis identified fracturing fluid type and tensile strength as the most influential factors, contributing 28.31% and 21.39%, respectively, followed by flow rate at 12.34%. Our findings provide valuable insights into the optimization of fracturing parameters, offering a promising approach to better predict breakdown pressure in SC-CO₂ fracturing operations.