Due to the large non-homogeneity of coal reservoirs, there is a large uncertainty about the extent of the impact on coal bed methane production capacity. The Hanchengbei Block has the problems of early exploration, less available production data, and large variations in developed production capacity within a single well group during test production. Therefore, how to use the existing data to analyze the geological factors affecting the development of coalbed methane in the Hanchengbei Block is particularly important. In this paper, based on the coal seam properties and production characteristics of the Hanchengbei Block, a three-dimensional geological model of the area was meticulously constructed using Petrel 2015 modeling software. Through the utilization of stochastic modeling techniques, reservoir attributes were visualized in three dimensions, and probability distribution functions as well as confidence intervals for different geological parameters were derived through geological statistics. Building upon this foundation, a dual-layer geological model incorporating multiple factors was established using Comet3.0 numerical simulation software. Monte Carlo simulation methods were then employed to simulate the effects of various geological parameters on gas production, yielding corresponding simulation results. Through normalization processes, parameter sensitivity was analyzed to determine the primary controlling factors influencing production capacity. The results show that the thickness of the No. 5 coal seam in the Hanchengbei Block is mainly distributed in the range of 1.35–6.89 m; the gas content is 10.28–15.52 m³/t; and the permeability is 0.014–0.048 mD. Under their joint influence, the average gas production of Hanchengbei Block is between 310–720 m³/d. The main factors affecting the capacity of Hanchengbei Block are the thickness and gas content of the coal seam. This study can provide a basis for the subsequent optimization of favorable areas, the formulation of drainage systems, and the design and optimization of development well networks.