Kinetic modeling of biogenic methane production from coal

Microbial in situ gasification mining of coal has a great application prospect in unmined remnant coal and in situ coal seams. To better understand the process of coal microbial gasification and grasp the key influencing factors of coal microbial gasification, a kinetic model of coal biogasification based on the research progress of coal microbial gasification was established. The model contains five processes of coal degradation, i.e., coal solubilization, hydrolysis, acid production, hydrogen and acetic acid production, and methane production. The model uses elemental and electron balances to determine the stoichiometric numbers of the biochemical reaction equations. Monod kinetic equations were used to describe the microbial growth and death processes, taking into account the organisms' own growth inhibition and product inhibition. To calibrate the model, anaerobic fermentation experiments with coal were carried out in the laboratory, and the model was calibrated using the methane production data obtained from the experiments. The calibration results show that the model has a good description of both microbial gasification of coal and nutrient-enhanced coal methanogenesis. A sensitivity analysis of the model parameters was carried out. By changing the model sensitivity parameters, the change rule of model parameters and the characteristics of methane production were analyzed. The numerical calculation results show that the larger the initial coal concentration, the larger the methane production, but there exists a maximum coal addition amount, and exceeding this optimal concentration will inhibit the methane production. Coal dissolution rate can shorten the initiation time of coal producer methane, and the use of coal pretreatment can increase the solubility of coal and methane production. Microbial concentration similarly affects the characterization of coal producer methane. Changing the initial concentration of coal-solubilizing and hydrolyzing bacteria can shorten the delay period of gas production; a 10-fold increase (1 mol/m³ to 10 mol/m³) in the concentration of coal-solubilizing bacteria can shorten the delay period by 83.33%, and the concentration of acetic acid-nutrient methane-producing bacteria affects the maximum methane production rate. The addition of cyanobacteria can provide substrates for microbial growth and also provide methanogenic substrates for methanogenic bacteria, which significantly increased the organic loading rate of the model and enhanced methane production. Adding 1.0, 1.63, 2.5, 4.0 mol/m³ of cyanobacteria enhanced the methane production by 12.9, 20.8, 27.7, and 54.3 times, respectively. The present study enriches the data modeling methods in the field of coal microbial gasification and provides important theoretical support and guidance for the laboratory test of this technology. At the same time, the method of combining laboratory experiments and numerical calculations for the study can improve the insights of coal producer methane.