Induced polarization as a tool to non-intrusively characterize embankment hydraulic properties

Ahmed, A. Soueid; Revil, A.; Abdulsamad, F.; Steck, B.; Vergniault, Christophe; Guihard, Vincent

doi:10.1016/j.enggeo.2020.105604

Cited by 22 publications

(11 citation statements)

References 44 publications

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“…As the ionic concentrations are higher in the EDL, there is also a contribution from the surface of the grains, called the surface conductivity σ sur f (S m −1 ). This contribution is especially measurable for low ionic concentrations, e.g., [7,44,45]. The bulk and surface conductivities can be considered as parallel components of the sample EC, e.g., [46][47][48],…”

Section: The Pore Water Ecmentioning

confidence: 99%

Interpreting Self-Potential Signal during Reactive Transport: Application to Calcite Dissolution and Precipitation

Rembert

Jougnot

Luquot

et al. 2022

Water

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Geochemistry and reactive transport play a critical role in many fields. In particular, calcite dissolution and precipitation are chemical processes occurring ubiquitously in the Earth’s subsurface. Therefore, understanding and quantifying them are necessary for various applications (e.g., water resources, reservoirs, geo-engineering). These fundamental geochemical processes can be monitored using the self-potential (SP) method, which is sensitive to pore space changes, water mineralization, and mineral–solution interactions. However, there is a lack of physics-based models linking geochemical processes to the SP response. Thus, in this study, we develop the first geochemical–geophysical fully coupled multi-species numerical workflow to predict the SP electrochemical response. This workflow is based on reactive transport simulation and the computation of a new expression for the electro-diffusive coupling for multiple ionic species. We apply this workflow to calcite dissolution and precipitation experiments, performed for this study and focused on SP monitoring alternating with sample electrical conductivity (EC) measurements. We carried out this experimental part on a column packed with calcite grains, equipped for multichannel SP and EC monitoring and subjected to alternating dissolution or precipitation conditions. From this combined experimental investigation and numerical analysis, the SP method shows clear responses related to ionic concentration gradients, well reproduced with electro-diffusive simulation, and no measurable electrokinetic coupling. This novel coupled approach allows us to determine and predict the location of the reactive zone. The workflow developed for this study opens new perspectives for SP applications to characterize biogeochemical processes in reactive porous media.

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Section: The Pore Water Ecmentioning

confidence: 99%

Interpreting Self-Potential Signal during Reactive Transport: Application to Calcite Dissolution and Precipitation

Rembert

Jougnot

Luquot

et al. 2022

Water

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“…This equation was validated silicoclastic geological media. According to Soueid Ahmed et al (2020), this equation can be generalized to unsaturated conditions:…”

Section: A Strategy To Estimate Soil Propertiesmentioning

confidence: 99%

Field-scale estimation of soil properties from spectral induced polarization tomography

et al. 2021

Self Cite

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Estimates of soil properties such as Cation Exchange Capacity (CEC), water content, grain size characteristics, and permeability are important in geotechnical engineering, water resources, and agriculture. We develop a nonintrusive approach to estimate these properties in the field using spectral induced polarization (SIP) tomography. This geophysical method provides information about the frequency dependence of the complex electrical conductivity of porous media. Using 18 soil samples collected from a Bordeaux vineyard, we first conducted a laboratory study using SIP over the frequency range 10 mHz-45 kHz. The laboratory data were used to confirm the accuracy of a recently developed dynamic Stern layer petrophysical model. The results are consistent with published values from previous works using soils. A comparison was made by comparing the field complex conductivity spectra and the experimental data at two locations where core samples were obtained. The model was then used in concert with field data to image the spatial distribution of CEC, water content, permeability, and mean grain size along a vineyard transect. For clay and sandy textures found in the field, measured and estimated CEC agree rather well (from 6 to 40% discrepancy). Our approach provides an efficient way to estimate important soil properties in a non-invasive manner, in high resolution, and over field-relevant scales of the critical zone of the Earth.

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“…Synthetic intrinsic hydraulic conductivity ( K i ) and electrical conductivity ( σ ) fields were generated by a spectral‐based Gaussian field generation method of Dietrich and Newsam (1993) using the geostatistical parameters in Table 1. In real‐world conditions, these two fields (i.e., K i and σ ) can be positively correlated, negatively correlated, and sometimes exhibit no correlation because they depend on different ways on water content (or porosity) and cation exchange capacity (Revil et al, 2019; Soueid Ahmed et al, 2020). Without loss of generality, the K i and σ fields were independently generated and were uncorrelated in this study.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Improved Characterization of DNAPL Source Zones via Sequential Hydrogeophysical Inversion of Hydraulic‐Head, Self‐Potential and Partitioning Tracer Data

Kang

Kokkinaki

Kitanidis

et al. 2020

Water Resources Research

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High‐resolution characterization of hydraulic properties and dense nonaqueous phase liquid (DNAPL) contaminant source is crucial to develop efficient remediation strategies. However, DNAPL characterization suffers from a limited number of borehole data in the field, resulting in a low‐resolution estimation. Moreover, high‐resolution DNAPL characterization requires a large number of unknowns to be estimated, presenting a computational bottleneck. In this paper, a low‐cost geophysical approach, the self‐potential method, is used as additional information for hydraulic properties characterization. Joint inversion of hydraulic head and self‐potential measurements is proposed to improve hydraulic conductivity estimation, which is then used to characterize the DNAPL saturation distribution by inverting partitioning tracer measurements. The computational barrier is overcome by (a) solving the inversion by the principal component geostatistical approach, in which the covariance matrix is replaced by a low‐rank approximation, thus reducing the number of forward model runs; (b) using temporal moments of concentrations instead of individual concentration data points for faster forward simulations. To assess the ability of the proposed approach, numerical experiments are conducted in a 3‐D aquifer with 104 unknown hydraulic conductivities and DNAPL saturations. Results show that with realistic DNAPL sources and a limited number of hydraulic heads, the traditional hydraulic/partitioning tracer tomography roughly reconstructs subsurface heterogeneity but fails to resolve the DNAPL distribution. By adding self‐potential data, the error is reduced by 24% in hydraulic conductivity estimation and 68% in DNAPL saturation characterization. The proposed sequential inversion framework utilizes the complementary information from multi‐source hydrogeophysical data sets, and can provide high‐resolution characterizations for realistic DNAPL sources.

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Induced polarization as a tool to non-intrusively characterize embankment hydraulic properties

Cited by 22 publications

References 44 publications

Interpreting Self-Potential Signal during Reactive Transport: Application to Calcite Dissolution and Precipitation

Interpreting Self-Potential Signal during Reactive Transport: Application to Calcite Dissolution and Precipitation

Field-scale estimation of soil properties from spectral induced polarization tomography

Improved Characterization of DNAPL Source Zones via Sequential Hydrogeophysical Inversion of Hydraulic‐Head, Self‐Potential and Partitioning Tracer Data

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