Abstract
The displacement mechanisms of adsorbed CH4 by injected CO2 at high pressures in CO2-enhanced coalbed methane (CO2-ECBM) processes involve competitive adsorption, diffusion, and dispersion. Inherent coal heterogeneity and the complexity of the CO2-CH4 displacement model make CO2-ECBM modelling and optimal process design challenging. The pure gas isotherms and Langmuir adsorptions constants for CO2 and CH4 were determined using the manometric method. Notably, CO2 shows higher adsorption capacity than methane, and Langmuir volume (VL) for CO2 is 2 to 2.3 times that of methane. High pressure adsorption isotherms and experimentally determined diffusion coefficients set the sorption kinetics. The diffusion coefficient of CH4 for all four samples was in the range between 1.35×10-12 and 7.42×10-12 m2/s, while for CO2, it varied from 10.9×10-12 to 15.48×10-12 m2/s. The new concept of caucus time was introduced in the sorption kinetics of CO2 and CH4. Each sample has distinct caucus time and was positively correlated with Langmuir volumes of CO2 and CH4 with R2 > 0.9. The critical desorption pressure above which CH4 exhibits retrograde adsorption behaviour is evaluated from co-adsorption isotherms adopting Ideal Adsorption Solution Theory (IAST). The critical desorption pressure for the four samples were 1220, 460, 575 and 740 psi respectively. IAST also predicts a critical mole fraction (∼30 %) in the gas phase above which CO2 becomes the dominant adsorbed phase on coal surfaces. The results of Advective-Dispersion modelling at a larger scale illustrate the value of the Dispersion coefficient in forecasting and screening. Since the time available for diffusion versus dispersion depends upon flowrate, high values of dispersion coefficient can negatively influence favourable competitive adsorption expectations through higher operational cost in CO2 separation. This work suggests the existence of both an optimal operational pressure and flowrate to maximize the potential of CO2-ECBM technology demonstrated in competitive adsorption modelling.
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