Accurately predicting the adsorbed gas content in coal reservoirs is crucial for evaluating the gas content in deep coal seams. However, due to the significant variations in temperature and pressure conditions across different coal reservoirs, accurately assessing the adsorbed gas quantity presents challenges. Based on the adsorption potential theory, this paper proposes a prediction model of adsorbed gas that is applicable under various temperature and pressure conditions. The results indicate that the adsorbed gas content in deep coal reservoirs is influenced by a combination of temperature, pressure, and coal rank. The increase in pressure and coal rank enhances the inhibitory effect of temperature on methane adsorption. Meanwhile, there are significant differences in the results obtained from various virtual saturated vapor pressure models. Among them, the Amankwah model theoretically satisfies the uniqueness of the adsorption characteristic curve, with the optimal k values for different coal rank samples ranging between 2 and 9. In terms of predicting the adsorption gas, the performance of the models is ranked as follows: Amankwah model > Antonie model > Astakhov model > Dubinin model > Reid model. The Amankwah model exhibits the smallest average relative error and root mean square error. In addition, as burial depth increases, the influence of the pressure on methane adsorption decreases, while the significance of temperature increases, with the critical depth located around 1600 m. At depths shallower than the critical depth, adsorbed gas tends to preferentially accumulate and form reservoirs, which generally have lower commercial value. At depths deeper than the critical depth, free gas has the potential to form reservoirs. At this stage, gas reservoirs dominated by adsorbed gas start transitioning to those containing free gas. These findings are expected to deepen the understanding of deep coalbed methane and provide a scientific basis for exploration and development in the study area.
