The adsorption of CO₂ and CO₂/CH₄ mixtures on kaolinite was calculated by grand canonical Monte Carlo (GCMC) simulations with different temperatures (283.15, 293.15, and 313.15 K) up to 40 MPa. The simulation results show that the adsorption amount of CO₂ followed the Langmuir model and decreased with an increasing temperature. The excess adsorption of CO₂ increased with an increasing pressure until the pressure reached 3 MPa and then decreased at different temperatures. The $S_{C{O}_2/C{H}_4}$ decreased logarithmically with increasing pressure, and the $S_{C{O}_2/C{H}_4}$ was lower with a higher temperature at the same pressure. The interaction energy between CO₂ and kaolinite was much higher than that between CH₄ and kaolinite at the same pressure. The interaction energy between the adsorbent and adsorbate was dominant, and that between CO₂ and CO₂ and between CH₄ and CH₄ accounted for less than 20% of the total interaction energy. The isothermal adsorption heat of CO₂ was higher than that of CH₄, indicating that the affinity of kaolinite to CO₂ was higher than that of CH₄. The strong adsorption sites of carbon dioxide on kaolinite were hydrogen, oxygen, and silicon atoms, respectively. CO₂ was not only physically adsorbed on kaolinite, but also exhibited chemical adsorption. In gas-bearing reservoirs, a CO₂ injection to displace CH₄ and enhance CO₂ sequestration and enhanced gas recovery (CS-EGR) should be implemented at a low temperature.

The uncertainty and complexity of the geological parameters of coalbed methane (CBM) reservoirs may result in the assignment of atypical exact values to a whole block. Therefore, the influence of different resources and productivity characterization indices on the development of CBM blocks was analyzed systematically in this research. Furthermore, this research reported an interval-number index evaluation system and a gray relational analysis optimization model for CBM development. The weights of the evaluation indices were determined by combining the entropy method and the best worst method (BWM) with the objective deviation law of the data and the subjective experience of experts. Based on the gray system theory, a multi-index gray relational analysis optimization model was established to evaluate the interval values and optimize the development potential of CBM blocks with complex geological conditions. The results show that the order of importance of the eight resources and reservoir evaluation indices, from highest to lowest, is permeability, reservoir pressure gradient, gas content, reservoir thickness, reservoir depth, critical reservoir ratio, Young’s modulus, and reservoir temperature. The order of the target blocks, from most to least optimal, is the Sanjiao block, Fanzhuang-Zhengzhuang block, Daning-Jixian block, Gujiao block, and Fengrun block. The evaluation results are consistent with actual conditions. Thus, the multi-index gray relation analysis optimization model, on account of the gray system theory, is feasible for the development evaluation of CBM blocks under complex conditions. This model is suitable for the CBM blocks in the range of 547 km²~675 km². When using this model, the index values must be representative and accurate.