Study of the geothermal potential in the area surrounding Ebensee for salt production

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Study of the geothermal potential in the area surrounding Ebensee for salt production. / Riegler, Lukas.
2021.

Publikationen: Thesis / Studienabschlussarbeiten und HabilitationsschriftenMasterarbeit

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@mastersthesis{ab66656d75be478b9e58debde5af0239,
title = "Study of the geothermal potential in the area surrounding Ebensee for salt production",
abstract = "With the steadily growing demand for energy and the simultaneously decreasing amount of available fossil fuels, the industry is forced to look for alternative supply options. One of these possibilities is the use of geothermal energy, which has different areas of applications depending on the existing temperature range. Since the salt production requires a large amount of energy, the use of renewable energy, which also has low CO2 emissions, is a welcome alternative. The aim of this study was to determine whether it would be feasible to install a geothermal well in the area surrounding Ebensee. Therefore, a schematic borehole was planned based on the underlying geology. Especially, the geothermal parameters, specific heat capacity, thermal conductivity and density, of the distinct formations are of interest, since these are the input variables for the different simulations. After the completion has been selected, different tubing insulation materials have been analyzed to minimize heat losses as good as possible during the production. The simulation was carried out using the WellUse software and compared different insulation materials and different insulation thicknesses. Next a matrix simulation has been done to create a decision matrix. Based on this matrix the most relevant operating conditions are chosen in order to limit the size of the simulation and to prevent results that present no significance. The next step was to generate random samples of the respective formations. For this purpose, a Gibbs Sampler is used, which is a subclass of the Markov Chain Monte Carlo Simulation. This algorithm uses the conditional probability of the input variables to generate new random samples which are correlated to each other. The input variables for this simulation are the mean values and the standard deviation of the thermodynamic parameters from the individual rock formations. These new random samples are then fed back into the WellUse simulation to check the stability of the simulation. The obtained results were compared and the statistics elaborated. Lastly, a recommendation is given which operating conditions should be used together with the selected insulation material and the development of the well throughout the years is presented.",
keywords = "Geothermal Energy, MCMC, Gibbs Sampler, Geothermische Energie, MCMC, Gibbs Sampler",
author = "Lukas Riegler",
note = "embargoed until null",
year = "2021",
language = "English",
school = "Montanuniversitaet Leoben (000)",

}

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TY - THES

T1 - Study of the geothermal potential in the area surrounding Ebensee for salt production

AU - Riegler, Lukas

N1 - embargoed until null

PY - 2021

Y1 - 2021

N2 - With the steadily growing demand for energy and the simultaneously decreasing amount of available fossil fuels, the industry is forced to look for alternative supply options. One of these possibilities is the use of geothermal energy, which has different areas of applications depending on the existing temperature range. Since the salt production requires a large amount of energy, the use of renewable energy, which also has low CO2 emissions, is a welcome alternative. The aim of this study was to determine whether it would be feasible to install a geothermal well in the area surrounding Ebensee. Therefore, a schematic borehole was planned based on the underlying geology. Especially, the geothermal parameters, specific heat capacity, thermal conductivity and density, of the distinct formations are of interest, since these are the input variables for the different simulations. After the completion has been selected, different tubing insulation materials have been analyzed to minimize heat losses as good as possible during the production. The simulation was carried out using the WellUse software and compared different insulation materials and different insulation thicknesses. Next a matrix simulation has been done to create a decision matrix. Based on this matrix the most relevant operating conditions are chosen in order to limit the size of the simulation and to prevent results that present no significance. The next step was to generate random samples of the respective formations. For this purpose, a Gibbs Sampler is used, which is a subclass of the Markov Chain Monte Carlo Simulation. This algorithm uses the conditional probability of the input variables to generate new random samples which are correlated to each other. The input variables for this simulation are the mean values and the standard deviation of the thermodynamic parameters from the individual rock formations. These new random samples are then fed back into the WellUse simulation to check the stability of the simulation. The obtained results were compared and the statistics elaborated. Lastly, a recommendation is given which operating conditions should be used together with the selected insulation material and the development of the well throughout the years is presented.

AB - With the steadily growing demand for energy and the simultaneously decreasing amount of available fossil fuels, the industry is forced to look for alternative supply options. One of these possibilities is the use of geothermal energy, which has different areas of applications depending on the existing temperature range. Since the salt production requires a large amount of energy, the use of renewable energy, which also has low CO2 emissions, is a welcome alternative. The aim of this study was to determine whether it would be feasible to install a geothermal well in the area surrounding Ebensee. Therefore, a schematic borehole was planned based on the underlying geology. Especially, the geothermal parameters, specific heat capacity, thermal conductivity and density, of the distinct formations are of interest, since these are the input variables for the different simulations. After the completion has been selected, different tubing insulation materials have been analyzed to minimize heat losses as good as possible during the production. The simulation was carried out using the WellUse software and compared different insulation materials and different insulation thicknesses. Next a matrix simulation has been done to create a decision matrix. Based on this matrix the most relevant operating conditions are chosen in order to limit the size of the simulation and to prevent results that present no significance. The next step was to generate random samples of the respective formations. For this purpose, a Gibbs Sampler is used, which is a subclass of the Markov Chain Monte Carlo Simulation. This algorithm uses the conditional probability of the input variables to generate new random samples which are correlated to each other. The input variables for this simulation are the mean values and the standard deviation of the thermodynamic parameters from the individual rock formations. These new random samples are then fed back into the WellUse simulation to check the stability of the simulation. The obtained results were compared and the statistics elaborated. Lastly, a recommendation is given which operating conditions should be used together with the selected insulation material and the development of the well throughout the years is presented.

KW - Geothermal Energy

KW - MCMC

KW - Gibbs Sampler

KW - Geothermische Energie

KW - MCMC

KW - Gibbs Sampler

M3 - Master's Thesis

ER -