Universität Stuttgart
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Item Open Access Porosity and permeability alterations in processes of biomineralization in porous media - microfluidic investigations and their interpretation(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Weinhardt, Felix; Class, Holger (apl. Prof. Dr.-Ing)Motivation: Biomineralization refers to microbially induced processes resulting in mineral formations. In addition to complex biomineral structures frequently formed by marine organisms, like corals or mussels, microbial activities may also indirectly induce mineralization. A famous example is the formation of stromatolites, which result from biofilm activities that locally alter the chemical and physical properties of the environment in favor of carbonate precipitation. Recently, biomineralization gained attention as an engineering application. Especially with the background of global warming and the objective to reduce CO2 emissions, biomineralization offers an innovative and sustainable alternative to the usage of conventional Portland cement, whose production currently contributes significantly to global CO2 emissions. The most widely used method of biomineralization in engineering applications, is ureolytic calcium carbonate precipitation, which relies on the hydrolysis of urea and the subsequent precipitation of calcium carbonate. The hydrolysis of urea at moderate temperatures is relatively slow and therefore needs to be catalyzed by the enzyme urease to be practical for applications. Urease can be extracted from plants, for example from ground jack beans, and the process is consequently referred to as enzyme-induced calcium carbonate precipitation (ECIP). Another method is microbially induced calcium carbonate precipitation (MICP), which uses ureolytic bacteria that produce the enzyme in situ. EICP and MICP applications allow for producing various construction materials, stabilizing soils, or creating hydraulic barriers in the subsurface. The latter can be used, for example, to remediate leakages at the top layer of gas storage reservoirs, or to contain contaminant plumes in aquifers. Especially when remediating leakages in the subsurface, the most crucial parameter to be controlled is its intrinsic permeability. A valuable tool for predicting and planning field applications is the use of numerical simulation at the scale of representative elementary volumes (REV). For that, the considered domain is subdivided into several REV’s, which do not resolve the pore space in detail, but represent it by averaged parameters, such as the porosity and permeability. The porosity describes the ratio of the pore space to the considered bulk volume, and the permeability quantifies the ease of fluid flow through a porous medium. A change in porosity generally also affects permeability. Therefore, for REV-scale simulations, constitutive relationships are utilized to describe permeability as a function of porosity. There are several porosity-permeability relationships in the literature, such as the Kozeny-Carman relationship, Verma-Pruess, or simple power-law relationships. These constitutive relationships can describe individual states but usually do not include the underlying processes. Different boundary conditions during biomineralization may influence the course of porosity-permeability relationships. However, these relationships have not yet been adequately addressed. Pore-scale simulations are, in principle, very well suited to investigate pore space changes and their effects on permeability systematically. However, these simulations also rely on simplifications and assumptions. Therefore, it is essential to conduct experimental studies to investigate the complex processes during calcium carbonate precipitation in detail at the pore scale. Recent studies have shown that microfluidic methods are particularly suitable for this purpose. However, previous microfluidic studies have not explicitly addressed the impact of biomineralization on hydraulic effects. Therefore, this work aims to identify relevant phenomena at the pore scale to conclude on the REV-scale parameters, porosity and permeability, and their relationship. Contributions: This work comprises three publications. First, a suitable microfluidic setup and workflow were developed in Weinhardt et al. [2021a] to study pore space changes and the associated hydraulic effects reliably. This paper illustrated the benefits and insights of combining optical microscopy and micro X-ray computed tomography (micro XRCT) with hydraulic measurements in microfluidic chips. The elaborated workflow allowed for quantitative analysis of the evolution of calcium carbonate precipitates in terms of their size, shape, and spatial distribution. At the same time, their influence on differential pressure could be observed as a measure of flow resistance. Consequently, porosity and permeability changes could be determined. Along with this paper, we published two data sets [Weinhardt et al., 2021b, Vahid Dastjerdi et al., 2021] and set the basis for two other publications. In the second publication [von Wolff et al., 2021], the simulation results of a pore-scale numerical model, developed by Lars von Wolff, were compared to the experimental data of the first paper [Weinhardt et al., 2021b]. We observed a good agreement between the experimental data and the model results. The numerical studies complemented the experimental observations in allowing for accurate analysis of crystal growth as a function of local velocity profiles. In particular, we observed that crystal aggregates tend to grow toward the upstream side, where the supply of reaction products is higher than on the downstream side. Crystal growth during biomineralization under continuous inflow is thus strongly dependent on the locally varying velocities in a porous medium. In the third publication [Weinhardt et al., 2022a], we conducted further microfluidic experiments based on the experimental setup and workflow of the first contribution and published another data set [Weinhardt et al., 2022b]. We used microfluidic cells with a different, more realistic pore structure and investigated the influence of different injection strategies. We found that the development of preferential flow paths during EICP application may depend on the given boundary conditions. Constant inflow rates can lead to the development of preferential flow paths and keep them open. Gradually reduced inflow rates can mitigate this effect. In addition, we concluded that the coexistence of multiple calcium carbonate polymorphs and their transformations could influence the temporal evolution of porosity-permeability relationships.Item Open Access High-resolution spatio-temporal measurements of the colmation phenomenon under laboratory conditions(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Mayar, Mohammad Assem; Wieprecht, Silke (Prof. Dr.-Ing.)The fine sediment infiltration and accumulation into the gravel bed of rivers, the so-called colmation phenomenon, is a pernicious process exacerbated by anthropogenic activities. Owing to the importance and complexity of this phenomenon, it has been widely studied over the last decades. Various devices and methods have been developed to assess this phenomenon, where most of them are destructive and sample-based, resulting in an alteration of the natural conditions. Therefore, non-intrusive techniques, which provide spatial and temporal details with a high-resolution, are required to discretize the mechanisms involved in the colmation process. To address these issues, investigations under laboratory conditions may simplify the complexity of nature and enable individual and exactly defined boundary conditions to be investigated. Therefore, this thesis aims at (i) developing a non-intrusive and undisturbed measurement method for the high-resolution spatio-temporal measurements of the sediment infiltration processes and the development of sediment accumulation in an artificial river bed under laboratory conditions, (ii) applying this method to certain experiments for the assessment of the effects of different boundary conditions on sediment infiltration, and (iii) investigating the colmation phenomenon (also known as clogging) of gravel beds. For this purpose, the gamma-ray attenuation method is used together with an artificial gravel bed arranged from the spheres with various diameters and placed in a laboratory flume. This new method works based on the gamma radiation that passes through the infiltrated sediments, water, and bed spheres, in which the gamma-ray attenuation is linked to the variations of the infiltrated sediments’ quantity. The main simplification of this approach is that gravel beds are represented by the combinations of different-sized spheres. This gives the opportunity to fully distinguish infiltrating sediments from the bed material, reduce the complexity of the natural environment, and allows for repetitive measurements of the same position with different boundary conditions. From the results of this study, first, the gamma-ray attenuation measurement method was optimized to resolve the inconsistencies in the measurements. Subsequently, the concept of the non-intrusive and undisturbed measurement is proved through box experiments. Additional reproducibility experiments in the laboratory flume, for a similar bed structure, showed only small deviations between two experiments with the same setup. Consequently, the established technique was used in a series of experiments to evaluate the effects of different supply rates, total supply masses, and sediment particle size boundary conditions on the sediment infiltration and colmation processes. Vertical profiles of the infiltrated sediment were quantified through high spatial resolution measurements. Furthermore, to evaluate the infiltrating sediment accumulation development, and the temporal variations of the infiltrated sediments, the vertical profile measurements were first repeated after a specific time-period to track interval-averaged variations in all positions of the vertical axis. Next, a specific position of the vertical axis was measured continuously during the entire experiment in a high temporal resolution. The measured vertical profiles illustrate the vertical distribution, colmation, and unimpeded percolation of the infiltrated sediments. The dynamic one-point measurement precisely identifies the three phases (the start of the pore-filling, the required time to fill the pore, and the final amount of infiltrated sediments including natural fluctuation during the ongoing experiments) of the sediment infiltration or the possible clogging. As a limitation, the gamma-ray attenuation system’s current configuration only works in artificial gravel beds because of the given density difference between infiltrated sediments and the artificial bed structure. Intense radiations that pass through the natural bed's thickness are capable of detecting a significant amount of infiltrated sediments. However, small amounts of infiltrated sediments will create only a minimal shift in attenuation, which might be confused with the statistical error. In addition, the legal restriction against using radioactive material in the natural environment is another reason for not applying it in the field. Furthermore, the gamma-ray attenuation method cannot resolve the sediment distribution in the measurement horizon and provides an integrative result for each measurement position. In addition, if a mixture of silt, clay, and sand is supplied to the experiment, the gamma-ray attenuation system will produce a bulk result of all the infiltrated materials. To conclude, despite the limitations mentioned above, the gamma-ray attenuation method offers a unique opportunity for the non-intrusive and undisturbed measurements of the sediment infiltration or the special case of colmation, with a high spatio-temporal resolution. This method has the potential to quantify the investigated processes on a millimetric spatial scale, if the measurement time is not a constraint, or vice versa, in a high temporal resolution (seconds) for a specific position, if spatial scale is not important. Moreover, the gamma-ray attenuation approach can simultaneously measure the longitudinal distribution of the sedimentological processes, if multiple instruments or a single device with several radiation-emitting-holes is in operation. Last, but not least, rather than the spheres, artificial gravel beds could be made of any substance with a composition significantly different from the infiltrating sediments, and the boundary conditions of the experiments can be improved in order to attain conditions close to nature. Finally, the gamma-ray attenuation method can be integrated with advanced flow measurement instruments such as Particle Image Velocimetry (PIV) and other high-resolution endoscopic devices to track the behavior of fine sediment infiltration and its clogging process in the porous gravel beds as it occurs in nature.Item Open Access Magnetic resonance imaging of water content and flow processes in natural soils by pulse sequences with ultrashort detection(2021) Haber-Pohlmeier, Sabina; Caterina, David; Blümich, Bernhard; Pohlmeier, AndreasMagnetic resonance imaging is a valuable tool for three-dimensional mapping of soil water processes due to its sensitivity to the substance of interest: water. Since conventional gradient- or spin-echo based pulse sequences do not detect rapidly relaxing fractions of water in natural porous media with transverse relaxation times in the millisecond range, pulse sequences with ultrafast detection open a way out. In this work, we compare a spin-echo multislice pulse sequence with ultrashort (UTE) and zero-TE (ZTE) sequences for their suitability to map water content and its changes in 3D in natural soil materials. Longitudinal and transverse relaxation times were found in the ranges around 80 ms and 1 to 50 ms, respectively, so that the spin echo sequence misses larger fractions of water. In contrast, ZTE and UTE could detect all water, if the excitation and detection bandwidths were set sufficiently broad. More precisely, with ZTE we could map water contents down to 0.1 cm3/cm3. Finally, we employed ZTE to monitor the development of film flow in a natural soil core with high temporal resolution. This opens the route for further quantitative imaging of soil water processes.Item Open Access Large-scale high head pico hydropower potential assessment(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2018) Schröder, Hans Christoph; Wieprecht, Silke (Prof. Dr.-Ing.)Due to a lack of site-related information, Pico hydropower (PHP) has hardly been a projectable resource so far. This is particularly true for large area PHP potential information that could open a perspective to increase the size of development projects by aggregating individual PHP installations. The present work is extending the capabilities of GIS based hydropower potential assessment into the PHP domain through a GIS based PHP potential assessment procedure that facilitates the discrimination of areas without high head PHP potential against areas with PHP potential and against areas with so called “favorable PHP potential”. The basic unit of the spatial output is determined by the underlying PHP potential definition of this work: a standardized PHP installation and the required hydraulic source, together called standard unit, are located on an area of one square kilometer. The gradation of the output is a consequence of the verification techniques. Several large area PHP potential field assessment methods, based on contemplative analysis techniques, are developed in this work. Field assessments were conducted in Yunnan Province/China, Costa Rica, Ecuador and Sri Lanka. The aim for all field assessments is to get a comprehensive view on the PHP potential distribution of the entire country/province. Application of the GIS based PHP potential assessment procedure is aimed at the global tropical and subtropical regions.Item Open Access Heat transport from atmosphere through the subsurface to drinking‐water supply pipes(2023) Nissler, Elisabeth; Scherrer, Samuel; Class, Holger; Müller, Tanja; Hermannspan, Mark; Osmancevic, Esad; Haslauer, ClausDrinking‐water quality in supply pipe networks can be negatively affected by high temperatures during hot summer months due to detrimental bacteria encountering ideal conditions for growth. Thus, water suppliers are interested in estimating the temperature in their distribution networks. We investigate both experimentally and by numerical simulation the heat and water transport from ground surface into the subsurface, (i.e., above drinking‐water pipes). We consider the meteorological forcing functions by a sophisticated approach to model the boundary conditions for the heat balance at the soil-atmosphere interface. From August to December 2020, soil temperatures and soil moisture were measured dependent on soil type, land‐use cover, and weather data at a pilot site, constructed specifically for this purpose at the University of Stuttgart with polyethylene and cast‐iron pipes installed under typical in situ conditions. We included this interface condition at the atmosphere-subsurface boundary into an integrated non‐isothermal, variably saturated (Richards') the numerical simulator DuMux 3. This allowed, after calibration, to match measured soil temperatures with ±2°C accuracy. The land‐use cover influenced the soil temperature in 1.5 m more than the soil material used for back‐filling the trench above the pipe.Item Open Access A modeling approach for alpine rivers impacted by hydropeaking including the second law inequality(2012) Tuhtan, Jeffrey Andrew; Wieprecht, Silke (Prof. Dr.-Ing.)An outcome of daily electrical energy consumption is that storage hydropower releases must match the changes in daily demand. These local, high intensity fluctuations are commonly called hydropeaking. Due to their large departure from natural flow rates, the river ecosystems downstream of hydro operations are forced to react. This causes a large shift in the dissipative regime of the river, affecting the entire food web from Sparganium emersum to Salmo trutta. Although the cause of hydropeaking in alpine rivers is obvious, assessing its ecological effects is not an easy task. The study of hydropeaking impacts on river ecology demands a great deal of new theoretical and phenomenological investigation. Complicating such studies is the fact that river ecosystems themselves are not stable systems but are evolving over time, even under steady flow conditions. Although ecological models of aquatic ecosystems have been present for several decades, it is currently not possible to model a fish’s response to the short-term fluctuations in the flow field caused by hydropeaking with the same degree of accuracy which has been achieved under steady flow conditions. The use of numerical models to assess the impacts of hydropeaking on aquatic ecosystems is still in its infancy. The challenge of this dissertation is to construct a theoretical framework that can be used to study abiotic-biotic interactions under highly unsteady conditions. The model is constructed through the lens of thermodynamics, by looking at system interactions in terms of the contributions of the relative equilibrium states: mechanical, chemical, and thermal. The objectives of this dissertation are: 1. Incorporate thermodynamic principles into an aquatic habitat model which can be effectively applied for highly unsteady flow regimes. 2. Evaluate the model in terms of performance, ease of application and theory. This work proposes a new kind of fish habitat model using thermodynamic concepts for use in European alpine rivers affected by hydropeaking. Ecosystem states may be found which allow for optimal systems in which animate components such as fish are able to participate. Furthermore, we show that a ‘first law’ approach which invokes only the conservation of energy is not sufficient to understand the energetics of the alpine river ecosystem. It is necessary to view the ecosystem in terms of its free energy and its entropy as well. This ‘second law’ methodology provides powerful insight and results in a more objective modeling approach to assess hydropeaking impacts on fish considering real-world conditions.Item Open Access Modeling of two phase flow in a hydrophobic porous medium interacting with a hydrophilic structure(2022) Michalkowski, Cynthia; Weishaupt, Kilian; Schleper, Veronika; Helmig, RainerFluid flow through layered materials with different wetting behavior is observed in a wide range of applications in biological, environmental and technical systems. Therefore, it is necessary to understand the occuring transport mechanisms of the fluids at the interface between the layered constituents. Of special interest is the water transport in polymer electrolyte membrane fuel cells. Here, it is necessary to understand the transport mechanisms of water throughout the cell constituents especially on the cathode side, where the excess water has to be removed. This is crucial to choose optimal operating conditions and improve the overall cell performance. Pore-scale modeling of gas diffusion layers (GDLs) and gas distributor has been established as a favorable technique to investigate the ongoing processes. Investigating the interface between the hydrophobic porous GDL and the hydrophilic gas distributor, a particular challenge is the combination and interaction of the different material structures and wetting properties at the interface and its influence on the flow. In this paper, a modeling approach is presented which captures the influence of a hydrophilic domain on the flow in a hydrophobic porous domain at the interface between the two domains. A pore-network model is used as the basis of the developed concept which is extended to allow the modeling of mixed-wet interactions at the interface. The functionality of the model is demonstrated using basic example configurations with one and several interface pores and it is applied to a realistic GDL representation in contact with a channel-land structured gas distributor.Item Open Access Stability criteria for Bayesian calibration of reservoir sedimentation models(2023) Mouris, Kilian; Acuna Espinoza, Eduardo; Schwindt, Sebastian; Mohammadi, Farid; Haun, Stefan; Wieprecht, Silke; Oladyshkin, SergeyModeling reservoir sedimentation is particularly challenging due to the simultaneous simulation of shallow shores, tributary deltas, and deep waters. The shallow upstream parts of reservoirs, where deltaic avulsion and erosion processes occur, compete with the validity of modeling assumptions used to simulate the deposition of fine sediments in deep waters. We investigate how complex numerical models can be calibrated to accurately predict reservoir sedimentation in the presence of competing model simplifications and identify the importance of calibration parameters for prioritization in measurement campaigns. This study applies Bayesian calibration, a supervised learning technique using surrogate-assisted Bayesian inversion with a Gaussian Process Emulator to calibrate a two-dimensional (2d) hydro-morphodynamic model for simulating sedimentation processes in a reservoir in Albania. Four calibration parameters were fitted to obtain the statistically best possible simulation of bed level changes between 2016 and 2019 through two differently constraining data scenarios. One scenario included measurements from the entire upstream half of the reservoir. Another scenario only included measurements in the geospatially valid range of the numerical model. Model accuracy parameters, Bayesian model evidence, and the variability of the four calibration parameters indicate that Bayesian calibration only converges toward physically meaningful parameter combinations when the calibration nodes are in the valid range of the numerical model. The Bayesian approach also allowed for a comparison of multiple parameters and found that the dry bulk density of the deposited sediments is the most important factor for calibration.Item Open Access Efficient concepts for optimal experimental design in nonlinear environmental systems(2014) Geiges, Andreas; Nowak, Wolfgang (Jun.-Prof. Dr.-Ing.)In modern scientific and practical applications, complex simulation tools are increasingly used to support various decision processes. Growing computer power in the recent decades allowed these simulation tools to grow in their complexity in order to model the relevant physical processes more accurately. The number of required model parameter that need to be calibrated is strongly connected to this complexity and hence is growing as well. In environmental systems, in contrast to technical systems, the relevant data and information for adequate calibration of these model parameters are usually sparse or unavailable. This hinders an exact determination of model parameters, initial and boundary conditions or even the correct formulation of a model concept. In such cases, stochastic simulation approaches allow to proceed with uncertain or unknown parameters and to transfer this input uncertainty to estimate the prediction uncertainty of the model. Thus, the predictive quality of an uncertain model can be assessed and thus represents the current state of knowledge about the model prediction. In the case that the prediction quality is judged to be insufficient, new measurement data or information about the real system is required to improve the model. For maximizing the benefits of such campaigns, it is necessary to assess the expected data impact of measurements that are collected according to a proposed campaign design. This allows to identify the so called 'optimal design' that promises the highest expected data impact with respect to the particular model purpose. This thesis addresses data impact analysis of measurements within nonlinear systems or nonlinear parameter estimation problems. In contrast to linear systems, data impact in nonlinear systems depends on the actual future measurement values, which are unknown at the stage of campaign planing. For this reason, only an expected value of data impact can be estimated, by averaging over many potential sets of future measurement values. This nonlinear analysis repeatedly employs nonlinear inference methods and is therefore much more computationally cumbersome than linear estimates. Therefore, the overall purpose of this thesis is to develop new and more efficient methods for nonlinear data impact analysis, which allow tackling complex and realistic applications for which in the past only linear(ized) methods were applicable. This thesis separated efficiency of data impact estimation into three different facets: Accuracy: The first goal of this thesis is the development of a nonlinear and fully flexible reference framework for the accurate estimation of data impact. The core of the developed method is the bootstrap filter, which was identified as the most efficient method for fast and accurate simulation of repeated of nonlinear Bayesian inference for many potential future measurement values. The method is implemented in a strict and rigorous Monte-Carlo framework based on a pre-computed ensemble of model evaluations. The non-intrusive nature of the framework allows its application for arbitrary physical systems and the consideration of any type of uncertainty. Computational speed: The second part of this thesis investigates the theoretical background of data impact analysis in order to identify potentials to speed up this analysis. The key idea followed in this part originates from the well-known symmetry of Bayes Theorem and of a related information measure called Mutual Information. Both allow considering a reversal of the direction of information analysis, in which the roles of potential measurement data and the relevant model prediction are exchanged. Since the space of potential measurements is usually much larger than the space of model prediction values and since both have fundamentally different properties, the reversal of the information assessment offers a high potential for increasing the evaluation speed. Robustness: The last basic facet of an efficient data impact estimation considers the robustness of such estimates with regard to the uncertainty of the underlying model. Basically, model-based data impact estimates are subject to the same uncertainty as any other model output. Thus, the data impact estimate can be regarded as just another uncertain model prediction. Therefore, the high uncertainty of the model (which is the reason for the search for new calibration data) also affects the process of evaluating the most useful new data. In summary, the developed methods and theoretic principles allow for more efficient evaluation of nonlinear data impact. The use of nonlinear measures for data impact lead to an essential improvement of the resulting data acquisition design with respect to a relevant prediction quality. These methods are flexibly applicable for any physical model system and allow the consideration of any degree of statistical dependency. Especially the interactive approach that counters the high initial uncertainties of the model does lead to huge improvement in the design of data acquisition. All achieved conceptual and practical improvements in the evaluation of nonlinear data impact assessment allow using such powerful nonlinear methods also for complex and realistic problems.Item Open Access Uncertainty studies and risk assessment for CO2 storage in geological formations(2013) Walter, Lena Sophie; Class, Holger (apl. Prof. Dr.-Ing.)Carbon capture and storage (CCS) in deep geological formations is one possible option to mitigate the greenhouse gas effect by reducing CO2 emissions into the atmosphere. The assessment of the risks related to CO2 storage is an important task. Events such as CO2 leakage and brine displacement could result in hazards for human health and the environment. In this thesis, a systematic and comprehensive risk assessment concept is presented to investigate various levels of uncertainties and to assess risks using numerical simulations. Depending on the risk and the processes, which should be assessed, very complex models, large model domains, large time scales, and many simulations runs for estimating probabilities are required. To reduce the resulting high computational costs, a model reduction technique (the arbitrary polynomial chaos expansion) and a method for model coupling in space are applied. The different levels of uncertainties are: statistical uncertainty in parameter distributions, scenario uncertainty, e.g. different geological features, and recognized ignorance due to assumptions in the conceptual model set-up. Recognized ignorance and scenario uncertainty are investigated by simulating well defined model set-ups and scenarios. According to damage values, which are defined as a model output, the set-ups and scenarios can be compared and ranked. For statistical uncertainty probabilities can be determined by running Monte Carlo simulations with the reduced model. The results are presented in various ways: e.g., mean damage, probability density function, cumulative distribution function, or an overall risk value by multiplying the damage with the probability. If the model output (damage) cannot be compared to provided criteria (e.g. water quality criteria), analytical approximations are presented to translate the damage into comparable values. The overall concept is applied for the risks related to brine displacement and infiltration into drinking water aquifers. The uncertainties on all three levels are investigated in three approaches with different focus. The concept can also be applied to CO2 leakage or hazards related to other technologies in the subsurface such as methane storage or atomic waste disposal. In the second part of this thesis, uncertainty studies for two realistic storage formations (the pilot site Ketzin (Germany) and a realistic storage formation in the North German Basin) are performed to investigate the related uncertainties and to reduce them as much as possible. For the Ketzin site, history matching of the measurement data, is an important task for dynamic modeling and essential for future risk assessment. A systematic approach to fit the data set using inverse modeling is presented in this work. For future risk assessment for realistic sites, e.g. for the Ketzin site, the uncertainty studies and the history matching approach provide important information. Finally, CCS is discussed in the context of risk perception and the possible input of the risk assessment concept presented in this work is discussed. This work is a first attempt to connect the technical risk assessment for CO2 storage to the social science approach for risk assessment. It is bridging the gap between engineering and social sciences by integrating the technical quantification of risk into the wider context of a comprehensive risk governance model.