Effect of Clay and Water Salinity on Electrochemical Behavior of Reservoir Rocks

Hill, H.J.; Milburn, J.D.

doi:10.2118/532-g

Cited by 106 publications

(40 citation statements)

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“…The experimental measurements follow the same trend regardless of whether the sample was initially saturated with 0.1 M electrolyte or 0.5 M electrolyte, which suggests that it is the concentration ratio between the saturated sample and the adjacent reservoir that dictates the measured EED potential, rather than the concentration of the saturating electrolyte. Figure 7 are data reported by Hill and Milburn [1956] and Ortiz et al [1973] measured across a variety of shaley sandstone and shale samples saturated with NaCl electrolyte. Hill and Milburn [1956] did not explain how electrode effects were accounted for in their experiments; Ortiz et al [1973] accounted for electrode effects using a similar method to that reported here.…”

Section: Eed Potentialmentioning

confidence: 77%

“…Electrochemical exclusion-diffusion potential (ΔV EED ) measured across our sandstone samples as a function of NaCl electrolyte concentration ratio, accounting for electrode effects. Also shown are measured data (various grey symbols) reported by Hill and Milburn [1956] and Ortiz et al [1973] on shaly sands. The dashed line shows the electrochemical exclusion potential calculated using equation (14); the solid line shows the electrochemical diffusion potential calculated using equation (15), which assumes that the ionic transport number of the Na ions (t Na ) is constant.…”

Section: Also Shown Inmentioning

confidence: 98%

“…The parameter R represents the ratio of surface to bulk (electrolyte) electrical conductivity. We use an approximated value of 0.2 for the porosity of our samples, reported in Table 3 and use the value of 0.8 for f Q , based on Leroy and Revil [2009]; the CEC is constant for a given curve, but curves are generated for CEC over the This study − 0.5M Hill & Milburn, 1956, Sample 14 Hill & Milburn, 1956, Sample 13 Hill & Milburn, 1956, Sample 9 Hill & Milburn, 1956, Sample 40 Ortiz et al, 1973 T + = 1 T + = t Na = Const. Figure 7.…”

Section: Also Shown Inmentioning

confidence: 99%

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Experimental measurements of the SP response to concentration and temperature gradients in sandstones with application to subsurface geophysical monitoring

Leinov

Jackson

2014

JGR Solid Earth

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Exclusion-diffusion potentials arising from temperature gradients are widely neglected in self-potential (SP) surveys, despite the ubiquitous presence of temperature gradients in subsurface settings such as volcanoes and hot springs, geothermal fields, and oil reservoirs during production via water or steam injection. Likewise, with the exception of borehole SP logging, exclusion-diffusion potentials arising from concentration gradients are also neglected or, at best, it is assumed that the diffusion potential dominates. To better interpret these SP sources requires well-constrained measurements of the various coupling terms. We report measurements of thermoelectric and electrochemical exclusion-diffusion potentials across sandstones saturated with NaCl brine and find that electrode effects can dominate the measured voltage. After correcting for these, we find that Hittorf transport numbers are the same within experimental error regardless of whether ion transport occurs in response to temperature or concentration gradients over the range of NaCl concentration investigated that is typical of natural systems. Diffusion potentials dominate only if the pore throat radius is more than approximately 4000 times larger than the diffuse layer thickness. In fine-grained sandstones with small pore throat diameter, this condition is likely to be met only if the saturating brine is of relatively high salinity; thus, in many cases of interest to earth scientists, exclusion-diffusion potentials will comprise significant contributions from both ionic diffusion through, and ionic exclusion from, the pore space of the rock. However, in coarse-grained sandstones, or sandstones saturated with high-salinity brine, exclusion-diffusion potentials can be described using end-member models in which ionic exclusion is neglected. Exclusion-diffusion potentials in sandstones depend upon pore size and salinity in a complex way: they may be positive, negative, or zero depending upon sandstone rock texture (expressed here by the pore radius r) and salinity.

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Section: Eed Potentialmentioning

confidence: 77%

Section: Also Shown Inmentioning

confidence: 98%

Section: Also Shown Inmentioning

confidence: 99%

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Experimental measurements of the SP response to concentration and temperature gradients in sandstones with application to subsurface geophysical monitoring

Leinov

Jackson

2014

JGR Solid Earth

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“…The black line represents the diffusion limit and the dashed line the exclusion limit calculated by Leinov and Jackson (2014). Also shown are values for shaly sand by Hill and Millburn (1956) and sandstone by Leinov and Jackson (2014).…”

Section: The Exclusion Efficiencymentioning

confidence: 99%

Characterizing the Self‐Potential Response to Concentration Gradients in Heterogeneous Subsurface Environments

et al. 2019

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Self‐potential (SP) measurements can be used to characterize and monitor, in real‐time, fluid movement and behavior in the subsurface. The electrochemical exclusion‐diffusion (EED) potential, one component of SP, arises when concentration gradients exist in porous media. Such concentration gradients are of concern in coastal and contaminated aquifers and oil and gas reservoirs. It is essential that estimates of EED potential are made prior to conducting SP investigations in complex environments with heterogeneous geology and salinity contrasts, such as the UK Chalk coastal aquifer. Here we report repeatable laboratory estimates of the EED potential of chalk and marls using natural groundwater (GW), seawater (SW), deionized (DI) water, and 5 M NaCl. In all cases, the EED potential of chalk was positive (using a GW/SW concentration gradient the EED potential was ca. 14 to 22 mV), with an increased deviation from the diffusion limit at the higher salinity contrast. Despite the relatively small pore size of chalk (ca. 1 μm), it is dominated by the diffusion potential and has a low exclusion efficiency, even at large salinity contrasts. Marl samples have a higher exclusion efficiency which is of sufficient magnitude to reverse the polarity of the EED potential (using a GW/SW concentration gradient the EED potential was ca. −7 to −12 mV) with respect to the chalk samples. Despite the complexity of the natural samples used, the method produced repeatable results. We also show that first order estimates of the exclusion efficiency can be made using SP logs, supporting the parameterization of the model reported in Graham et al. (2018, https://doi.org/10.1029/2018WR022972), and that derived values for marls are consistent with the laboratory experiments, while values derived for hardgrounds based on field data indicate a similarly high exclusion efficiency. While this method shows promise in the absence of laboratory measurements, more rigorous estimates should be made where possible and can be conducted following the experimental methodology reported here.

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“…The presence of clays with high surface conduction would not allow the use of Archie's law as a surface conduction process should be added (e.g., Waxman and Smits 1968). The water conductivity σ w was set to 0.06 S/m and p, q were both set to 2, which represent average values for limestone medium (Hill and Milburn 1956;Carothers 1968). Table 1 Fixed Hydrodynamic Parameters Used in the Coupled Models in the Synthetic and Field Cases…”

Section: Model Parametersmentioning

confidence: 99%

Characterizing Stream‐Aquifer Exchanges with Self‐Potential Measurements

et al. 2017

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Characterizing the interactions between streams and aquifers is a major challenge in hydrology. Electrical self-potential (SP) is sensitive to groundwater flow through the electrokinetic effect, which is proportional to Darcy velocity. SP surveys have been extensively used for the characterization of seepage flow in a variety of contexts. But to our knowledge, a model coupling SP and groundwater flow has never been implemented for the study of stream-aquifer interactions. To address the issue, we first implemented a two-dimensional model to a synthetic stream-aquifer cross section. Results underline the very distinct nature of SP profiles in gaining or losing stream conditions. Second, we presented a field application in a transect crossing a stream in losing conditions. The coupled model successfully reproduced the observed SP profile. This inverse modeling of the SP signal provides quantitative data on hydrodynamic parameters (hydraulic conductivity, hydraulic heads) and geophysical parameters (coupling coefficient). Nevertheless, all relevant parameters cannot be uniquely estimated without precise prior information on at least some of these parameters. Our results confirm the potential of SP surveys on the characterization of stream-aquifer exchanges. Recommendations on the collection of high-quality data are also provided, along with a description of the contexts in which the methodology is likely to perform well.

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Effect of Clay and Water Salinity on Electrochemical Behavior of Reservoir Rocks

Cited by 106 publications

References 0 publications

Experimental measurements of the SP response to concentration and temperature gradients in sandstones with application to subsurface geophysical monitoring

Experimental measurements of the SP response to concentration and temperature gradients in sandstones with application to subsurface geophysical monitoring

Characterizing the Self‐Potential Response to Concentration Gradients in Heterogeneous Subsurface Environments

Characterizing Stream‐Aquifer Exchanges with Self‐Potential Measurements

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