Low-frequency complex conductivity of sandy and clayey materials

The complex conductivity of soils remains poorly known despite the growing importance of this method in hydrogeophysics. In order to fill this gap of knowledge, we investigate the complex conductivity of 71 soils samples (including four peat samples) and one clean sand in the frequency range 0.1 Hz to 45 kHz. The soil samples are saturated with six different NaCl brines with conductivities (0.031, 0.53, 1.15, 5.7, 14.7, and 22 S m−1, NaCl, 25°C) in order to determine their intrinsic formation factor and surface conductivity. This data set is used to test the predictions of the dynamic Stern polarization model of porous media in terms of relationship between the quadrature conductivity and the surface conductivity. We also investigate the relationship between the normalized chargeability (the difference of in‐phase conductivity between two frequencies) and the quadrature conductivity at the geometric mean frequency. This data set confirms the relationships between the surface conductivity, the quadrature conductivity, and the normalized chargeability. The normalized chargeability depends linearly on the cation exchange capacity and specific surface area while the chargeability shows no dependence on these parameters. These new data and the dynamic Stern layer polarization model are observed to be mutually consistent. Traditionally, in hydrogeophysics, surface conductivity is neglected in the analysis of resistivity data. The relationships we have developed can be used in field conditions to avoid neglecting surface conductivity in the interpretation of DC resistivity tomograms. We also investigate the effects of temperature and saturation and, here again, the dynamic Stern layer predictions and the experimental observations are mutually consistent.

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“…This solution is changed very regularly (e.g., Revil et al [2013Revil et al [ , 2014a). Equilibrium was reached in several weeks.…”

Section: Complex Conductivity Measurementsmentioning

confidence: 99%

Complex conductivity of soils

Revil

Coperey

Shao

et al. 2017

Water Resources Research

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“…According to Revil [2012], f % 0.90 for illite and smectite (the salinity dependence of f is discussed in Revil et al [2013c]). The surface conductivity and the Dukhin number are defined as the real part of the complex surface conductivity and the real part of the complex Dukhin number,…”

Section: à3mentioning

confidence: 99%

“…Indeed, a number of recent geophysical studies [Kowalsky et al, 2011;Gasperikova et al, 2012;Revil et al, 2013a] have focused on determining the extent of the plumes associated with contaminant migration from the former S-3 disposal ponds as well as evaluating the potential for natural attenuation of these plumes. Recently, Revil et al [2013aRevil et al [ , 2013bRevil et al [ , 2013c have pointed out that the interpretation of resistivity data cannot be properly done without taking into account the surface conductivity associated with the presence of clay minerals. That said, the Revil et al [2013a] study was conducted with samples from the uncontaminated background site keeping only the fine fraction of the saprolite and using a simple NaCl solution as the leachate to conduct the experiments.…”

Section: Introductionmentioning

confidence: 99%

Geochemical and geophysical responses during the infiltration of fresh water into the contaminated saprolite of the Oak Ridge Integrated Field Research Challenge site, Tennessee

Revil

Karaoulis

et al. 2013

Water Resources Research

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[1] At the Oak Ridge Integrated Field Research Challenge (IFRC) site, Tennessee, the saprolitic aquifer was contaminated by leaks from the former S-3 disposal ponds between 1951 and 1983. The chemistry of the contaminant plume is also episodically impacted by fresh meteoritic water infiltrating vertically from a shallow variably saturated perched zone and the ditch surrounding the former S-3 ponds. We performed a column experiment using saprolite from the contaminated aquifer to understand the geochemical and complex electrical conductivity signatures associated with such events. The changes in the pH and pore water ionic strength are responsible for measurable changes in both the in-phase and quadrature conductivities. The pore water conductivity can be related to the nitrate concentration (the main ionic species in the plume) while the release of uranium is controlled by the pH. We developed a simple model to determine the pore water conductivity and pH from the recorded complex conductivity. This model is applied to time-lapse resistivity data at the IFRC site. Time-lapse inversion of resistivity data, performed with an active time constrain approach, shows the occurrence of an infiltration event during the winter of 2008-2009 with a dilution of the pore water chemistry and an increase of the pH. A simple numerical simulation of the infiltration of fresh water into the unconfined contaminated aquifer is consistent with this scenario.

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“…highly compacted, saturated clay formations with well-aligned clay particles) and when the interstitial water phase has a high resistivity (e.g. Wildenschild et al 2000;Glover 2010;Ponziani et al 2012;Revil et al 2013). …”

Section: Surface Conduction Effectsmentioning

confidence: 99%

Monitoring and characterisation of sand-mud sedimentation processes

et al. 2016

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Estuaries and tidal inlets are often characterised by the presence of both cohesive and non-cohesive sediments. Knowledge of the sedimentation behaviour of sand-mud mixtures is therefore crucial to the understanding and prediction of the time-dependent structure (i.e. mixed or segregated), composition and erodibility of sediment bed deposits developing within these environments. In the current study, a series of settling column tests are conducted to investigate the hindered settling and initial bed consolidation phases of a range of sandclay mixtures to determine the parametric conditions under which bed segregation occurs. A new, non-invasive, electrical resistivity measurement technique is employed to capture both temporal and spatial changes in the density, porosity and composition of the evolving sand-clay bed deposits, complimented by time-lapsed images of the sedimentation process within the column. The results show that the formation of segregated (sand-clay) bed layers with bed deposits is largely controlled by the initial fractional composition (i.e. relative sand and clay concentrations). Specifically, mixtures with low clay contents are shown to form well-defined (sandclay) layer segregation within the resulting deposits, while higher clay contents result in more transitional segregation patterns or no layer segregation (for very high clay concentrations). The physical mechanisms under which these different segregation types can be generated are illustrated through predictions from an existing polydisperse hindered settling model. This model indicates that the degree of bed segregation, and time scale over which this occurs, correlates well with the difference in predicted hindered settling characteristics and upward displacements associated with the sand and clay fractions, respectively. In this regard, the new experimental dataset provides validation for the polydisperse model (for the first time), with the combined data and model predictions providing new insight into mixed (sand-clay) sedimentation processes.

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Low-frequency complex conductivity of sandy and clayey materials

Cited by 66 publications

References 50 publications

Complex conductivity of soils

Complex conductivity of soils

Geochemical and geophysical responses during the infiltration of fresh water into the contaminated saprolite of the Oak Ridge Integrated Field Research Challenge site, Tennessee

Monitoring and characterisation of sand-mud sedimentation processes

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