Complex resistivity tomography for environmental applications

Kemna, Andreas; Binley, Andrew; Ramirez, Abelardo; Daily, William

doi:10.1016/s1385-8947(99)00135-7

Cited by 157 publications

(107 citation statements)

References 9 publications

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“…This, however, would have to be done for each temperature and consequently represents a time-consuming procedure. Since we are interested here only in the EC response, we followed a much simpler approach and removed both MW polarization and EM effects from the spectral response by fitting a superposition of Cole-Cole functions to the data [e.g., Pelton et al, 1978;Major and Silic, 1981;Brown, 1985;Kemna et al, 2000], expressed in terms of complex resistivity as…”

Section: Data Processingmentioning

confidence: 99%

Dependence of spectral‐induced polarization response of sandstone on temperature and its relevance to permeability estimation

Zisser¹,

Kemna²,

Nover³

2010

J. Geophys. Res.

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[1] The possibility to estimate permeability from the electrical spectral induced polarization (SIP) response might be the most important benefit offered by SIP measurements. It can thus be deduced that, in the future, SIP measurements will be carried out more frequently at the field scale or in a well-logging context to estimate permeability. In the shallow subsurface, however, the temperature generally exhibits seasonal variability, and in the deeper subsurface, it usually increases with depth. Hence, knowledge about the dependence of the SIP response on temperature is necessary in order to avoid possible misinterpretation of datasets impacted by thermal effects. In our study, we present a semiempirical framework to describe the temperature dependence of the SIP response. We briefly introduce the SIP response and its relation to permeability in terms of an electrochemical polarization mechanism and combine this formulation with relationships for the dependence of ionic mobility on temperature. We compare the predictions of our formulation with the experimental data from SIP measurements performed on sandstone at temperatures from 0°C to 80°C. The measured SIP response was transformed into a relaxation time distribution, using the empirical Cole-Cole model and a regularized Debye decomposition procedure. The SIP response was found to be in good agreement with the theoretical model. The temperature dependence of both direct current conductivity and relaxation time is controlled mainly by the dependence of ionic mobility on temperature, and the shape of the relaxation time distribution of the investigated sandstone is almost independent of temperature. The temperature effect on the SIP response can therefore be easily corrected.Citation: Zisser, N., A. Kemna, and G. Nover (2010), Dependence of spectral-induced polarization response of sandstone on temperature and its relevance to permeability estimation,

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Section: Data Processingmentioning

confidence: 99%

Dependence of spectral‐induced polarization response of sandstone on temperature and its relevance to permeability estimation

Zisser¹,

Kemna²,

Nover³

2010

J. Geophys. Res.

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“…Numerical inversion of these data is undertaken to produce tomograms of subsurface electrical property distributions. Examples of electrical impedance imaging procedures are given by Cho (1996), Ramirez et al (1999), Daily et al (2000) and Kemna et al (2000).…”

Section: Electrical Impedance Tomographymentioning

confidence: 99%

Noninvasive monitoring of DNAPL migration through a saturated porous medium using electrical impedance tomography

Chambers

Loke

Ogilvy

et al. 2004

Journal of Contaminant Hydrology

113

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Electrical impedance tomography was used to monitor the movement of a fluorinated hydrocarbon DNAPL through a saturated porous medium within a laboratory column. Impedance measurements were made using a horizontal plane of twelve electrodes positioned at regular intervals around the centre of the column. A 2D inversion algorithm, which incorporated the cylindrical geometry of the column, was used to reconstruct resistivity and phase images from the measured data. Differential time-lapse images of DNAPL movement past the plane of electrodes were generated by the cell-bycell subtraction of resistivity and phase baseline models from those associated with the DNAPL release stage of the experiment.The DNAPL pulse was clearly delineated as resistive anomalies in the differential time-lapse resistivity images. The spatial extent of the resistive anomalies indicated that, in addition to vertical migration, some lateral spreading of the DNAPL had occurred. Residual contamination could be detected after quasi-static conditions were re-established. Residual DNAPL saturation was estimated from the resistivity model data by applying Archie's second equation. Despite significant measured phase changes due to DNAPL contamination, the differential phase images revealed only weak anomalies associated with DNAPL flow; these anomalies could be seen only in the initial stages of the experiment during peak flow through the plane of electrodes.

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“…There are two methods used to calculate I.P. effects, the perturbation (Oldenburg and Li, 1994) and the complex resistivity (Kenma et al, 2000) methods. The first method assumes the intrinsic I.P.…”

Section: Discussionmentioning

confidence: 99%

“…The second I.P. model calculation method is to treat the conductivity as a complex quantity with real and imaginary components (Kenma et al, 2000), which is given by…”

Section: Discussionmentioning

confidence: 99%