Proppant transport within fractures is one of the most critical tasks in oil, gas and geothermal reservoir stimulation, as it largely determines the ultimate performance of the operating well. Proppant transport in rough fracture networks is still a relatively new area of research and the associated transport mechanisms are still unclear. In this study, representative parameters of rough fracture surfaces formed by supercritical CO₂ fracturing were used to generate a rough fracture network model based on a spectral synthesis method. Computational fluid dynamics (CFD) coupled with the discrete element method (DEM) was used to study proppant transport in this rough fracture network. To reveal the turning transport mechanism of proppants into branching fractures at the intersections of rough fracture networks, a comparison was made with the behavior within smooth fracture networks, and the effect of key pumping parameters on the proppant placement in a secondary fracture was analyzed. The results show that the transport behavior of proppant in rough fracture networks is very different from that of the one in the smooth fracture networks. The turning transport mechanisms of proppant into secondary fractures in rough fracture networks are gravity-driven sliding, high velocity fluid suspension, and fracture structure induction. Under the same injection conditions, supercritical CO₂ with high flow Reynolds number still has a weaker ability to transport proppant into secondary fractures than water. Thickening of the supercritical CO₂ needs to be increased beyond a certain value to have a significant effect on proppant carrying, and under the temperature and pressure conditions of this paper, it needs to be increased more than 20 times (about 0.94 mPa s). Increasing the injection velocity and decreasing the proppant concentration facilitates the entry of proppant into the branching fractures, which in turn results in a larger stimulated reservoir volume. The results help to understand the proppant transport and placement process in rough fracture networks formed by reservoir stimulation, and provide a theoretical reference for the optimization of proppant pumping parameters in hydraulic fracturing.

Figuring out rock strength plays essential roles in the sub ground mining activities, such as oil and gas well drilling and hydraulic fracturing, coal mining, tunneling, and other civil engineering scenarios. To help understand the effects of the mineralogical composition on evaluating the rock strength, this research tries to establish indirect prediction models of rock strength by specific input mineral contents for common sedimentary rocks. Using rock samples collected from the outcrops in the Sichuan Basin, uniaxial compression tests have been conducted to sandstone, carbonate, and shale cores. Combining with statistical analysis, the experimental data prove it true that the mineralogical composition can be utilized to predict the rock strength under specific conditions but the effects of mineralogical composition on the rock strength highly depend on the rock lithologies. According to the statistical analysis results, the predicted values of rock strengths by the mineral contents can get high accuracies in sandstone and carbonate rocks while no evidences can be found in shale rocks. The best indicator for predicting rock strength should be the quartz content for the sandstone rocks and the dolomite content for the carbonate rocks. Especially, to improve the evaluation accuracy, the rock strengths of sandstones can be obtained by substituting the mineral contents of quartz and clays, and those of carbonates can be calculated by the mineral contents of dolomite and calcite. Noticeably, the research data point out a significant contrast of quartz content in evaluating the rock strength of the sandstone rocks and the carbonate rocks. Increasing quartz content helps increase the sandstone strength but decrease the carbonate strength. As for shale rocks, no relationship exists between the rock strength and the mineralogical composition (e.g., the clay fractions). To provide more evidences, detailed discussion also provides the readers more glances into the framework of the rock matrix, which can be further studied in the future. These findings can help understand the effects of mineralogical composition on the rock strengths, explain the contrasts in the rock strength of the responses to the same mineral content (e.g., the quartz content), and provide another indirect method for evaluating the rock strength of common sedimentary rocks.