## 5 Discussion
### Fractal Dimension and Microscopic Pore-Throat Structure Characteristics  
The fractal dimension provides a quantitative measure of the complexity and heterogeneity of pore structures. By calculating the fractal dimension values from mercury injection data, the relationship between fractal dimension and pore structure parameters is systematically explored. By plotting scatter diagrams of fractal dimension versus pore  
Figure 6: Fractal dimension distribution of micropores, mesopores, and macropores in the study area samples. Figure 7: (**a**) The relationship between fractal dimension and porosity; (**b**) the relationship between fractal dimension and permeability. throat structure parameters, the variation patterns of fractal dimension and the influence of fractal characteristics on pore-throat structure can be determined (Figure 8). The median pore-throat radius can be approximated as the average pore radius of the sample. It shows a certain negative relationship with the fractal dimension (Figure 8a). As the fractal dimension approaches 3, the median pore-throat radius decreases accordingly. The main reason is that as the median pore-throat radius increases, the pore-throat distribution of the reservoir becomes more concentrated, the pore surface becomes more regular, and the storage space increases, which reduces the complexity of the pore structure, weakens the heterogeneity of the reservoir, and improves the physical properties of the reservoir. The sorting coefficient (also known as the coefficient of variation) better reflects the uniformity of the pore-throat size distribution. The sorting coefficient of the reservoir in the study area's Denglouku Formation ranges from 1.108 to 3.966, with an average  
Figure 8: The relationship between fractal dimension and **(a)** Pore-throat radius median; **(b)** Sorting Coefficient; **(c)** Skewness; **(d)** Displacement pressure; **(e)** Maximum mercury injection satu-ration; **(f)** Withdraw efficiency. value of 2.403. The sorting coefficient shows a certain positive relationship with the fractal dimension, where a smaller value indicates a more uniform pore-throat distribution. The large variation range of the sorting coefficient in the study area (Figure 8b) indicates that the pore-throat distribution is highly uneven, reflecting the complexity of the reservoir's pore-throat structure in the study area. The positive and negative values of skewness reflect the skewness of the pore-throat distribution. When the skewness is greater than 0 (positive skew), the pore-throat distribution is biased toward larger pore sizes, and the proportion of larger pore throats is higher. When the skewness is less than 0 (negative skew), the pore-throat distribution is biased toward smaller pore sizes. The skewness in the study area shows a certain degree of negative relationship with the fractal dimension (Figure 8c). As the fractal dimension approaches 3, the skewness gradually shifts from positive to negative, reflecting that, as the heterogeneity of the reservoir increases, the pore-throat structure gradually shifts from micro-small pore throats dominating, which results in poorer flow capacity. The displacement pressure in the study area shows a certain degree of positive relationship with the fractal dimension (Figure 8d). The larger the fractal dimension, the higher the displacement pressure, indicating that as the pore structure becomes more complex, higher displacement pressure is required. The maximum mercury injection saturation reflects the connectivity between pore throats in the tight sandstone reservoir. The relationship between the maximum mercury injection saturation and the fractal dimension shows a certain degree of negativity (Figure 8e). A certain negative relationship is observed between it and the fractal dimension, indicating that lower fractal dimensions correspond to weaker heterogeneity, simpler pore structures, better reservoir connectivity, and improved physical properties.