Browsing by Author "Helmig, Rainer"

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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.
Finding a Balance between Accuracy and Effort For Modeling Biomineralization
(2016-11) Hommel, Johannes; Ebigbo, Anozie; Gerlach, Robin; Cunningham, Alfred B.; Helmig, Rainer; Class, Holger
Microbially induced calcite precipitation (MICP) is a technology aiming at the mitigation of potential leakage from underground gas storage sites. A numerical model for MICP was previously developed and validated. The model complexity leads to high computation times, prohibiting at the moment the use of the model for designing field-scale MICP applications. This study investigates savings of the computational time by well-chosen model simplifications. Additionally, this approach is motivated by the high uncertainty of relevant input-parameters. Excessively detailed equations are unnecessary burdens to the MICP model, whose reliability is influenced by the input-parameter uncertainty.
Investigating the influence of the initial biomass distribution and injection strategies on biofilm-mediated calcite precipitation in porous media
(2016-09) Hommel, Johannes; Lauchnor, Ellen G.; Gerlach, Robin; Cunningham, Alfred B.; Ebigbo, Anozie; Helmig, Rainer; Class, Holger
Attachment of bacteria in porous media is a complex mixture of processes resulting in the transfer and immobilization of suspended cells onto a solid surface within the porous medium. Quantifying the rate of attachment is difficult due to the many simultaneous processes possibly involved in attachment, including straining, sorption, and sedimentation, and the difficulties in measuring metabolically active cells attached to porous media. Preliminary experiments confirmed the difficulty associated with measuring active Sporosarcina pasteurii cells attached to porous media. However, attachment is a key process in applications of biofilm-mediated reactions in the subsurface such as microbially induced calcite precipitation. Independent of the exact processes involved, attachment determines both the distribution and the initial amount of attached biomass and as such the initial reaction rate. As direct experimental investigations are difficult, this study is limited to a numerical investigation of the effect of various initial biomass distributions and initial amounts of attached biomass. This is performed for various injection strategies, changing the injection rate as well as alternating between continuous and pulsed injections. The results of this study indicate that, for the selected scenarios, both the initial amount and the distribution of attached biomass have minor influence on the Ca2+2+ precipitation efficiency as well as the distribution of the precipitates compared to the influence of the injection strategy. The influence of the initial biomass distribution on the resulting final distribution of the precipitated calcite is limited, except for the continuous injection at intermediate injection rate. But even for this injection strategy, the Ca2+2+ precipitation efficiency shows no significant dependence on the initial biomass distribution.
Modeling biofilm growth in the presence of carbon dioxide and water flow in the subsurface
(2010-07) Ebigbo, Anozie; Helmig, Rainer; Cunningham, Alfred B.; Class, Holger; Gerlach, Robin
The concentration of greenhouse gasesâ€”particularly carbon dioxide (CO2)â€”in the atmosphere has been on the rise in the past decades. One of the methods which have been proposed to help reduce anthropogenic CO2 emissions is the capture of CO2 from large, stationary point sources and storage in deep geological formations. The caprock is an impermeable geological layer which prevents the leakage of stored CO2, and its integrity is of utmost importance for storage security. Due to the high pressure build-up during injection, the caprock in the vicinity of the well is particularly at risk of fracturing. Biofilms could be used as biobarriers which help prevent the leakage of CO2 through the caprock in injection well vicinity by blocking leakage pathways. The biofilm could also protect well cement from corrosion by CO2-rich brine.The goal of this paper is to develop and test a numerical model which is capable of simulating the development of a biofilm in a CO2 storage reservoir. This involves the description of the growth of the biofilm, flow and transport in the geological formation, and the interaction between the biofilm and the flow processes. Important processes which are accounted for in the model include the effect of biofilm growth on the permeability of the formation, the hazardous effect of supercritical CO2 on suspended and attached bacteria, attachment and detachment of biomass, and two-phase fluid flow processes. The model is tested by comparing simulation results to experimental data.
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, Holger
The 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.