A revised model for microbially induced calcite precipitation: Improvements and new insights based on recent experiments
A revised model for microbially induced calcite precipitation: Improvements and new insights based on recent experiments
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DOI：
10.1002/2014wr016503
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发表时间：
2015-05-01
影响因子：
5.4
通讯作者：
Class, Holger
中科院分区：
文献类型：
--
作者：
Hommel, Johannes;Lauchnor, Ellen;Class, Holger
Ebigbo等人（2012）发表的微生物诱导方解石沉淀（MICP）模型已根据从实验和模型校准中获得的新见解进行了改进。在地下用MICP构建渗透率降低的预测模型的挑战是量化流动、运输、生物膜生长和反应动力学之间的复杂相互作用。Lauchnor等人（2015）关于来自批实验的全细胞尿素分解动力学的新数据被纳入模型中，这使得相关参数的定量更加精确，并且简化了模型方程中的反应动力学。此外，该模型已被客观地校准通过逆模拟使用准一维柱实验和径向流实验。通过对反演模型的后处理，对模型标定过程中拟合的模型输入参数进行了全面的灵敏度分析。这表明，方解石沉淀和NH4+和Ca2+的浓度是特别敏感的参数与脲解速率和附着行为的生物质。根据确定的灵敏度和反演中估计参数的值范围，可以确定进一步研究可能对改善对MICP的理解和工程产生重大影响的重点领域。
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 NH4+ and Ca2+ 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.