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- ItemMonitoring freshwater–saltwater interfaces with SAMOS – installation effects on data and inversion(Oxford : Wiley, 2020) Ronczka, Mathias; Günther, Thomas; Grinat, Michael; Wiederhold, HelgaA major problem for the freshwater supply of coastal regions is the intrusion of saltwater into aquifers. Due to extensive extraction of freshwater to suffice increasing drinking water demands and/or in periods of reduced groundwater recharge, the equilibrium state may be disturbed. The result is an upconing or movement of the fresh–saline groundwater interface, which reduces the local drinking water resources at coastal regions or islands. The saltwater monitoring system (SAMOS) is a vertical electrode chain installed in a backfilled borehole. It provides a solution to observe the transition zone in detail, both temporally and spatially. We present monitoring data of the first year from three locations - with different geological conditions that show disturbances in the resistivity distribution that result from the drilling processes. A clayey backfilling, for example, can lead to beam-like artefacts, and a mixed fluid within the backfilling changes its bulk resistivity, both leading to misinterpretations. We performed data inversion under cylindrically symmetrical conditions in full-space in order to separate these resistivity artefacts from the undisturbed background. Data inversion reveals that it is possible to separate drilling effects on the resistivity distribution from the undisturbed background. Thus, an interpretation of the natural transition zones can be made immediately after the installation. © 2020 The Authors. Near Surface Geophysics published by John Wiley & Sons Ltd on behalf of European Association of Geoscientists and Engineers.
- ItemUtilizing pre-polarization to enhance SNMR signals - Effect of imperfect switch-off(Oxford : Oxford Univ. Press, 2020) Hiller, Thomas; Dlugosch, Raphael; Müller-Petke, MikeSurface nuclear magnetic resonance (SNMR) is a well-established technique for the hydrogeological characterization of the subsurface up to depths of about 150 m. Recently, SNMR has been adapted to investigate also the shallow unsaturated zone with small surface loop setups. Due to the decreased volume, a pre-polarization (PP) field prior to the classical spin excitation is applied to enhance the measured response signal. Depending on the strength and orientation of the applied PP-field, the enhancement can often reach several orders of magnitude in the vicinity of the PP-loop. The theoretically achievable enhancement depends on the assumption of an adiabatic, that is perfect, switch-off of the corresponding PP-field. To study the effect of imperfect switch-off, we incorporate full spin dynamics simulations into the SNMR forward modelling. The affected subsurface volume strongly depends on the chosen PP switch-off ramp and the geometry of the loop setup. Due to the imperfect switch-off, the resulting SNMR sounding curves can have significantly decreased signal amplitudes. For comparison, the signal amplitudes of either a 1 ms exponential or linear switch-off ramp are reduced by 17 and 65 per cent, respectively. Disregarding this effect would therefore yield an underestimation of the corresponding subsurface water content of similar magnitude. © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of The Royal Astronomical Society.
- ItemQuantitative imaging of water, ice and air in permafrost systems through petrophysical joint inversion of seismic refraction and electrical resistivity data(Oxford : Oxford Univ. Press, 2019) Wagner, F.M.; Mollaret, C.; Günther, T.; Kemna, A.; Hauck, C.Quantitative estimation of pore fractions filled with liquid water, ice and air is crucial for a process-based understanding of permafrost and its hazard potential upon climate-induced degradation. Geophysical methods offer opportunities to image distributions of permafrost constituents in a non-invasive manner. We present a method to jointly estimate the volumetric fractions of liquid water, ice, air and the rock matrix from seismic refraction and electrical resistivity data. Existing approaches rely on conventional inversions of both data sets and a suitable a priori estimate of the porosity distribution to transform velocity and resistivity models into estimates for the four-phase system, often leading to non-physical results. Based on two synthetic experiments and a field data set from an Alpine permafrost site (Schilthorn, Bernese Alps and Switzerland), it is demonstrated that the developed petrophysical joint inversion provides physically plausible solutions, even in the absence of prior porosity estimates. An assessment of the model covariance matrix for the coupled inverse problem reveals remaining petrophysical ambiguities, in particular between ice and rock matrix. Incorporation of petrophysical a priori information is demonstrated by penalizing ice occurrence within the first two meters of the subsurface where the measured borehole temperatures are positive. Joint inversion of the field data set reveals a shallow air-rich layer with high porosity on top of a lower-porosity subsurface with laterally varying ice and liquid water contents. Non-physical values (e.g. negative saturations) do not occur and estimated ice saturations of 0–50 per cent as well as liquid water saturations of 15–75 per cent are in agreement with the relatively warm borehole temperatures between −0.5 and 3 ° C. The presented method helps to improve quantification of water, ice and air from geophysical observations.
- ItemRandom Noise Suppression of Magnetic Resonance Sounding Oscillating Signal by Combining Empirical Mode Decomposition and Time-Frequency Peak Filtering(New York, NY : IEEE, 2019) Lin, Tingting; Zhang, Yang; Muller-Petke, MikeMagnetic resonance sounding (MRS) signals are always corrupted by random noise. Although time-frequency peak filtering (TFPF) has been proven to be an effective method to suppress the random noise, it shows shortcomings when processing the oscillating high-frequency MRS signal at about 2 kHz. In this study, a new method combining empirical mode decomposition (EMD) and TFPF is proposed to overcome the TFPF limitation when processing the MRS oscillating signal. With the help of EMD decomposition characteristics, the random-noise-corrupted MRS oscillating signal is first decomposed into several different components which contain frequencies ranging from the highest to the lowest ones. Then, the components which do not have signal frequency are discarded to bring down the level of random noise. The residual components are further processed by TFPF, respectively, based on the theory of instantaneous frequency estimation and the property of noise accumulation. Finally, the de-noised result is obtained by reconstructing the processed components. The numerical simulations on synthetic signals embedded in both artificial noise and real noise show the combined method can improve the signal-to-noise ratios and reduce the uncertainties of signal parameters. In addition, the combined method is applied following a standard processing scheme in field data, and better results are also obtained.