Underground coal gasification (UCG) is an emerging energy technology for a cleaner type of coal extraction method. It avoids current coal mining challenges such as drastic changes to landscapes, high machinery costs, elevated risks to personnel, and post-extraction transport. UCG has a huge potential to provide a clean coal energy source by implementing carbon capture and storage techniques as part of the process. In order to support mitigation strategies for clean coal production and policy development, much research needs to be completed. One component of this information is the need to understand what happens when the coal burns and a subsurface cavity is formed. This paper looks at the efforts to enhance reliable prediction of the size and shape of the cavities. Reactions are one of the most important mechanisms that control the rate of the growth of the cavities. Therefore, modeling the reactions and precise prediction of reaction kinetics can influence the accuracy of a UCG process. The produced syngas composition during UCG is closely linked to the reactions that take place in this process, the permeability of the coal seam, and the temperature distribution. Since the combination of reactions can influence the distributions of the heat and gas components in the coal seam during UCG or even extinguish the combustion, accurate modeling of the reactions is crucial, particularly when all phenomena affecting the reaction rate are considered in a single set of kinetics. In this study, procedures are proposed to estimate the frequency factor and activation energy of the pyrolysis reaction using a single-step decomposition method, the kinetics of the endothermic direction of homogeneous reversible reactions, and the frequency factor of heterogeneous reactions from experiments or literature data. The estimated kinetics is more appropriate for simulation of the UCG process using the porous medium approach. Computer Modelling Group's CMG-STARS (Steam, Thermal, and Advanced Processes Reservoir Simulator) software is used in this study.
