文摘
Biogenic production of coalbed methane under anaerobic conditions occurs through a large number of reactions involving a community of micro-organisms. We propose a kinetic scheme for this complicated reaction network using lumped species reacting in a series of enzymatic reaction blocks consisting of coal solubilization, hydrolysis, acidogenesis, acetogenesis, and methanogenesis. Among these pathways, acetoclastic methanogenesis is assumed to be dominant. Based on implications from experimental data, tryptone (a nitrogen rich nutrient used in the stimulation of methane production) is assumed to produce aromatic ring intermediates. Coal solubilization is described by a diffusion layer model. Monod kinetics are applied to model the enzymatic reaction rates, but the rate of methanogenesis is modeled with modified Monod kinetics to account for substrate inhibition. An analytical solution to the model is derived and its parametric sensitivity is investigated in different operating regions. Model parameters are estimated from data from various anaerobic bottle experiments conducted by us using nonlinear regression with the particle swarm optimization algorithm, and the model’s predictive ability has been validated for various coal samples from the literature, too. The predictive kinetic model thus established provides estimates of the concentration of products as well as intermediate species in the conversion of coal. The model can be used to optimize biogenic methane production from coal at different scales ranging from coreflooding experiments to the reservoir and field scales.