A Cross-Scale Study of Data-Driven Micro-to-Macro Mechanical Heterogeneity in Sandstone

Tight sandstone gas development is largely governed by mineral composition and micromechanical heterogeneity. This study proposes a cross-scale method integrating these two factors to characterize macroscopic sandstone heterogeneity. First, a CNN–Transformer model was trained on thin-section images to identify mineral types and contents. Second, probability density functions of Young’s modulus for each mineral were derived from nanoindentation data, and stochastic sampling was used to assign mechanical properties to mineral grains in an FDEM-GBM uniaxial compression model. Finally, numerical results validated against experiments show that the random spatial distribution of micromechanical parameters leads to a normal distribution of the macroscopic Young’s modulus. Decreasing high-strength mineral content reduces the mean Young’s modulus while increasing its standard deviation, indicating greater mechanical heterogeneity, with cracks preferentially propagating in low-strength minerals. Mineral composition and content are the primary controls on macroscopic behavior, while micromechanical heterogeneity plays a secondary role. A brittleness index integrating mineral composition and multi-scale Young’s modulus distribution is proposed, providing a theoretical basis for evaluating heterogeneity and fracability in tight sandstone reservoirs.