Salinity dependence of the complex surface conductivity of the Portland sandstone

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. D125-D140 ◽  
Author(s):  
Qifei Niu ◽  
André Revil ◽  
Milad Saidian
Keyword(s):  
Relaxation Time ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Space ◽  
Complex Surface ◽  
Surface Conductivity ◽  
Formation Factor ◽  
Polarization Model ◽  
Fluid Conductivity

Induced polarization can be used to estimate surface conductivity by assuming a universal linear relationship between the surface and quadrature conductivities of porous media. However, this assumption has not yet been justified for conditions covering a broad range of fluid conductivities. We have performed complex conductivity measurements on Portland sandstone, an illite- and kaolinite-rich sandstone, at 13 different water salinities (NaCl) over the frequency range of 0.1 Hz to 45 kHz. The conductivity of the pore water [Formula: see text] affected the complex surface conductivity mainly by changing the tortuosity of the conduction paths in the pore network from high to low salinities. As the fluid conductivity decreases, the magnitude of the surface conductivity and quadrature conductivity was observed to decrease. At relatively high salinities ([Formula: see text]), the ratio between the surface conductivity and quadrature conductivity was roughly constant. At low salinities ([Formula: see text]), the ratio decreased slightly with the decrease of the salinity. A Stern layer polarization model was combined with the differential effective medium (DEM) theory to describe this behavior. The tortuosity entering the complex surface conductivity was salinity dependent following the prediction of the DEM theory. At high salinity, it reached the value of the bulk tortuosity of the pore space given by the product of the intrinsic formation factor and the connected porosity. The relaxation time distributions were also obtained at different salinities by inverting the measured spectra using a Warburg decomposition. The mode of the relaxation time probability distribution found a small but clear dependence on the salinity. This salinity dependence can be explained by considering the ions exchange between Stern and diffuse layers during polarization of the former. The pore-size distribution obtained from the distribution of the relaxation time agreed with the pore-size distribution from nuclear magnetic resonance measurements.

scholarly journals POROSIMETRY BY RANDOM NODE STRUCTURING IN VIRTUAL CONCRETE

2012 ◽  
Vol 31 (2) ◽  
pp. 79 ◽  
Author(s):  
Piet Stroeven ◽  
Nghi L.B. Le ◽  
Lambertus J Sluys ◽  
Huan He
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Space ◽  
Cementitious Materials ◽  
Discrete Element Modeling ◽  
Concurrent Algorithm ◽  
Random Node ◽  
Volume Measurements ◽  
3D Information

Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of the aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator “opening” can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. However, aggregate grain surfaces lead to anisotropy in porosity. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements. In addition to size of pores their continuity is of crucial importance for durability estimation. Double-random multiple tree structuring (DRaMuTS), introduced earlier in IA&S (Stroeven et al., 2011b) and random node structuring (RaNoS) provide such information.

scholarly journals Partitioning of the pore space based on a non-hierarchical decomposition model

2019 ◽  
Vol 29 ◽  
pp. 1-18
Author(s):  
Irving Cruz-Matías
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Space ◽  
Physical Method ◽  
Scientific Data ◽  
New Approach ◽  
Decomposition Model ◽  
Spatial Partition

Bio-CAD and in-silico experimentation currently have a growing interest in biomedical applications where scientific data coming from real samples are used to evaluate physical properties. In this sense, analyzing the pore-size distribution is a demanding task to help interpret the characteristics of porous materials by partitioning it into its constituent pores. Pores are defined intuitively as local openings that can be interconnected by narrow apertures called throats that control a non-wetting phase invasion in a physical method. There are several approaches to characterize the pore space in terms of its constituent pores, several of them requiring prior computation of a skeleton. This paper presents a new approach to characterize the pore space, in terms of a pore-size distribution, which does not require the skeleton computation. Throats are identified using a new decomposition model that performs a spatial partition of the object in a non-hierarchical sweep-based way consisting of a set of disjoint boxes. This approach enables the characterization of the pore space in terms of a pore-size distribution. computation. Throats are identified using a new decomposition model that performs a spatial partition of the object in a non-hierarchical sweep-based way consisting of a set of disjoint boxes. This approach enables the characterization of the pore space in terms of a pore-size distribution.

scholarly journals Combining SEM and Mercury Intrusion Capillary Pressure in the characterization of pore-throat distribution in tight sandstone and its modification by diagenesis: A case study in the Yanchang Formation, Ordos Basin, China

2020 ◽  
Vol 24 (1) ◽  
pp. 19-28
Author(s):  
Wei Wang ◽  
Caili Yu ◽  
Le Zhao ◽  
Shuang Xu ◽  
Lei Gao
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Pore Space ◽  
Ordos Basin ◽  
Pore Throat ◽  
Tight Sandstone ◽  
Nano Scale ◽  
Carbonate Cementation ◽  
Pressure Controlled

Determining the characteristics of pore-throat structures, including the space types present and the pore size distribution, is essential for the evaluation of reservoir quality in tight sandstones. In this study, the results of various testing methods, including scanning electron microscopy (SEM), pressure-controlled porosimetry (PCP) and rate-controlled porosimetry (RCP), were compared and integrated to characterize the pore size distribution and the effects of diagenesis upon it in tight sandstones from the Ordos Basin, China. The results showed that reservoir spaces in tight sandstones can be classified into those with three types of origins (compaction, dissolution, and clay-related) and that the sizes and shapes of pore space differ depending on origin. Considering the data obtained by mercury injection porosimetry and the overestimation of pore radii by pressure-controlled porosimetry, the full-range pore size distribution of tight sandstones can be determined by combining data from PCP with corrected RCP data. The pore-throat radii in tight sandstone vary from 36 nm to 200 μm, and the distribution curve is characterized by three peaks. The right peak remains similar across the sample set and corresponds to residual intergranular pores and dissolution pores. The middle and left peaks show variation between samples due to the heterogeneity and complexity of nano-scale throat bodies. The average micro-scale pore content is 33.49%, and nano-scale throats make up 66.54%. The nano-scale throat spaces thus dominate the reservoir space of the tight sandstones. Compaction, dissolution, carbonate cementation, and clay cementation have various effects on pore-throats. Compaction and carbonate cementation decrease pore body content. Pore-bridging clay cementation decreases throat space content. As pore-lining clay cementation preserves pore space.

scholarly journals Fractal Properties of Various Clay Minerals Obtained from SEM Images

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Naser Golsanami ◽  
Shanilka Gimhan Fernando ◽  
Madusanka Nirosh Jayasuriya ◽  
Weichao Yan ◽  
Huaimin Dong ◽  
...  
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Clay Minerals ◽  
Pore Space ◽  
Reservoir Rock ◽  
Distribution Area ◽  
Sem Images ◽  
Fractal Properties ◽  
Internal Pore

Clay minerals significantly alter the pore size distribution (PSD) of the gas hydrate-bearing sediments and sandstone reservoir rock by adding an intense amount of micropores to the existing intragranular pore space. Therefore, in the present study, the internal pore space of various clay groups is investigated by manually segmenting Scanning Electron Microscopy (SEM) images. We focused on kaolinite, smectite, chlorite, and dissolution holes and characterized their specific pore space using fractal geometry theory and parameters such as pore count, pore size distribution, area, perimeter, circularity, and density. Herein, the fractal properties of different clay groups and dissolution holes were extracted using the box counting technique and were introduced for each group. It was observed that the presence of clays complicates the original PSD of the reservoir by adding about 1.31-61.30 pores/100 μm2 with sizes in the range of 0.003-87.69 μm2. Meanwhile, dissolution holes complicate the pore space by adding 4.88-8.17 extra pores/100 μm2 with sizes in the range of 0.06-119.75 μm2. The fractal dimension ( D ) and lacunarity ( L ) values of the clays’ internal pore structure fell in the ranges of 1.51-1.85 and 0.18-0.99, respectively. Likewise, D and L of the dissolution holes were in the ranges of, respectively, 1.63-1.65 and 0.56-0.62. The obtained results of the present study lay the foundation for developing improved fractal models of the reservoir properties which would help to better understand the fluid flow, irreducible fluid saturation, and capillary pressure. These issues are of significant importance for reservoir quality and calculating the accurate amount of producible oil and gas.

A FRACTAL PERMEABILITY MODEL FOR SHALE MATRIX WITH MULTI-SCALE POROUS STRUCTURE

Fractals ◽  
2016 ◽  
Vol 24 (01) ◽  
pp. 1650002 ◽  
Author(s):  
MAO SHENG ◽  
GENSHENG LI ◽  
SHOUCENG TIAN ◽  
ZHONGWEI HUANG ◽  
LIQIANG CHEN
Keyword(s):  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Shale Gas ◽  
Gas Permeability ◽  
Pore Space ◽  
Fractal Theory ◽  
Permeability Model ◽  
Multi Scale ◽  
Nanopore Structure

Nanopore structure and its multiscale feature significantly affect the shale-gas permeability. This paper employs fractal theory to build a shale-gas permeability model, particularly considering the effects of multiscale flow within a multiscale pore space. Contrary to previous studies which assume a bundle of capillary tubes with equal size, in this research, this model reflects various flow regimes that occur in multiscale pores and takes the measured pore-size distribution into account. The flow regime within different scales is individually determined by the Knudsen number. The gas permeability is an integral value of individual permeabilities contributed from pores of different scales. Through comparing the results of five shale samples, it is confirmed that the gas permeability varies with the pore-size distribution of the samples, even though their intrinsic permeabilities are the same. Due to consideration of multiscale flow, the change of gas permeability with pore pressure becomes more complex. Consequently, it is necessary to cover the effects of multiscale flow while determining shale-gas permeability.

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