02 Fakultät Bau- und Umweltingenieurwissenschaften
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/3
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Item Open Access Reconstruction of μXRCT data sets using the ASTRA toolbox(2020) Voland, PaulItem Open Access Pressure management via brine extraction in geological CO2 storage : adaptive optimization strategies under poorly characterized reservoir conditions(2019) González-Nicolás, Ana; Cihan, Abdullah; Petrusak, Robin; Zhou, Quanlin; Trautz, Robert; Godec, Michael; Birkholzer, Jens T.Industrial-scale injection of CO2 into the subsurface increases the fluid pressure in the reservoir, which if not properly controlled can potentially lead to geomechanical damage (i.e., fracturing of the caprock or reactivation of faults) and subsequent CO2 leakage. Brine extraction is one approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. The management of the extracted brine can be expensive (i.e., due to transportation, treatment, disposal, or re-injection), with added cost to the carbon capture and sequestration (CCS); thus, minimizing the volume of extraction brine is of great importance to ensure that the economics of CCS are favorable. The main objective of this study is to demonstrate the use of adaptive optimization methods in the planning of brine extraction and to investigate how the quality of initial site characterization data and the use of newly acquired monitoring data (e.g. pressure at observation wells) impact the optimization performance. We apply an adaptive management approach that integrates monitoring, calibration, and optimization of brine extraction rates to achieve pre-defined pressure constraints. Our results show that reservoir pressure management can be extremely benefited by early and high frequency pressure monitoring during early injection times, especially for poor initial reservoir characterization. Low frequencies of model calibration and optimization with monitoring data may lead to optimization problems, because either pressure buildup constraints are violated or excessively high extraction rates are proposed. The adaptive pressure management approach may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the volumes of extracted brine while controlling pressure buildup.Item Open Access Diagnosing similarities in probabilistic multi-model ensembles : an application to soil-plant-growth-modeling(2022) Schäfer Rodrigues Silva, Aline; Weber, Tobias K. D.; Gayler, Sebastian; Guthke, Anneli; Höge, Marvin; Nowak, Wolfgang; Streck, ThiloThere has been an increasing interest in using multi-model ensembles over the past decade. While it has been shown that ensembles often outperform individual models, there is still a lack of methods that guide the choice of the ensemble members. Previous studies found that model similarity is crucial for this choice. Therefore, we introduce a method that quantifies similarities between models based on so-called energy statistics. This method can also be used to assess the goodness-of-fit to noisy or deterministic measurements. To guide the interpretation of the results, we combine different visualization techniques, which reveal different insights and thereby support the model development. We demonstrate the proposed workflow on a case study of soil–plant-growth modeling, comparing three models from the Expert-N library. Results show that model similarity and goodness-of-fit vary depending on the quantity of interest. This confirms previous studies that found that “there is no single best model” and hence, combining several models into an ensemble can yield more robust results.Item Open Access Strategies for simplifying reactive transport models : a Bayesian model comparison(2020) Schäfer Rodrigues Silva, Aline; Guthke, Anneli; Höge, Marvin; Cirpka, Olaf A.; Nowak, WolfgangFor simulating reactive transport on aquifer scale, various modeling approaches have been proposed. They vary considerably in their computational demands and in the amount of data needed for their calibration. Typically, the more complex a model is, the more data are required to sufficiently constrain its parameters. In this study, we assess a set of five models that simulate aerobic respiration and denitrification in a heterogeneous aquifer at quasi steady state. In a probabilistic framework, we test whether simplified approaches can be used as alternatives to the most detailed model. The simplifications are achieved by neglecting processes such as dispersion or biomass dynamics, or by replacing spatial discretization with travel‐time‐based coordinates. We use the model justifiability analysis proposed by Schöniger, Illman, et al. (2015, https://doi.org/10.1016/j.jhydrol.2015.07.047) to determine how similar the simplified models are to the reference model. This analysis rests on the principles of Bayesian model selection and performs a tradeoff between goodness‐of‐fit to reference data and model complexity, which is important for the reliability of predictions. Results show that, in principle, the simplified models are able to reproduce the predictions of the reference model in the considered scenario. Yet, it became evident that it can be challenging to define appropriate ranges for effective parameters of simplified models. This issue can lead to overly wide predictive distributions, which counteract the apparent simplicity of the models. We found that performing the justifiability analysis on the case of model simplification is an objective and comprehensive approach to assess the suitability of candidate models with different levels of detail.Item Open Access Diagnosing hydro-mechanical effects in subsurface fluid flow through fractures(2023) Schmidt, Patrick; Steeb, Holger; Renner, JörgHydro-mechanically induced transient changes in fracture volume elude an analysis of pressure and flow rate transients by conventional diffusion-based models. We used a previously developed fully coupled, inherently non-linear numerical simulation model to demonstrate that harmonic hydraulic excitation of fractures leads to systematic overtones in the response spectrum that can thus be used as a diagnostic criterion for hydro-mechanical interaction. The examination of response spectra, obtained from harmonic testing at four different field sites, for the occurrence of overtones confirmed their potential for the hydro-mechanical characterization of tested reservoirs. A non-dimensional analysis identified relative aperture change as the critical system parameter.Item Open Access Bayesian calibration and validation of a large‐scale and time‐demanding sediment transport model(2020) Beckers, Felix; Heredia, Andrés; Noack, Markus; Nowak, Wolfgang; Wieprecht, Silke; Oladyshkin, SergeyThis study suggests a stochastic Bayesian approach for calibrating and validating morphodynamic sediment transport models and for quantifying parametric uncertainties in order to alleviate limitations of conventional (manual, deterministic) calibration procedures. The applicability of our method is shown for a large‐scale (11.0 km) and time‐demanding (9.14 hr for the period 2002-2013) 2‐D morphodynamic sediment transport model of the Lower River Salzach and for three most sensitive input parameters (critical Shields parameter, grain roughness, and grain size distribution). Since Bayesian methods require a significant number of simulation runs, this work proposes to construct a surrogate model, here with the arbitrary polynomial chaos technique. The surrogate model is constructed from a limited set of runs (n=20) of the full complex sediment transport model. Then, Monte Carlo‐based techniques for Bayesian calibration are used with the surrogate model (105 realizations in 4 hr). The results demonstrate that following Bayesian principles and iterative Bayesian updating of the surrogate model (10 iterations) enables to identify the most probable ranges of the three calibration parameters. Model verification based on the maximum a posteriori parameter combination indicates that the surrogate model accurately replicates the morphodynamic behavior of the sediment transport model for both calibration (RMSE = 0.31 m) and validation (RMSE = 0.42 m). Furthermore, it is shown that the surrogate model is highly effective in lowering the total computational time for Bayesian calibration, validation, and uncertainty analysis. As a whole, this provides more realistic calibration and validation of morphodynamic sediment transport models with quantified uncertainty in less time compared to conventional calibration procedures.Item Open Access Characterization of export regimes in concentration-discharge plots via an advanced time-series model and event-based sampling strategies(2021) González-Nicolás, Ana; Schwientek, Marc; Sinsbeck, Michael; Nowak, WolfgangCurrently, the export regime of a catchment is often characterized by the relationship between compound concentration and discharge in the catchment outlet or, more specifically, by the re-gression slope in log-concentrations versus log-discharge plots. However, the scattered points in these plots usually do not follow a plain linear regression representation because of different processes (e.g., hysteresis effects). This work proposes a simple stochastic time-series model for simulating compound concentrations in a river based on river discharge. Our model has an ex-plicit transition parameter that can morph the model between chemostatic behavior and che-modynamic behavior. As opposed to the typically used linear regression approach, our model has an additional parameter to account for hysteresis by including correlation over time. We demonstrate the advantages of our model using a high-frequency data series of nitrate concen-trations collected with in situ analyzers in a catchment in Germany. Furthermore, we identify event-based optimal scheduling rules for sampling strategies. Overall, our results show that (i) our model is much more robust for estimating the export regime than the usually used regres-sion approach, and (ii) sampling strategies based on extreme events (including both high and low discharge rates) are key to reducing the prediction uncertainty of the catchment behavior. Thus, the results of this study can help characterize the export regime of a catchment and manage water pollution in rivers at lower monitoring costs.Item Open Access Experimental evaluation of fluid connectivity in two‐phase flow in porous media during drainage(2022) Vahid Dastjerdi, Samaneh; Karadimitriou, Nikolaos; Hassanizadeh, S. Majid; Steeb, HolgerThis study aims to experimentally investigate the possibility of combining two extended continuum theories for two‐phase flow. One of these theories considers interfacial area as a separate state variable, and the other explicitly discriminates between connected and disconnected phases. This combination enhances our potential to effectively model the apparent hysteresis, which generally dominates two‐phase flow. Using optical microscopy, we perform microfluidic experiments in quasi‐2D artificial porous media for various cyclic displacement processes and boundary conditions. Specifically for a number of sequential drainage processes, with detailed image (post‐)processing, pore‐scale parameters such as the interfacial area between the phases (wetting, non‐wetting, and solid), and local capillary pressure, as well as macroscopic parameters like saturation, are estimated. We show that discriminating between connected and disconnected clusters and the concept of the interfacial area as a separate state variable can be an appropriate way of modeling hysteresis in a two‐phase flow scheme. The drainage datasets of capillary pressure, saturation, and specific interfacial area, are plotted as a surface, given by f (Pc, sw, awn) = 0. These surfaces accommodate all data points within a reasonable experimental error, irrespective of the boundary conditions, as long as the corresponding liquid is connected to its inlet. However, this concept also shows signs of reduced efficiency as a modeling approach in datasets gathered through combining experiments with higher volumetric fluxes. We attribute this observation to the effect of the porous medium geometry on the phase distribution. This yields further elaboration, in which this speculation is thoroughly studied and analyzed.Item Open Access Surrogate-based Bayesian comparison of computationally expensive models : application to microbially induced calcite precipitation(2021) Scheurer, Stefania; Schäfer Rodrigues Silva, Aline; Mohammadi, Farid; Hommel, Johannes; Oladyshkin, Sergey; Flemisch, Bernd; Nowak, WolfgangGeochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface reservoirs that currently contains strong conceptual uncertainty. This means, several modeling approaches describing the biogeochemical process are plausible and modelers face the uncertainty of choosing the most appropriate one. The considered models differ in the underlying hypotheses about the process structure. Once observation data become available, a rigorous Bayesian model selection accompanied by a Bayesian model justifiability analysis could be employed to choose the most appropriate model, i.e. the one that describes the underlying physical processes best in the light of the available data. However, biogeochemical modeling is computationally very demanding because it conceptualizes different phases, biomass dynamics, geochemistry, precipitation and dissolution in porous media. Therefore, the Bayesian framework cannot be based directly on the full computational models as this would require too many expensive model evaluations. To circumvent this problem, we suggest to perform both Bayesian model selection and justifiability analysis after constructing surrogates for the competing biogeochemical models. Here, we will use the arbitrary polynomial chaos expansion. Considering that surrogate representations are only approximations of the analyzed original models, we account for the approximation error in the Bayesian analysis by introducing novel correction factors for the resulting model weights. Thereby, we extend the Bayesian model justifiability analysis and assess model similarities for computationally expensive models. We demonstrate the method on a representative scenario for microbially induced calcite precipitation in a porous medium. Our extension of the justifiability analysis provides a suitable approach for the comparison of computationally demanding models and gives an insight on the necessary amount of data for a reliable model performance.Item Open Access The method of forced probabilities : a computation trick for Bayesian model evidence(2022) Banerjee, Ishani; Walter, Peter; Guthke, Anneli; Mumford, Kevin G.; Nowak, WolfgangBayesian model selection objectively ranks competing models by computing Bayesian Model Evidence (BME) against test data. BME is the likelihood of data to occur under each model, averaged over uncertain parameters. Computing BME can be problematic: exact analytical solutions require strong assumptions; mathematical approximations (information criteria) are often strongly biased; assumption-free numerical methods (like Monte Carlo) are computationally impossible if the data set is large, for example like high-resolution snapshots from experimental movies. To use BME as ranking criterion in such cases, we develop the “Method of Forced Probabilities (MFP)”. MFP swaps the direction of evaluation: instead of comparing thousands of model runs on random model realizations with the observed movie snapshots, we force models to reproduce the data in each time step and record the individual probabilities of the model following these exact transitions. MFP is fast and accurate for models that fulfil the Markov property in time, paired with high-quality data sets that resolve all individual events. We demonstrate our approach on stochastic macro-invasion percolation models that simulate gas migration in porous media, and list additional examples of probable applications. The corresponding experimental movie was obtained from slow gas injection into water-saturated, homogeneous sand in a 25 x 25 x 1 cm acrylic glass tank. Despite the movie not always satisfying the high demands (resolving all individual events), we can apply MFP by suggesting a few workarounds. Results confirm that the proposed method can compute BME in previously unfeasible scenarios, facilitating a ranking among competing model versions for future model improvement.