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Abstract

In the context of climate change, the geological storage of carbon dioxide (CO2) is considered as a transitional technology to reduce anthropogenic greenhouse gas emissions. Safe and reliable geo- logical storage requires a thorough understanding of the storage reservoir and its induced spatiotem- poral changes. Geoelectrical monitoring techniques are highly sensitive to compositional changes of the pore fluid and offer opportunities for spatiotemporal imaging of fluid displacement processes. Although well established in near-surface geophysics, the application of geoelectrical techniques to CO2 storage monitoring is relatively new and entails specific practical and methodological challenges. This thesis investigates the optimal locations of electrodes along the borehole trajectories, borehole related imaging artifacts, and the integration with data sets from other monitoring techniques by means of a process-based hydrogeophysical modeling and inversion framework with an application to the pilot site for CO2 storage at Ketzin, Germany. Based on a developed optimization algorithm, it is demonstrated that a sparse, but well conceived set of electrodes can provide a large part of the information content offered by comparably dense electrode distributions. Optimized layouts exhibit a refinement of the electrode spacing within the target horizon and are symmetric for layered and homogeneous models. Effects of complex bore- hole completions are identified and minimized by means of an explicit discretization of the different completion types within the finite-element model. Of particular relevance are open parts of the well completion, since these can exhibit varying electrical properties due to the prevalence of either re- sistive CO2 or conductive brine during the storage operation. Influences of borehole deviations are analyzed and the possibility to infer borehole deviations solely based on geoelectrical data sets is investigated. Finally, a new hydrogeophysical modeling and inversion framework is presented that allows to integrate geoelectrical data with observed CO2 arrival times and gas pressure measure- ments for an estimation of the spatial permeability distribution. The integration of multi-physical data sets enables a better parameterization of the numerical reservoir simulations and thereby con- tributes significantly to an improvement of predictive simulation capabilities and understanding of the underlying processes. Although primarily developed to increase the reliability and efficiency of geoelectrical monitoring for geological storage reservoirs, the developed approaches are transferable to other applications in the field of electrical resistivity imaging.