2017
DOI: 10.1016/j.fuel.2017.06.050
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Local diffusion coefficient measurements in shale using dynamic micro-computed tomography

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Cited by 35 publications
(17 citation statements)
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“…The estimated permeability appears to be very low, about 9 nanodarcy, but this is about an order of magnitude greater than what we previously estimated for a Marcellus shale rock core with a porosity of 0.1 in Cihan et al (2019). The estimated effective diffusion coefficients are also an order of magnitude greater than the estimated values for the same shale and the reported values for other nanoporous rocks (Peng et al, 2012;Tokunaga et al, 2017;Zhang et al, 2017). The ideal Knudsen diffusion coefficient in a cylindrical pore of 2 nm radius is about 8 × 10 −7 m 2 /s, which is in the same order of magnitude with our estimated diffusivity value for the gas phase, D (g) = 2.78 × 10 −7 m 2 /s.…”
Section: Resultscontrasting
confidence: 66%
See 1 more Smart Citation
“…The estimated permeability appears to be very low, about 9 nanodarcy, but this is about an order of magnitude greater than what we previously estimated for a Marcellus shale rock core with a porosity of 0.1 in Cihan et al (2019). The estimated effective diffusion coefficients are also an order of magnitude greater than the estimated values for the same shale and the reported values for other nanoporous rocks (Peng et al, 2012;Tokunaga et al, 2017;Zhang et al, 2017). The ideal Knudsen diffusion coefficient in a cylindrical pore of 2 nm radius is about 8 × 10 −7 m 2 /s, which is in the same order of magnitude with our estimated diffusivity value for the gas phase, D (g) = 2.78 × 10 −7 m 2 /s.…”
Section: Resultscontrasting
confidence: 66%
“…The fluid‐solid interaction forces, also known as surface forces (e.g., van der Waals, electrostatic, structural forces) (Churaev, 2000; Israelachvili, 2011), result from electrostatic and electromagnetic fields generated by charges and oscillating molecular dipoles. These forces can alter macroscopic fluid phase behavior and control related processes such as sorption, wetting, and transport (e.g., Berthonneau et al., 2018; Li, Fratini et al., 2012; Velasco et al., 2017; Zarzycki & Gilbert, 2016; Zhang et al., 2017); they can also cause microstructural changes, especially in clay‐rich systems (e.g., swelling, shrinking, and fracturing) (e.g., Bertoncello, 2014; Dehghanpour et al., 2012).…”
Section: Introductionmentioning
confidence: 99%
“…The magnitudes of the estimated diffusion coefficients are overall in agreement with reported values for similar rocks. 9,14,59 However, as shown by the sensitivity analysis results in Table 3, the low sensitivity values indicate that the estimation of the matrix diffusivity parameters from the water uptake data only may not be precise for the tested experimental conditions.…”
Section: ■ Theorymentioning
confidence: 99%
“…Multiphase fluid behavior in nanoporous materials is of interest for various science and engineering applications, including geoscience applications, chemical and material engineering, , and biological sciences. , In the context of geoscience applications, shales and mudstones are commonly occurring sedimentary rocks that have considerable importance as low-permeability seals for geologic carbon sequestration and nuclear waste disposal or, with increasing emphasis over the last two decades, as large reserves for unconventional oil and gas production. Pores within these rocks are predominantly in the micropore (<2 nm) and mesopore (2 to 50 nm) size categories. , When the pore sizes approach nanoscales, physicochemical interactions among fluid and solid molecules can alter bulk fluid phase properties such as phase composition, density, viscosity, and interfacial tension. Likewise, basic macroscopic transport properties in porous media such as permeability and diffusivity can become strongly influenced by fluid–pore wall interactions in addition to the effects of pore size distribution and connectivity. …”
Section: Introductionmentioning
confidence: 99%
“…Segmented data has been used to study rock petrophysical properties (porosity, permeability, electrical resistivity, elastic moduli etc.) (Andrä et al ., ; Blunt et al ., ; Mostaghimi et al ., ), pore morphology (Armstrong et al ., ), multiphase flow (Armstrong et al ., ; Berg et al ., ; Brown et al ., ) and mass transport (Tidwell et al ., ; Cavé et al ., ; Vega et al ., ; Liu et al ., ; Zhang et al ., ; Zhang et al ., ). Alternatively, quantitative information can be extracted from the greyscale CT values without the need for image segmentation (Schlüter et al ., ).…”
Section: Introductionmentioning
confidence: 99%