The high affinity and adsorption capacity of coal to carbon dioxide provides an alternative approach for the enhanced recovery of methane from unminable coalfields (CO2-ECBM) by which a potential solution for long-term CO2 sequestration in deep geological formations can also be achieved. However, due to chemomechanical effects induced by the interactions between CO2 and coal, the effective methane production and carbon dioxide storage can be degraded which has caused uncertainties about the techno-economic feasibility of the CO2-ECBM process. This study presents an experimental investigation that aims to address key knowledge gaps related to the efficiency of CO2 storage and CH4 recovery in high rank coals for which a comprehensive experimental data set and analysis are largely missing. Competitive displacements of CH4 with N2 or CO2 in an anthracite coal sample from a South Wales coalfield have been studies, based on a series of core flooding experiments. The results show that the N2 breakthrough time (the time at which 1% of the total gas injected was recovered) was almost spontaneous whereas a considerably delayed breakthrough time was observed for the case of the CO2-ECBM experiment. In addition it was observed that for the CO2-ECBM experiment, the ratios of CH4 recovery with respect to the total amount of gas injected and gas stored were higher by factors of 10 and 2.4, respectively. The results also show that 90% of the total N2 injected was produced in the outflow gas, whereas for the case of the CO2 experiment, only 63% of the total injected CO2 was produced. The presence of a high amount of N2 in the outflow may lead to additional challenges in order to separate N2 from CH4 and thus affect the efficiency of the N2-ECBM method. Under the conditions of the experiments, the total CH4 displacement ratio and breakthrough for the case CO2-ECBM were found to be more favorable compared to those obtained from N2-ECBM. This study provides new insights into the efficiency of the CO2-ECBM process and offers a comprehensive experimental data set that can be used for testing the accuracy of predictive models.