Abstract: To establish a refined geological model, thereby achieving geological transparency and scientifically planning mining operations, research is conducted on constructing a coal seam model using optimized Kriging interpolation, revealing the distribution and calorific value differences in coal thickness. Firstly, a dataset simulating coal seam geological conditions is created by generating a two-dimensional regionalized variable random field with both regularity and randomness based on the principle of regionalized variable, and the data quality for validating interpolation methods is enhanced by characterizing different geological conditions through their variability coefficients. Secondly, an Ant Colony Optimization-Particle Swarm Optimization （ACO-PSO） algorithm is introduced to optimize the ordinary Kriging method, overcoming the impact of spatial variability on interpolation methods and improving accuracy and robustness of the method. Thirdly, an error comparison is conducted between ordinary Kriging and the optimized interpolation methods using both the regionalized random variable dataset and the actual measured coal thickness and calorific values from exploratory boreholes in the No.10 coal seam at the Yangliu Coal Mine in Huaibei. Finally, using the optimized method, a block model is constructed, and a model of the No.10 coal seam is built by integrating constraints such as wellfield boundaries, working face boundaries, and roadway information. Error comparison experiments show that among the four classes of regionalized variable datasets with increasing variability, the root mean square error of the optimized method decreased by 35.4%, 18.4%, 20.4%, and 15.8%, respectively. Similarly, lower errors are observed in the internal extrapolation comparison based on the coal thickness and calorific values measured from 254 coal-exposing boreholes in the No.10 seam. This paper demonstrates that the optimized Kriging interpolation method provides better performance and a broader application scenario in the construction of coal seam model.