多组分气体吸附预测及模型对比研究

Prediction for adsorption of multi-component gas of coals and comparative study of different adsorption models

为了更精确描述煤层气注气开发或二氧化碳煤层封存涉及到的多组分吸附过程,采用扩展Langmuir、理想吸附溶剂和二维状态方程预测不同煤对甲烷–二氧化碳混合气体的吸附,并将三种模型预测结果与实验数据进行对比分析,结果表明:二维状态方程模型对混合气体的吸附预测精度最高,并且能较好适用于高压系统的吸附预测。除此之外,从三种模型分离因子的变化规律可以看出,理想吸附溶剂和二维状态方程模型在吸附时都考虑了气体相对吸附性随平衡气相组分和压力的变化,而扩展Langmuir没有考虑该因素。因此,也表明理想吸附溶剂和二维状态方程模型在预测多组分气体相对吸附方面具有一定的优势。

To accurately describe the process of multi-component gas adsorption that is related to the studies of enhanced coalbed methane(ECBM) or carbon dioxide coal sequestration, we use respectively the extended Langmuir equation, ideal adsorbed solution(IAS) model and the two dimensional equation of state(2D EOS) to predict the adsorption of methane-carbon dioxide mixed gas on coal and activated carbon. Then, we compare the results predicted with the previous experimental data from literature. It is demonstrated that 2D EOS model can achieve the highest prediction accuracy and be more suitable to predict the multi-component gas adsorption in high pressure system. In addition, from the trends of separation factor for three models, we have known that both the IAS and 2D EOS models can take the changes of gas relative adsorption to equilibrium gas components and pressure into consideration, but extended Langmuir does not consider the factor. So IAS and 2D EOS models have the greater advantage that can better predict the gas relative adsorption over extended Langmuir.