The study of the mechanical properties of moderately consolidated sandstones is crucial for engineering safety assessments. As an effective research tool, the discrete element method (DEM) encounters challenges during the modeling phase, such as a large number of micromechanical parameters, low modeling efficiency, and unclear coupling mechanisms among multiple parameters. To address these issues, this paper proposes a calibration method for the micromechanical parameters of DEM models for moderately consolidated sandstones. By integrating orthogonal experimental design with a multivariate analysis of variance, the influence of micromechanical parameters on macroscopic mechanical properties is quantified, and a parameter prediction model is constructed using an intelligent dynamic regression selection mechanism, significantly improving the efficiency and accuracy of micromechanical parameter calibration. The results show that the macroscopic elastic modulus E is primarily controlled by the effective modulus ($\overline{E}$), stiffness ratio (k), and particle size ratio (R_max/R_min), following a linear relationship. The influence of the particle size ratio decreases significantly once it exceeds a threshold value. The macroscopic uniaxial compressive strength (UCS) is dominated by cohesion ($\overline{c}$) and tensile strength (${\overline{\mathrm{\sigma }}}_c$), exhibiting a polynomial relationship, where a stronger synergistic effect is generated when both parameters are at higher levels. Poisson’s ratio ($\mu$) is significantly correlated only with the stiffness ratio (k), following a logarithmic relationship. An iterative correction method for micromechanical parameter calibration is proposed. The errors between the three groups of simulation results and laboratory test results are all less than 10%, and the crack distribution patterns show a high degree of consistency. The findings of this study provide a theoretical foundation and technical means for exploring the mechanical behavior and damage mechanism of moderately consolidated sandstones.

Depleted oil and gas reservoirs, owing to their large storage capacity and well-established infrastructure, are attractive sites for storing green energy carriers such as natural gas, hydrogen, and compressed air. During injection–production cycling in underground gas storage (UGS), variations in effective stress can cause repeated stress disturbances in the reservoir and surrounding rock, which may trigger borehole sand production. In this study, laboratory sand-production simulation tests were conducted to evaluate the effects of cyclic-loading stage, upper stress limit, and cycling frequency on borehole damage and sand-production behavior. The results show that sand production is stage-dependent. During the rapid-hardening and stable stages, the borehole remains largely intact and sand production is negligible. Once the failure and collapse stages are reached, borehole integrity deteriorates and sand production increases sharply, with fine particles becoming dominant. Cumulative sand production increases with the upper stress limit. Increasing the upper limit from 80% to 95% leads to a 2.53-fold increase in produced sand mass, together with a higher fine-sand fraction and a shift in the particle-size distribution (PSD) toward smaller sizes. The cycling frequency also plays an important role. When the frequency decreases, cumulative sand production increases and becomes 53.1% higher than the baseline at 0.001 Hz. Meanwhile, the median particle size (D50) decreases, indicating stronger particle breakage under low-frequency cycling. These findings provide guidance for designing injection–production schemes for UGS and for selecting appropriate sand-control completion strategies.