Spectral induced polarization porosimetry

Revil, A.; Florsch, Nicolás; Camerlynck, Christian

doi:10.1093/gji/ggu180

Cited by 91 publications

(79 citation statements)

References 47 publications

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“…since, as discussed in several papers (Revil et al 2014a(Revil et al ,b, 2015Niu & Revil 2016), clean sandstones as well as clay-coated sandstones would exhibit such a behaviour. We search for the macroscopic parameters ρ 0,m , m m , c m and log 10 (τ m ) producing a Pelton resistivity model that fits the best the computed macroscopic IP response-what we call 'macroscopic optimization'.…”

Section: Principlementioning

confidence: 87%

“…For all the tests reported in this section, we choose the 'local' values ρ 0,l = 100 Ohm·m, m l = 0.1 V·V −1 , c l = 0.5 and log10(D l ) = −11 in eqs (14) and (15), based on preliminary tests carried out on real samples (see Section 4). We choose the local value c l = 0.5 based on the recent works by Revil et al (2014a) and Niu & Revil (2016); this is representative of a diffusive process (elementary Warburg model, see Revil et al 2014a). Note that in real rocks, ρ 0,l and m l are expected to vary from pore to pore (e.g.…”

Section: Principlementioning

confidence: 99%

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Upscaling of spectral induced polarization response using random tube networks

Maineult¹,

Revil

Camerlynck³

et al. 2017

Geophysical Journal International

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Section: Principlementioning

confidence: 87%

Section: Principlementioning

confidence: 99%

Upscaling of spectral induced polarization response using random tube networks

Maineult¹,

Revil

Camerlynck³

et al. 2017

Geophysical Journal International

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“…In the realm of the dynamic Stern layer model, the complex conductivity of a porous granular material without metallic grains is given by [Revil, 2013a, b;Revil et al, 2014a]…”

Section: Complex Conductivity Modelmentioning

confidence: 99%

“…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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130

191

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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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“…The RTS inverted from the IP decay potential can be used to analyze the pore size distribution of the strata, and then to make assessments on the rock permeability, the amount of oil or water storage, and so on (Liu et al 2014a, b;Rezaee et al 2006;Binley et al 2005;Zimmermann et al 2008;Gurin et al 2013;Beckett and Augarde 2013;Li et al 2010). A lot of research work has been carried out on the RTS, including inversion algorithms (Moody and Xia 2004;Xiao et al 2012;Chen et al 2013;Jang et al 2014;Florsch et al 2014), determining the appropriate number of relaxation time constants and its distribution (Tong et al 2004;Buecker and Hoerdt 2013;Revil et al 2014). The results of this work have a certain relevance for the inversion of IP RTS (Liu et al 2014a).…”

Section: Introductionmentioning

confidence: 99%

Research into the inversion of the induced polarization relaxation time spectrum based on the uniform amplitude sampling method

et al. 2016

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The induced polarization relaxation time spectrum (RTS) reflects the distribution of rock pore size, which is a key factor in estimating the oil or water storage capacity of strata. However, as the data acquisition and transmission abilities of well logging instruments are much limited due to the underground environment, it is necessary to explore suitable sampling methods which can be used to obtain an accurate RST with less sampling data. This paper presents a uniform amplitude sampling method (UASM), and compares it with the conventional uniform time sampling method (UTSM) and logarithm time sampling method (LTSM) in terms of the adaptability to different strata, RTS inversion accuracy, and stratum vertical resolution. Numerical simulation results show that the UASM can obtain high inversion accuracy of RTS with different kinds of pore size distribution formation, with high dynamic ranges of pore size, and with a small number of sampling points. The UASM, being able to adapt to the attenuation speed of polarization curve automatically, thus has the highest vertical resolution. The inversion results of rock samples also show that the UASM is superior to the UTSM and LTSM.

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Spectral induced polarization porosimetry

Cited by 91 publications

References 47 publications

Upscaling of spectral induced polarization response using random tube networks

Upscaling of spectral induced polarization response using random tube networks

Complex conductivity of soils

Research into the inversion of the induced polarization relaxation time spectrum based on the uniform amplitude sampling method

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