Modeling the Nonlinear–To–Linear Relationship Between Bulk and Pore Water Electrical Conductivity in Saturated Porous Media Using a Padé Approximant

Abstract A petrophysical model that accurately relates bulk electrical conductivity (σ) to pore fluid conductivity (σ w ) is critical to the interpretation of geophysical measurements. Classical models are either only applicable over a limited salinity regime or incorrectly explain the nonlinear‐to‐linear behavior of the σ(σ w ) relationship. In this study, asymptotic limits at zero and infinite salinity are first established in which, σ is expressed as a linear function of σ w with four parameters: cementation exponent ( m ), the equivalent value of volumetric surface electrical conductivity (σ s ), the volume fraction of overlapped diffuse layer (ϕ od ) and parameter χ representing the ratio of the volume fraction of the water phase to that of the solid phases in the surface conduction pathway. Subsequently, we bridge the gap between the two extremes by employing the Padé approximant (PA). Given that parameter χ exhibits a marginal influence on the σ(σ w ) curve, based on measurements for 15 samples, we identify its optimal value to be 0.4. After setting the optimal value of χ , we proceed to evaluate the performance of the PA model by comparing its estimates and estimates made by two existing models to measured values from 27 rock samples and eight sediment samples. The comparison confirms that the PA model estimates are more accurate than estimates made by existing models, particularly at low salinity and for samples with higher cation exchange capacity. The PA model is advantageous in scenarios involving the interpretation of electrical data in freshwater environments.

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Publication Details

Journal
Water Resources Research
Published
2024-12-01
DOI
https://doi.org/10.1029/2024wr037935
Citations
2
Primary Topic
Geophysical and Geoelectrical Methods
Type
article
Field-Weighted Citation Impact
1.07

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article

Modeling the Nonlinear–To–Linear Relationship Between Bulk and Pore Water Electrical Conductivity in Saturated Porous Media Using a Padé Approximant

Robert Horton, Andrew Binley, Joshua L. Heitman, Yongwei Fu
2 citations
Water Resources Research
Geophysical and Geoelectrical Methods
1.07
article

Modeling the Nonlinear–To–Linear Relationship Between Bulk and Pore Water Electrical Conductivity in Saturated Porous Media Using a Padé Approximant

Robert Horton, Andrew Binley, Joshua L. Heitman, Yongwei Fu
article en
2 citations

Abstract

Abstract A petrophysical model that accurately relates bulk electrical conductivity (σ) to pore fluid conductivity (σ w ) is critical to the interpretation of geophysical measurements. Classical models are either only applicable over a limited salinity regime or incorrectly explain the nonlinear‐to‐linear behavior of the σ(σ w ) relationship. In this study, asymptotic limits at zero and infinite salinity are first established in which, σ is expressed as a linear function of σ w with four parameters: cementation exponent ( m ), the equivalent value of volumetric surface electrical conductivity (σ s ), the volume fraction of overlapped diffuse layer (ϕ od ) and parameter χ representing the ratio of the volume fraction of the water phase to that of the solid phases in the surface conduction pathway. Subsequently, we bridge the gap between the two extremes by employing the Padé approximant (PA). Given that parameter χ exhibits a marginal influence on the σ(σ w ) curve, based on measurements for 15 samples, we identify its optimal value to be 0.4. After setting the optimal value of χ , we proceed to evaluate the performance of the PA model by comparing its estimates and estimates made by two existing models to measured values from 27 rock samples and eight sediment samples. The comparison confirms that the PA model estimates are more accurate than estimates made by existing models, particularly at low salinity and for samples with higher cation exchange capacity. The PA model is advantageous in scenarios involving the interpretation of electrical data in freshwater environments.

Water Resources ResearchVol. 60(12)
North Carolina State University (US), Iowa State University (US), China Agricultural University (CN), Lancaster University (GB)
National Science Foundation, U.S. Department of Agriculture, National Natural Science Foundation of China, National Institute of Food and Agriculture
Clean water and sanitation
Openalex Percentile: Top 23%
Geophysical and Geoelectrical Methods
1.07
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