Scholarly Work - Chemical & Biological Engineering
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/8718
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Item Importance of specific substrate utilization by microbes in microbially enhanced coal-bed methane production: A modelling study(2020-07) Emmert, Simon; Class, Holger; Davis, Katherine J.; Gerlach, RobinThis study addresses a major gap in the understanding and control of microbially enhanced coal-bed methane (MECBM) production. A mathematical and conceptual model comprises a food-web that includes two types of bacteria and three types of archaea representing substrate-specific members of the community; the microbial community members are potentially interacting by competing for or being inhibited by substrates or products of other microbial community members. The model was calibrated using data sets from two different experimental setups. The calibrated model effectively predicted the methane concentrations within a 7% range of deviation from the experimental results. The results of additional batch experiments using varied conditions are also reproduced in an attempt to validate the model and to test the hypothesis of amendment-induced stimulation of microbial community members capable of converting coal into substrates available to methane producing microbes. This study significantly enhances the understanding of the complex interactions between microbial activity, substrate-specificity and bio-availability of coal for methane production, and provides the basis for including hydraulic flow and transport processes into future mathematical models important for the design and implementation of more sustainable methods of harvesting methane from un-mineable coalbeds.Item Darcy-scale modeling of microbially induced carbonate mineral precipitation in sand columns(2012-07) Ebigbo, Anozie; Phillips, Adrienne J.; Gerlach, Robin; Helmig, Rainer; Cunningham, Alfred B.; Class, Holger; Spangler, Lee H.This investigation focuses on the use of microbially induced calcium carbonate precipitation (MICP) to set up subsurface hydraulic barriers to potentially increase storage security near wellbores of CO2 storage sites. A numerical model is developed, capable of accounting for carbonate precipitation due to ureolytic bacterial activity as well as the flow of two fluid phases in the subsurface. The model is compared to experiments involving saturated flow through sand-packed columns to understand and optimize the processes involved as well as to validate the numerical model. It is then used to predict the effect of dense-phase CO2 and CO2-saturated water on carbonate precipitates in a porous medium.Item A revised model for microbially induced calcite precipitation: Improvements and new insights based on recent experiments(2015-05) Hommel, Johannes; Lauchnor, Ellen G.; Phillips, Adrienne J.; Gerlach, Robin; Cunningham, Alfred B.; Helmig, Rainer; Ebigbo, Anozie; Class, HolgerThe model for microbially induced calcite precipitation (MICP) published by Ebigbo et al. (2012) has been improved based on new insights obtained from experiments and model calibration. The challenge in constructing a predictive model for permeability reduction in the underground with MICP is the quantification of the complex interaction between flow, transport, biofilm growth, and reaction kinetics. New data from Lauchnor et al. (2015) on whole-cell ureolysis kinetics from batch experiments were incorporated into the model, which has allowed for a more precise quantification of the relevant parameters as well as a simplification of the reaction kinetics in the equations of the model. Further, the model has been calibrated objectively by inverse modeling using quasi-1D column experiments and a radial flow experiment. From the postprocessing of the inverse modeling, a comprehensive sensitivity analysis has been performed with focus on the model input parameters that were fitted in the course of the model calibration. It reveals that calcite precipitation and concentrations of inline image and inline image are particularly sensitive to parameters associated with the ureolysis rate and the attachment behavior of biomass. Based on the determined sensitivities and the ranges of values for the estimated parameters in the inversion, it is possible to identify focal areas where further research can have a high impact toward improving the understanding and engineering of MICP.