Not only is water the source of life, but access to clean drinking water is acknowledged to be a human right. Nuclear magnetic resonance (NMR) can help to gather detailed information about the extent and hydraulic properties of an aquifer which are essential information for a sustainable use. The main objectives of this thesis are (i) to revise the prediction of hydraulic conductivities including coarse-grained unconsolidated sediments using NMR and (ii) to develop a robust inversion approach for surface NMR to estimate the 2D distribution of water content and NMR relaxation time in the subsurface. The Kozeny-Godefroy model is introduced which allows for an advanced prediction of hydraulic conductivity from NMR measurements. The model replaces the empirical factors in known relations with physical, structural and NMR intrinsic parameters. It additionally accounts for the relaxation of protons in the bulk water and in pores which are controlled by diffusion limited conditions. A new sophisticated inversion approach for 2D surface NMR surveys is presented. It considers the entire recorded data set at once allowing to determine the 2D distribution of water content and NMR relaxation time in the subsurface. The outstanding features of this new inversion approach are its 2D capability, robustness in spite of noisy data and the potential to distinguish aquifers of different lithology due to their NMR relaxation times. Finally, the results of an extensive hydrogeophysical study at the Schillerslage test site, including surface, Earth’s field, borehole and laboratory NMR measurements, are presented, compared and discussed. The obtained NMR parameters are used for the prediction of 1D and 2D distributions of the hydraulic conductivity in the subsurface. In conclusion, this thesis demonstrates that the estimation of hydraulic conductivities in aquifers using NMR can be improved using the Kozeny-Godefroy model. The presented new inversion approach increases the range of application for surface NMR to 2D targets. This allows obtaining 2D images of the hydraulic conductivity distribution in the subsurface.
|Advisor:||Yaramanci, UgurMüller-Petke, Mike|
|School:||Technische Universitaet Berlin (Germany)|
|Source:||DAI-C 81/1(E), Dissertation Abstracts International|
|Subjects:||Hydrologic sciences, Hydraulic engineering, Geophysics|
|Keywords:||Groundwater, Hydraulic conductivity|
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