Complex Conductivity Measurements

Börner, F.

doi:10.1007/3-540-29387-6_4

Cited by 12 publications

(43 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using the ratio T∕Φ as an equivalent for the formation factor F, the modulus of surface conductivity can be formulated as Börner (1991Börner ( , 1992 showed that the real (σ 0 surf ) and imaginary (σ 0 0 surf ) parts of σ Ã surf linearly are related and introduced parameter l to represent the ratio of σ 0 0 surf to σ 0 surf . Therefore, assuming the validity of equation 4,…”

Section: The Dlp Modelmentioning

confidence: 99%

“…For example, Weller et al (2010b) showed how 114 samples from 10 independent data sets could be described well by a linear relationship between imaginary conductivity (σ 0 0 ) and the surface area to pore volume (S por ). Earlier evidence of such a relationship (Börner and Schön, 1991;Börner, 1992;Börner et al, 1996;Slater and Lesmes, 2002) inspired efforts to use IP measurements to predict permeability (Börner et al, 1996;Slater and Lesmes, 2002;Revil and Florsch, 2010;Weller et al, 2010a).…”

Section: Introductionmentioning

confidence: 96%

“…However, the contribution of the pore fluid chemical composition to the electrical double layer (EDL) polarization recorded with IP is less well defined, although several researchers have previously studied the controls of pore fluid salinity (Klein and Sill, 1982;Vinegar and Waxman, 1984;Lesmes and Frye, 2001;Revil and Skold, 2011;Weller et al, 2011), in addition to pH (Lesmes and Frye, 2001;Skold et al, 2011), and valence (Börner, 1992;Revil and Skold, 2011;Weller et al, 2011). A notable advance in the mechanistic understanding of fluid chemistry effects is the work of Vaudelet et al (2011), who combined a mechanistic model (discussed later) with a surface complexation model to predict the effect of differing sorption properties for the mineral surface for different cations.…”

Section: Introductionmentioning

confidence: 99%

“…One such early model is based on the polarization of the EDL surrounding the pores making up the porous medium, which is conceptualized as a bunch of capillary tubes (Börner, 1991(Börner, , 1992. This model, which we will refer to here as the "diffuse layer polarization (DLP) model" because the salinity dependence relates to a varying capacity of the diffuse layer, predicts an approximate dependence of σ 0 0 on the square root of the fluid electrical conductivity (σ w ) at low salinity.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Salinity dependence of complex conductivity of unconsolidated and consolidated materials: Comparisons with electrical double layer models

Weller

Slater

2012

GEOPHYSICS

View full text Add to dashboard Cite

We examined the dependence of imaginary conductivity (σ 0 0 ) on pore fluid conductivity (σ w ) for an extensive database of 67 samples acquired from twelve independent studies. We compared fitting of functions describing the salinity dependence of σ 0 0 for two models of the electrical double layer (EDL) polarization, both of which predict asymptotic behavior of σ 0 0 at high σ w . We define these models as the diffuse layer polarization (DLP) and Stern layer polarization (SLP) models based on the physical description of the salinity dependence of the surface polarization. We also examined the database for evidence of a high salinity decrease in σ 0 0 not predicted by either model. The dependence of σ 0 0 on σ w prior to the polarization plateau predicted by both models approximates a simple empirical power law with an average exponent of 0.34. The salinity dependence predicted by the DLP model adequately describes most data sets. A fitting parameter representing the high salinity σ 0 0 asymptote is strongly correlated (R 2 ¼ 0.822) with pore normalized specific surface (S por ). The SLP model describes well the observations when a recently proposed additive polarization term representing the contribution of the protons is included. In this case, the SLP model provides an excellent fit to the data sets, including a low salinity asymptote (in log-log conductivity space) seen in some samples. Predicted values of the fitting parameters of the SLP model generally are consistent with the values expected based on the theory; the fitting parameter describing the high salinity asymptote of the SLP model is also strongly correlated (R 2 ¼ 0.890) with S por . The SLP and DLP models neglect a high salinity decrease in the polarization that is observed in numerous data sets from independent studies. New data acquired on a sandstone sample demonstrate that this high salinity decrease is likely not attributable to the limited phase accuracy of earlier measurements.

show abstract

Section: The Dlp Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Salinity dependence of complex conductivity of unconsolidated and consolidated materials: Comparisons with electrical double layer models

Weller

Slater

2012

GEOPHYSICS

View full text Add to dashboard Cite

show abstract

“…Both the phase and the chargeability are essentially a measure of polarization relative to conduction. The complex conductivity and the chargeability are sensitive to parameters that can be used to describe the permeability (Börner 1992(Börner , 2006Kemna 2000;Revil and Florsch 2010) and the chemistry at the pore-water/mineral interface (Vaudelet et al 2011a, b). They are also very sensitive to the presence of metallic particles like pyrite (e.g., Pelton et al 1978).…”

Section: Introductionmentioning

confidence: 99%

Review: Some low-frequency electrical methods for subsurface characterization and monitoring in hydrogeology

et al. 2012

View full text Add to dashboard Cite

Low-frequency geoelectrical methods include mainly self-potential, resistivity, and induced polarization techniques, which have potential in many environmental and hydrogeological applications. They provide complementary information to each other and to in-situ measurements. The self-potential method is a passive measurement of the electrical response associated with the in-situ generation of electrical current due to the flow of pore water in porous media, a salinity gradient, and/or the concentration of redoxactive species. Under some conditions, this method can be used to visualize groundwater flow, to determine permeability, and to detect preferential flow paths. Electrical resistivity is dependent on the water content, the temperature, the salinity of the pore water, and the clay content and mineralogy. Time-lapse resistivity can be used to assess the permeability and dispersivity distributions and to monitor contaminant plumes. Induced polarization characterizes the ability of rocks to reversibly store electrical energy. It can be used to image permeability and to monitor chemistry of the pore water-minerals interface. These geophysical methods, reviewed in this paper, should always be used in concert with additional in-situ measurements (e.g. in-situ pumping tests, chemical measurements of the pore water), for instance through joint inversion schemes, which is an area of fertile on-going research.

show abstract

Permeability estimation from induced polarization: an evaluation of geophysical length scales using an effective hydraulic radius concept

Weller

Slater

2019

Near Surface Geophysics

View full text Add to dashboard Cite

Geophysical length scales defined from induced‐polarization measurements can be used in models of permeability (k) prediction. We explore the relative merit of different induced‐polarization parameters as proxies of an effective hydraulic radius (reff) that can be used to predict permeability from a modified Hagen–Poiseuille equation. Whereas geometrical measures of the hydraulic radius are good proxies of reff, the induced‐polarization measures are not well correlated with reff. However, a new proxy of reff that considers both imaginary conductivity and formation factor shows an improved correlation with reff. The resulting model enables a better quality of permeability prediction compared with the other geophysical length scales, but does not reach the predictive quality of the models based on geometrical length scales. The specific polarizability defined when incorporating the effect of the formation factor on imaginary conductivity appears to be independent of pore geometry, indicating that it is the correct parameter representing the role of the surface electrochemistry on the induced‐polarization effect. However, the joint dependence of induced‐polarization measurements on both the pore radius and the tortuosity and porosity of the interconnected pore network is a limitation to the widely explored use of induced‐polarization measurements to isolate surface properties from volumetric properties of the interconnected pore network.

show abstract

Complex Conductivity Measurements

Cited by 12 publications

References 40 publications

Salinity dependence of complex conductivity of unconsolidated and consolidated materials: Comparisons with electrical double layer models

Salinity dependence of complex conductivity of unconsolidated and consolidated materials: Comparisons with electrical double layer models

Review: Some low-frequency electrical methods for subsurface characterization and monitoring in hydrogeology

Permeability estimation from induced polarization: an evaluation of geophysical length scales using an effective hydraulic radius concept

Contact Info

Product

Resources

About