On Automatically Extracting the Statistical Information of Pores in Heterogeneous Materials From the Sem Morphology

Li, Haolin; Dong, Shuhao; Qin, Na; Liu, Jiantao; Yu, Yaoxiang; Zhang, Zhengqing; Wu, Muqing; Zhu, Chen

doi:10.1615/jpormedia.v24.i8.60

Cited by 2 publications

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“…The pore structure has been studied by many scholars using the above means. Using scanning electron microscopy, XRD, etc., the pore morphology and connectivity of coal rock bodies can be obtained visually [26][27][28][29]. However, the pore characteristic data observed by these methods are mainly used for qualitative characterization, and it is difficult to analyze quantitatively.…”

Section: Introductionmentioning

confidence: 99%

Joint Characterization and Fractal Laws of Pore Structure in Low-Rank Coal

Zhou

Bai

et al. 2023

Sustainability

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The pore structure of low-rank coal reservoirs was highly complex. It was the basis for predicting the gas occurrence and outburst disasters. Different scale pores have different effects on adsorption–desorption, diffusion, and seepage in coalbed methane. To study the pore structure distribution characteristics, which are in different scales of low-rank coal with different metamorphism grade, the pore structure parameters of low-rank coal were obtained by using the mercury injection, N2 adsorption, and CO2 adsorption. These three methods were used to test the pore volume and specific surface area of low-rank coal in their test ranges. Then, the fractal dimension method was used to calculate the fractal characteristics of the pore structure of full aperture section to quantify the complexity of the pore structure. The experimental results showed that the pore volume and specific surface area of low-rank coal were mainly controlled by microporous. The pore fractal characteristics were obvious. With the influence of coalification process, as the degree of coal metamorphism increases, fluctuations in the comprehensive fractal dimension, specific surface area, and pore volume of the pore size range occur within the range of Rmax = 0.50% to 0.65%.

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Section: Introductionmentioning

confidence: 99%

Joint Characterization and Fractal Laws of Pore Structure in Low-Rank Coal

Zhou

Bai

et al. 2023

Sustainability

View full text Add to dashboard Cite

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“…The commonly used visual experimental devices mainly include microfluidic models [ 4 , 5 , 6 , 7 ], X-ray computerized tomography (CT) [ 8 , 9 , 10 ], focused ion beam-scanning electron microscopy (FIB-SEM) [ 11 , 12 , 13 ] and transmission electron microscope (TEM) [ 14 , 15 ]. The microfluidic models can visualize the fluid flow intuitively in pore space, which are widely utilized to reveal the percolation law of multiphase fluid.…”

Section: Introductionmentioning

confidence: 99%

Study on Oil Recovery Mechanism of Polymer-Surfactant Flooding Using X-ray Microtomography and Integral Geometry

et al. 2022

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Understanding pore-scale morphology and distribution of remaining oil in pore space are of great importance to carry out in-depth tapping of oil potential. Taking two water-wet cores from a typical clastic reservoir in China as an example, X-ray CT imaging is conducted at different experimental stages of water flooding and polymer-surfactant (P-S) flooding by using a high-resolution X-ray microtomography. Based on X-ray micro-CT image processing, 3D visualization of rock microstructure and fluid distribution at the pore scale is achieved. The integral geometry newly developed is further introduced to characterize pore-scale morphology and distribution of remaining oil in pore space. The underlying mechanism of oil recovery by P-S flooding is further explored. The results show that the average diameter of oil droplets gradually decreases, and the topological connectivity becomes worse after water flooding and P-S flooding. Due to the synergistic effect of “1 + 1 > 2” between the strong sweep efficiency of surfactant and the enlarged swept volume of the polymer, oil droplets with a diameter larger than 124.58 μm can be gradually stripped out by the polymer-surfactant system, causing a more scattered distribution of oil droplets in pore spaces of the cores. The network-like oil clusters are still dominant when water flooding is continued to 98% of water cut, but the dominant pore-scale oil morphology has evolved from network-like to porous-type and isolated-type after P-S flooding, which can provide strong support for further oil recovery in the later stage of chemical flooding.

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On Automatically Extracting the Statistical Information of Pores in Heterogeneous Materials From the Sem Morphology

Cited by 2 publications

References 0 publications

Joint Characterization and Fractal Laws of Pore Structure in Low-Rank Coal

Joint Characterization and Fractal Laws of Pore Structure in Low-Rank Coal

Study on Oil Recovery Mechanism of Polymer-Surfactant Flooding Using X-ray Microtomography and Integral Geometry

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