Characteristics of pore structure and fractal dimension of low-rank coal: A case study of Lower Jurassic Xishanyao coal in the southern Junggar Basin, NW China

Fu, Hengzhi; Tang, Dazhen; Xu, Ting; Xu, Hao; Tao, Shu; Yin, Zhenyong; Chen, Baoli; Zhang, Cheng; Wang, Linlin

doi:10.1016/j.fuel.2016.11.069

Cited by 257 publications

(148 citation statements)

References 35 publications

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“…It can be known that the coal matrix's surface and internal pore structure of the treated samples were more rough and complex due to the damaged effect by the frost-heave force as the coal samples infiltrated in LqCO 2 , which caused the increase in the fractal dimension [22,26,42]. There is a positive linear correlation between D 1 and D 2 (Figure 3), which is consistent with the results of previous research [5,16,43]. The fractal characteristics of the adsorbed pores were clearer when the coal samples were frozen by LqCO 2 [32].…”

Section: Fractal Characteristics Of the Adsorbed Pores From Raw And Lsupporting

confidence: 88%

“…From the above analysis and isotherm descriptions, monolayer adsorption generally occurred in region 1, where nitrogen molecules are gradually adsorbed to the pores of the coal sample. Accordingly, the fractal dimension D 1 was calculated to be in region 1 and could be used to describe the fractal characteristics of the pores' surface areas [16]. Multilayer adsorption and capillary condensation mainly occurred in region 2, and the fractal dimension D 2 was calculated in region 2 and can be used to describe fractal characteristics of internal pore structure [43].…”

Section: Lp-n 2 -Ad Isotherms and Pore Structure Parameters Analysis mentioning

confidence: 99%

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Damage Effects and Fractal Characteristics of Coal Pore Structure during Liquid CO2 Injection into a Coal Bed for E-CBM

Wei

et al. 2018

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Pore structure has a significant influence on coal-bed methane (CBM) enhancement. Injecting liquid CO 2 into coal seams is an effective way to increase CBM recovery. However, there has been insufficient research regarding the damage effects and fractal characteristics of pore structure at low temperature induced by injecting liquid CO 2 into coal samples. Therefore, the methods of low-pressure nitrogen adsorption-desorption (LP-N 2 -Ad) and mercury intrusion porosimetry (MIP) were used to investigate the damage effects and fractal characteristics of pore structure with full aperture as the specimens were frozen by liquid CO 2 . The adsorption isotherms revealed that the tested coal samples belonged to type B, indicating that they contained many bottle and narrow-slit shaped pores. The average pore diameter (APD; average growth rate of 18.20%), specific surface area (SSA; average growth rate of 7.38%), and total pore volume (TPV; average growth rate of 18.26%) increased after the specimens were infiltrated by liquid CO 2 , which indicated the generation of new pores and the transformation of original pores. Fractal dimensions D 1 (average of 2.58) and D 2 (average of 2.90) of treated coal samples were both larger the raw coal (D 1 , average of 2.55 and D 2 , average of 2.87), which indicated that the treated specimens had more rough pore surfaces and complex internal pore structures than the raw coal samples. The seepage capacity was increased because D 4 (average of 2.91) of the treated specimens was also higher than the raw specimens (D 4 , average of 2.86). The grey relational coefficient between the fractal dimension and pore structure parameters demonstrated that the SSA, APD, and porosity positively influenced the fractal features of the coal samples, whereas the TPV and permeability exerted negative influences.

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Section: Fractal Characteristics Of the Adsorbed Pores From Raw And Lsupporting

confidence: 88%

Section: Lp-n 2 -Ad Isotherms and Pore Structure Parameters Analysis mentioning

confidence: 99%

Damage Effects and Fractal Characteristics of Coal Pore Structure during Liquid CO2 Injection into a Coal Bed for E-CBM

Wei

et al. 2018

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“…Chen et al (2016) analyzed the difference in pore structure of each HFUs based on the fractal theory. Winland r 35 (pore radii at 35% mercury situation during MICP) is use to characterize the HFUs (Nie et al, 2015;Hikosaka et al, 2016;Fu et al, 2017) which can be estimated by the following empirical equation: log r 35 = 0.732 + 0.588 log K − 0.864 log(100φ)…”

Section: Pore Type and Hfusmentioning

confidence: 99%

Applications of digital core analysis and hydraulic flow units in petrophysical characterization

Chen

Zhou

2017

Adv. Geo-Energ. Res.

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Conventional petrophysical characterizations are often based on direct laboratory measurements. Although they provide accurate results, such measurements are time-consuming and limited by instrument and environment. What's more, in the georesource energy industry, availability and cuttings of core plugs are difficult. Because of these reasons, virtual digital core technology is of increasing interest due to its capability of characterizing rock samples without physical cores and experiments. Virtual digital core technology, also known as digital rock physics, is used to discover, understand and model relationships between material, fluid composition, rock microstructure and macro equivalent physical properties. Based on actual geological conditions, modern mathematical methods and imaging technology, the digital model of the core or porous media is created to carry out physical field numerical simulation. In this review, the methods for constructing digital porous media are introduced first, then the characterization of thin rock cross section and the capillary pressure curve using scanning electron microscope image under mixed wetting are presented. Finally, we summarize the hydraulic flow unit methods in petrophysical classification.Keywords: Digital core, porous media, petrophysical characterization, thin section, mercury injection capillary pressure.Citation: Chen, X., Zhou, Y. Applications of digital core analysis and hydraulic flow units in petrophysical characterization. Adv.

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“…Fractal dimension (FD) is a relatively new image feature used in CV, and it has been successfully applied in coal, 19 structure rebuilding, 20 delamination detection, 21 etc. In this study, we make a tentative test to use FD to extract distinguishing features from MS brain images.…”

Section: Introductionmentioning

confidence: 99%

Synthetic Minority Oversampling Technique and Fractal Dimension for Identifying Multiple Sclerosis

Zhang

Phillips

et al. 2017

Fractals

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Multiple sclerosis (MS) is a severe brain disease. Early detection can provide timely treatment. Fractal dimension can provide statistical index of pattern changes with scale at a given brain image. In this study, our team used susceptibility weighted imaging technique to obtain 676 MS slices and 880 healthy slices. We used synthetic minority oversampling technique to process the unbalanced dataset. Then, we used Canny edge detector to extract distinguishing edges. The Minkowski-Bouligand dimension was a fractal dimension estimation method and used to extract features from edges. Single hidden layer neural network was used as the classifier. Finally, we proposed a three-segment representation biogeography-based optimization to train the classifier. Our method achieved a sensitivity of 97.78±1.29%, a specificity of 97.82±1.60% and an accuracy of 97.80±1.40%. The proposed method is superior to seven state-of-the-art methods in terms of sensitivity and accuracy.

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Characteristics of pore structure and fractal dimension of low-rank coal: A case study of Lower Jurassic Xishanyao coal in the southern Junggar Basin, NW China

Cited by 257 publications

References 35 publications

Damage Effects and Fractal Characteristics of Coal Pore Structure during Liquid CO2 Injection into a Coal Bed for E-CBM

Damage Effects and Fractal Characteristics of Coal Pore Structure during Liquid CO2 Injection into a Coal Bed for E-CBM

Applications of digital core analysis and hydraulic flow units in petrophysical characterization

Synthetic Minority Oversampling Technique and Fractal Dimension for Identifying Multiple Sclerosis

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