## 7 Summary and Conclusions  
The developed EICP model was calibrated and validated using laboratory column experiments. Due to the increased temperatures compared to previous investigations focusing on MICP, the experiments and some of the geochemical parameterizations are associated with some level of uncertainty, but we are confident that the overall model concept and the parameterizations are robust and able to reproduce the main features of the laboratory experiments. We showed that the model is able to qualitatively predict the outcome of experiments with varied injection strategy and injected medium concentration. Using a minimal set of two calibration parameters, i.e., the ad- and desorption rate coefficients for urease, proved to be the most meaningful choice of those investigated, as adding more calibration parameters increased the residuals for the validation setup. The presented model can now be applied to model EICP engineering problems. One application could be supporting a subsurface engineering method selection by using the presented model to compare the use of EICP to the more established MICP using any of the developed models for MICP (see Section 1) and more conventional methods of modifying subsurface properties, such as chemical grouting or cement injection, predicted by appropriate numerical models. Further, it would be beneficial to compare the model predictions with additional experimental results of experiments conducted at various environmental or design conditions such as temperature, injection concentrations and strategies, experiment size, and complexity, similarly to the decade-long development and improvement of the (low-temperature) MICP model, which proved essential in the scale-up of the biomineralization technology [12]. Ultimately, this would help to design field applications of subsurface-modification technologies and help to choose the most promising method for a given location and its properties, comparing not only injection strategies but also different methods to induce precipitation. However, for this, the relatively complex models should be eventually simplified to be able to perform an increased number of simulations to be able to account for the imminent scenario uncertainties associated with applications in the subsurface with limited access for site investigation. Figure 8: Prediction of concentration measurements at 10.16 cm from the inlet for column experiment #1 (0.33 M mineralization medium concentration). **Author Contributions:** Conceptualization, J.H., A.J.P., R.G., A.B.C., and H.C.; methodology, J.H. (modeling), A.A., and Z.F. (experiments); software, J.H. ; validation, J.H., A.J.P., and R.G. ; formal analysis, J.H. ; investigation, J.H. (modeling), A.A., and Z.F. (experiments); resources, J.H., A.J.P., and R.G. ; data curation, J.H. ; writing--original draft preparation, J.H. ; writing--review and editing, J.H., R.H., and H.C.; visualization, [PERSON]; supervision, [PERSON] and [PERSON]; project administration, [PERSON]; funding acquisition, [PERSON], [PERSON], and [PERSON] All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)--project number HO 6055/1-1. The experimental work was funded by the U.S. Department of Energy, Office of Fossil Energy under the DOE award number DE-FE0026513, \"Wellbore Leakage Mitigation Using Advanced Mineral Precipitation Strategies\". **Acknowledgments:** We further thank the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for supporting this work by funding SFB 1313, project number 327154368. The authors acknowledge the Center for Biofilm Engineering and the Imaging and Chemical Analysis Laboratory at Montana State University part of the Montana Nanotechnology Facility, an NNCI facility supported by NSF grant ECCS-1542210. **Conflicts of Interest:** The authors declare no conflict of interest. **Abbreviations**  
The following abbreviations are used in this manuscript: