Physical Explanation of Archie's Porosity Exponent in Granular Materials: A Process‐Based, Pore‐Scale Numerical Study

Niu, Qifei; Zhang, Chi

doi:10.1002/2017gl076751

Cited by 20 publications

(14 citation statements)

References 44 publications

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“…The code applies a uniform electric field across the sample and then solves the spatial electric potential and current density in the sample with the conjugate gradient method. Based on averaged current density, Ohm's law can be used to calculate the effective electrical conductivity of the sample σ eff (e.g., Niu & Zhang, ). Since σ eff is solely from the ionic conduction in the bulk solution, the formation factor F of the sample can be simply determined as F = σ f / σ eff .…”

Section: Numerical Methods and Samplesmentioning

confidence: 99%

“…Two samples are used in this study: a synthetic loosely packed ooids sample (Sample 1) and a carbonate mudstone (Sample 2). The ooids sample (Figure a) with the initial porosity ϕ = 30.2% is obtained using the discrete element method by compressing sparsely distributed spherical particles (e.g., Niu & Zhang, ). The carbonate mudstone sample has a porosity of ~13% (from helium measurement) and is from the Wellington Formation, KS; its microstructural image in Figure a is from micro‐computed tomography scan data after segmentation.…”

Section: Numerical Methods and Samplesmentioning

confidence: 99%

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Permeability Prediction in Rocks Experiencing Mineral Precipitation and Dissolution: A Numerical Study

Niu

Zhang

2019

Water Resources Research

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In this study, we focus on the electrical tortuosity‐based permeability model k = reff2/8F (reff is an effective pore size, and F is the formation factor) and analyze its applicability to rocks experiencing mineral precipitation and dissolution. Two limiting cases of advection‐dominated water‐rock reactions are simulated, that is, the reaction‐limited and transport‐limited cases. At the pore scale, the two precipitation/dissolution patterns are simulated with a geometrical model and a phenomenological model. The fluid and electric flows in the rocks are simulated by directly solving the linear Stokes equation and Laplace equation on the representative elementary volume of the samples. The numerical results show that evolutions of k and F differ significantly in the two limiting cases. In general, the reaction‐limited precipitation/dissolution would result in a smooth variation of k and F, which can be roughly modeled with a power function of porosity ϕ with a constant exponent. In contrast, the transport‐limited precipitation/dissolution mostly occurs near the pore throats where the fluid velocity is high. This induces a sharp change in k and F despite a minor variation in ϕ. The commonly used power laws with constant exponents are not able to describe such variations. The results also reveal that the electrical tortuosity‐based permeability prediction generally works well for rocks experiencing precipitation/dissolution if reff can be appropriately estimated, for example, with the electrical field normalized pore size Λ. The associated prediction errors are mainly due to the use of electrical tortuosity, which might be considerably larger than the true hydraulic tortuosity.

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Section: Numerical Methods and Samplesmentioning

confidence: 99%

Section: Numerical Methods and Samplesmentioning

confidence: 99%

Permeability Prediction in Rocks Experiencing Mineral Precipitation and Dissolution: A Numerical Study

Niu

Zhang

2019

Water Resources Research

Self Cite

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“…where σ w is the fluid conductivity, ϕ int is the interconnected porosity, and S is the aqueous saturation. The cementation exponent m is dependent on the rate of change in pore complexity with porosity (Yue 2019), and on particle shape and orientation (Niu and Zhang 2018), and typically varies between 1.2 and 4.4 (Lesmes and Friedman 2005). A value of 1.8, which has been previously applied to represent Hanford sediments (Johnson and Wellman 2013), was used.…”

Section: Transformation Of Flow and Transport Parameters To Bulk Electrical Conductivitymentioning

confidence: 99%

Groundwater characterization and monitoring at a complex industrial waste site using electrical resistivity imaging

et al. 2020

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A contaminated industrial waste site in Washington State (USA) containing buried, metallic-waste storage tanks, pipes, and wells, was evaluated to determine the feasibility of monitoring groundwater remediation activities associated with an underlying perched aquifer system using electrical resistivity tomography. The perched aquifer, located ~65 m below ground surface and ~10 m above the regional water table, contains high concentrations of nitrate, uranium, and other contaminants of concern from past tank leaks and intentional releases of wastes to surface disposal sites. The extent of the perched water aquifer is not well known, and the effectiveness of groundwater extraction for contaminant removal is uncertain, so supplemental characterization and monitoring technologies are being evaluated. Numerical simulations of subsurface flow and contaminant transport were performed with a highly resolved model of the hydrogeologic system and waste site infrastructure, and these simulations were used as the physical basis for electrical resistivity tomography modeling. The modeling explicitly accounted for metallic infrastructure at the site. The effectiveness of using surface electrodes versus surface and horizontal subsurface electrodes, for imaging groundwater extraction from the perched water aquifer, was investigated. Although directional drilling is a mature technology, its use for electrode emplacement in the deep subsurface under a complex industrial waste site via horizontal wells has not yet been demonstrated. Results from this study indicate that using horizontal subsurface electrode arrays could significantly improve the ability of electrical resistivity tomography to image deep subsurface features and monitor remediation activities under complex industrial waste sites.

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“…Note that surface conduction is neglected in Equation 4 because of the low clay content of most Hanford sediments. The cementation exponent m is related to the pore tortuosity and connectivity, dependent on particle shape and orientation (e.g., Niu and Zhang ) and typically varies between 1.2 and 4.4 (Lesmes and Friedman ). For the Hanford B‐Complex, a representative value of 1.27 was used.…”

Section: Simulation Detailsmentioning

confidence: 99%

Feasibility Assessment of Long‐Term Electrical Resistivity Monitoring of a Nitrate Plume

2019

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Long‐term monitoring solutions at contaminated sites are necessary to track plume migration and evaluate the performance of remediation efforts. Electrical resistivity imaging (ERI) can potentially provide information about plume dynamics; however, the feasibility and likelihood of success are seldom evaluated before conducting a field study. Coupling flow and transport models with geoelectrical models provide a powerful way to assess the potential effectiveness of an actual ERI field campaign. We present a coupled approach for evaluating the feasibility of monitoring nitrate migration and remediation using 4D time‐lapse ERI at a legacy nuclear waste facility. This kilometer‐scale study focuses on depths below the water table (∼70 m). A flow and transport model is developed to perform simulations of nitrate migration and removal via a hypothetical pump‐and‐treat system. A tracer injection is also simulated at the leading edge of the nitrate plume to enhance the conductivity contrast between the native subsurface and the groundwater fluids. Images of absolute bulk conductivity provide limited information concerning plume migration while time‐lapse difference images, which remove the static effects of geology, provide more useful information concerning plume dynamics over time. A spatial moment analysis performed on flow and transport and ERI models matches well during the tracer injection; however, inversion regularization smoothing otherwise limits the value in terms of locating the center of mass. We find that the addition of a tracer enables ERI to characterize plume dynamics during pump‐and‐treat operations, and late‐time ERI monitoring provides a conservative estimate of nitrate plume boundaries in this synthetic study.

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Physical Explanation of Archie's Porosity Exponent in Granular Materials: A Process‐Based, Pore‐Scale Numerical Study

Cited by 20 publications

References 44 publications

Permeability Prediction in Rocks Experiencing Mineral Precipitation and Dissolution: A Numerical Study

Permeability Prediction in Rocks Experiencing Mineral Precipitation and Dissolution: A Numerical Study

Groundwater characterization and monitoring at a complex industrial waste site using electrical resistivity imaging

Feasibility Assessment of Long‐Term Electrical Resistivity Monitoring of a Nitrate Plume

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