The Application of Spectral Induced Polarization to Determination of Hydraulic Conductivity

<p>Spectral Induced Polarization (SIP) is a geophysical technique that measures the frequency dependence of the electrical conductivity of a material. This thesis is an attempt to investigate the potential of using SIP as a proxy to predict the hydraulic conductivity of New Zealand shallow coastal aquifers. SIP measurements were made on sand samples that are typical of New Zealand coastal aquifers with a custom built impedance spectrometer and sample holder allowing the measurement of a phase difference as small a milliradian. Even though the relaxation time shows a small dependence on pore fluid conductivity, especially at lower pore fluid conductivities, this variation is not serious enough to affect the hydraulic conductivity estimation at the field scale, but could be significant in the investigation of mechanisms that cause polarization in porous media. Measurements on sieved fractions of sand established that there is an excellent correlation between the Cole-Cole relaxation time constant and grain size. The Cole-Cole relaxation time constant is very sensitive to the grain size distribution. Hydraulic conductivity predictions were attempted using various existing models. While the results are encouraging, it looks like there may not be a single universal model to predict hydraulic conductivity using SIP response. When a correction term in the form of a multiplication constant is used, all the tested models seem to make very good predictions. But the constants calculated by fitting to the measured data could be applicable only to the type of materials studied. The dependence of the existing models on quantities like counterion diffusion coefficient, electrical formation factor and porosity makes hydraulic conductivity prediction challenging as these quantities are difficult to measure accurately in a field setting. Nevertheless it is concluded that SIP can be successfully applied to study hydraulic conductivity of New Zealand shallow coastal aquifers.</p>

The Application of Spectral Induced Polarization to Determination of Hydraulic Conductivity

<p>Spectral Induced Polarization (SIP) is a geophysical technique that measures the frequency dependence of the electrical conductivity of a material. This thesis is an attempt to investigate the potential of using SIP as a proxy to predict the hydraulic conductivity of New Zealand shallow coastal aquifers. SIP measurements were made on sand samples that are typical of New Zealand coastal aquifers with a custom built impedance spectrometer and sample holder allowing the measurement of a phase difference as small a milliradian. Even though the relaxation time shows a small dependence on pore fluid conductivity, especially at lower pore fluid conductivities, this variation is not serious enough to affect the hydraulic conductivity estimation at the field scale, but could be significant in the investigation of mechanisms that cause polarization in porous media. Measurements on sieved fractions of sand established that there is an excellent correlation between the Cole-Cole relaxation time constant and grain size. The Cole-Cole relaxation time constant is very sensitive to the grain size distribution. Hydraulic conductivity predictions were attempted using various existing models. While the results are encouraging, it looks like there may not be a single universal model to predict hydraulic conductivity using SIP response. When a correction term in the form of a multiplication constant is used, all the tested models seem to make very good predictions. But the constants calculated by fitting to the measured data could be applicable only to the type of materials studied. The dependence of the existing models on quantities like counterion diffusion coefficient, electrical formation factor and porosity makes hydraulic conductivity prediction challenging as these quantities are difficult to measure accurately in a field setting. Nevertheless it is concluded that SIP can be successfully applied to study hydraulic conductivity of New Zealand shallow coastal aquifers.</p>

Spectral Induced Polarization imaging to investigate an ice-rich mountain permafrost site in Switzerland

Spectral induced polarization (SIP) measurements were collected at the Lapires talus slope, a long-term permafrost monitoring site located in the Western Swiss Alps, to assess the potential of the frequency dependence (within the frequency range of 0.1–225 Hz) of the electrical polarization response of frozen rocks for an improved permafrost characterization. The aim of our investigation was to (a) find a field protocol that provides SIP imaging data sets less affected by electromagnetic coupling and easy to deploy in rough terrains, (b) cover the spatial extent of the local permafrost distribution, and (c) evaluate the potential of the spectral data to discriminate between different substrates and spatial variations in the volumetric ice content within the talus slope. To qualitatively assess data uncertainty, we analyze the misfit between normal and reciprocal (N&amp;R) measurements collected for all profiles and frequencies. A comparison between different cable setups reveals the lowest N&amp;R misfits for coaxial cables and the possibility to collect high-quality SIP data in the range between 0.1–75 Hz. We observe an overall smaller spatial extent of the ice-rich permafrost body compared to its assumed distribution from previous studies. Our results further suggest that SIP data help to improve the discrimination between ice-rich permafrost and unfrozen bedrock in ambiguous cases based on their characteristic spectral behavior, with ice-rich areas showing a stronger polarization towards higher frequencies in agreement with the well-known spectral response of ice.

Broadband Spectral Induced Polarization for the detection of Permafrost and an approach to ice content estimation – A Case study from Yakutia, Russia

The reliable detection of subsurface ice using non-destructive geophysical methods is an important objective in permafrost research. Furthermore, the ice content of the frozen ground is an essential parameter for further interpretation, for example in terms of risk analysis, e.g. for the description of permafrost carbon feedback by thawing processes. The High-Frequency Induced Polarization method (HFIP) enables the measurement of the frequency dependent electrical signal of the subsurface. In contrast to the well-established Electrical Resistivity Tomography (ERT), the usage of the full spectral information provides additional physical parameters of the ground. As the electrical properties of ice exhibit a strong characteristic behaviour in the frequency range between 100 Hz and 100 kHz, HFIP is in principle suitable to estimate ice content. Here, we present methodological advancements of the HFIP method and suggest an explicit procedure for ice content estimation. A new measuring device, the Chameleon-II (Radic Research), was used for the first time. It was designed for the application of Spectral Induced Polarization over a wide frequency range and is usable under challenging conditions, for example in field sites under periglacial influence and the presence of permafrost. Amongst other improvements, compared to a previous generation, the new system is equipped with longer cables and larger power, such that we can now achieve larger penetration depths up to 10 m. Moreover, it is equipped with technology to reduce electromagnetic coupling effects which can distort the desired subsurface signal. The second development is a method to estimate ice content quantitatively from five Cole-Cole parameters obtained from spectral two-dimensional inversion results. The method is based on a description of the subsurface as a mixture of two components (matrix and ice) and uses a previously suggested relationship between frequency-dependent electrical permittivity and ice content. Measurements on a permafrost site near Yakutsk, Russia, were carried out to test the entire procedure under real conditions at the field scale. We demonstrate that the spectral signal of ice can clearly be identified even in the raw data, and show that the spectral 2-D inversion algorithm is suitable to obtain the multidimensional distribution of electrical parameters. The parameter distribution and the estimated ice content agree reasonably well with previous knowledge of the field site from borehole and geophysical investigations. We conclude that the method is able to provide quantitative ice content estimates, and that relationships that have been tested in the laboratory may be applied at the field scale.