Study on separation of CO2 condensation from natural gas based on cellular automaton method

Abstract

ABSTRACT The CO2-containing natural gas is increasing, and there is an urgent need for green treatment of natural gas containing CO2 to realize the utilization of natural gas. Conventional natural gas decarbonization methods have drawbacks such as non-environmental friendliness, and the low-temperature condensation separation of carbon dioxide (snowing-separation) method as a green method of carbon capture is proposed in this paper. Aiming at the characteristics of CO2 condensation in the snowing-separation process, the growth process of CO2 crystals is obtained by simulation using the CA (Cellular Automata) method and finds that the effect of supersaturation on the growth of CO2 crystals is exponential. The snowing-separation process at .5 MPa is analyzed, and it is found that the condensation range is 158.51 K–173.86 K, the upper limit of CO2 mole fraction in natural gas is 10.1%, and the minimum separation time is 8.65 × 10−8s. Analyzing the influencing factors of CO2 separation efficiency, combining the simulation results with the experimental results, the maximum relative error is 13.93%, which can better predict the snowing-separation technology of CO2 in natural gas, and then promote the development of efficient low-temperature carbon capture process.