DoE-based history matching for probabilistic uncertainty quantification of thermo-hydro-mechanical processes around heat sources in clay rocks

Buchwald, Jörg; Chaudhry, Aqeel Afzal; Yoshioka, Keita; Kolditz, Olaf; Attinger, Sabine; Nagel, Thomas

doi:10.1016/j.ijrmms.2020.104481

Cited by 12 publications

(14 citation statements)

References 28 publications

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“…A software written in Python is used to conduct the sensitivity analysis. It is based on a development by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig for sensitivity and uncertainty analyses in radioactive waste repository research by Buchwald et al (2020) and was adapted and further developed for application to BHEs. The Python software is coupled with the simulation software OGS via the application programming interface (API) ogs6py (Buchwald et al 2021).…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…These methods provide information about parameter influences based on the smallest possible representative number of parameter variations (Campolongo et al 2007). The OVAT method is used in this study as described by Buchwald et al (2020). Starting from a base setting of the parameters, two calculations are carried out for each parameter with its maximum and minimum values.…”

Section: Sensitivity Analysismentioning

confidence: 99%

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Global sensitivity analysis and uncertainty quantification for design parameters of shallow geothermal systems

Richter,

Lubashevsky,

Randow

et al. 2024

Geotherm Energy

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To improve the design process of geothermal systems, it is important to know which design parameters particularly affect the performance of the system. This article presents investigations on design parameters for borehole heat exchangers in the shallow subsurface. The study is based on numerical simulations with one double U-tube borehole heat exchanger and approximated models obtained using machine learning. As a result of the global sensitivity analysis, relevant parameters are identified and their respective influence on the performance of a borehole heat exchanger is compared. For example, according to this analysis, the three parameters with the highest sensitivity are the initial temperature, the heat demand and the share of the borehole heat exchanger that is surrounded by groundwater flow. Finally, the effects of uncertainties in the parameters identified as relevant for the design of a borehole heat exchanger are considered in an uncertainty quantification for a fictitious site. Uncertainties for regulatory compliance with respect to temperature limits as well as a large probability of oversizing the system were identified for the considered example. The results of the exemplary uncertainty quantification indicate that it has the potential to be a useful tool for planning practice.

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Section: Sensitivity Analysismentioning

confidence: 99%

Section: Sensitivity Analysismentioning

confidence: 99%

Global sensitivity analysis and uncertainty quantification for design parameters of shallow geothermal systems

Richter,

Lubashevsky,

Randow

et al. 2024

Geotherm Energy

View full text Add to dashboard Cite

show abstract

“…As the phase-field approach is costly regarding computation time, we studied the risk using a proxy model. For this purpose, we employed a workflow (Figure 1) similar to an approach used elsewhere to study uncertainties in the context of reservoir engineering [4] or waste repositories [7] based on a history matching and Design-of-Experiments Approach and also very similar to a proxy-based approach for studying sensitivity and uncertainty of fracture properties of nanocomposites with the phase field method [18]. As no detailed data on parameter distributions for our set of parameters was available, we used a uniform probability density function for all parameters.…”

Section: Description Of the Workmentioning

confidence: 99%

“…However, these fracturing simulations are computationally costly. Furthermore, computational costs become infeasible if we are to estimate the sensitivity of the parameters and assess risks under various scenarios, For this reason, we have embedded the fracturing simulation in a risk analysis tool, the Design of Experiments (DoE) [4,5,6,7], which develops a computationally inexpensive proxy model based on a reduced set of significant parameters known as heavy hitters.…”

Section: Introductionmentioning

confidence: 99%

Clay–rock fracturing risk assessment under high gas pressures in repository systems

Mollaali

Buchwald

Montoya

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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At the interface between the steel canister and the bentonite in a nuclear waste repository, we expect generation of hydrogen gas because of corrosion processes. The pressurized gas might fracture the engineered or natural clay barrier system, enhancing radionuclide transport into the geosphere. To assess the long-term integrity of the clay host rock under various conditions and scenarios, we need a large number of numerical simulations. However, a simulation tool for complex fracture propagation is often prohibitively expensive to run many realizations. Here, we developed a risk analysis tool based on the Design of Experiments to overcome the computational challenges by generating a computationally inexpensive proxy fracture model using a set of critical factors known as heavy hitters. We provided parameters and their probability distributions that are subject to uncertainty, as well as an objective function that assesses the risk of fracturing due to high gas pressures. Through various scenarios, we found that the fracture toughness dominates the impact on the risk.

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“…Second, we used an LHS-based surrogate approach (Buchwald et al 2020). Here, a number of samples of NGWM input parameter vectors are selected at random via the LHS method.…”

Section: Application Example: Calibration With Bo Example Descriptionmentioning

confidence: 99%

r2ogs5: Calibration of Numerical Groundwater Flow Models with Bayesian Optimization in R

2022

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Large-scale and high-resolution groundwater models are currently becoming increasingly important in order to clarify the extent to which climate trends and extreme weather affect the groundwater balance regionally. As a result, the parameterization of groundwater models is becoming more detailed and more complex, making conventional calibration methods too time-consuming. Moderating the computational demand to find optimal solutions for the resulting potentially multi-modal objective function requires intelligent and efficient global optimization methods. Moreover, the increasing use of modern scripting languages R and Python to craft environmental analysis workflows calls to integrate groundwater flow simulators in such. Here we introduce and exemplify r2ogs5, a tool that integrates version 5 of the open-source simulation software OpenGeoSys into the programming language R. r2ogs5 allows for calibration of numerical groundwater flow models with a sequential model-based optimization approach that combines Bayesian optimization (BO) with surrogate modeling. Here, we describe the structure and function of r2ogs5 as well as the implemented calibration method. We then demonstrate the calibration method by calibrating 4 and 12 parameters of two simple groundwater flow models. The results indicate that this method needs fewer runs of the groundwater flow model than conventional gradient search and Latin hypercube sampling in case of the 12 parameter model. We believe that our method offers the potential to calibrate computationally expensive groundwater flow models. r2ogs5 supports groundwater flow modelers to access the statistical analysis and visualization capabilities of the R language and is a valuable tool for geoscientists already using R.

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DoE-based history matching for probabilistic uncertainty quantification of thermo-hydro-mechanical processes around heat sources in clay rocks

Cited by 12 publications

References 28 publications

Global sensitivity analysis and uncertainty quantification for design parameters of shallow geothermal systems

Global sensitivity analysis and uncertainty quantification for design parameters of shallow geothermal systems

Clay–rock fracturing risk assessment under high gas pressures in repository systems

r2ogs5: Calibration of Numerical Groundwater Flow Models with Bayesian Optimization in R

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