Fractal analysis of high rank coal from southeast Qinshui basin by using gas adsorption and mercury porosimetry

Peng, Cheng; Zou, Changchun; Yang, Yuqing; Guo-hua, Zhang; Wang, Wenwen

doi:10.1016/j.petrol.2017.06.001

Cited by 81 publications

(29 citation statements)

References 47 publications

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“…The gas is mainly adsorbed and stored in the micropores (<10 nm) and transition pores (10–100 nm), and the micropores (<10 nm) and transition pores (10–100 nm) are usually called adsorption pores. In contrast, the mesopores (100–1000 nm) and macropores (>1000 nm) are usually called seepage pores, and the seepage pores are the main locations of methane and water (Chen et al., 2018; Peng et al., 2017; Liu et al., 2015; Meng et al., 2016). Many researchers have performed relevant investigations of pore structures in coals.…”

Section: Introductionmentioning

confidence: 99%

Investigation of pore structure characteristics and adsorption characteristics of coals with different destruction types

Yue

Wang

Chen

et al. 2019

Adsorption Science & Technology

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The occurrence of coal and gas outbursts is closely linked to the presence of tectonic coal. To study the pore structure characteristics and adsorption characteristics of different destruction types of coal, nondestructive coal, destructive coal, strongly destructive coal, pulverized coal, and fully pulverized coal are selected based on the coal and gas outburst mine identification specifications. The experimental methods used are liquid nitrogen adsorption, mercury intrusion porosimetry and CH 4 isothermal adsorption. The results show that the pore volume obtained by the Barrett-Joyner-Halenda method and the specific surface area increase with increasing

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Section: Introductionmentioning

confidence: 99%

Investigation of pore structure characteristics and adsorption characteristics of coals with different destruction types

Yue

Wang

Chen

et al. 2019

Adsorption Science & Technology

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“…Among them, the FHH method has a wide application range, and convenient calculation. [39][40][41][42][43] When Avnir and Jaroniec 44 studied the adsorption of gas molecules on porous solids with uneven surfaces, the fractal dimension was introduced into the adsorption potential theory, and the gas adsorption model on the fractal surface (>2 nm) in the capillary condensation region was established, namely the FHH equation…”

Section: Gas Adsorption: Fhh Methodsmentioning

confidence: 99%

Pore Structure Characterization for a Continental Lacustrine Shale Parasequence Based on Fractal Theory

Zhang

Chai

et al. 2019

Fractals

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Fractal dimension is an important parameter in the evaluation of tight reservoirs. For an outcrop section of the Nenjiang formation in the Songliao Basin, China, the pore structure and pore fractal characteristics of shale parasequences were investigated using fractal theory. In addition, factors causing pore structure changes were analyzed using the results of low-temperature nitrogen adsorption and scanning electron microscope (SEM) experiments. Conducive to gas migration and secondary pores development such as dissolution, results showed that nanoscale pores dominated by fracture-like morphology and consequent good internal connectivity were observed in each pore size section within the target layer. Each parasequence is characterized by a sequential upward decrease of average pore size and an upward increase of total pore volume, with an increasing number of pores from 2[Formula: see text]nm to 50[Formula: see text]nm. Pores are isolated from each other, with poor connectivity and relatively complex composition of brittle minerals and clay minerals. Main components of the brittle minerals, quartz and feldspar, occur in 20–50% and higher clay mineral content ranging from 50% to 70%. In the parasequence cycle, clay mineral gradually decreases while the brittle mineral content increases. Fractal dimension is negatively correlated with clay mineral content and positively correlated with brittle mineral (quartz and feldspar) content. The fractal dimension calculated by the imaging method and the FHH method shows an upward increasing tendency in each of the parasequence cycles. This is as a result of different phenomena, varied sediment hydrodynamic forces leading to particle size differences and increased brittle minerals resulting in microcracks, therefore, the fractal dimension of the large pores (imaging method) increases upward in the parasequence. Simultaneously, with increased content and accompanied dissolution of brittle minerals causing an increase of small pores from base to top of the parasequence, the fractal dimension of the small pores (FHH method) grows.

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“… 22 , 23 Hence, fractal characterization of pore structures by an integrated method is commonly used lately. 24 , 25 Several studies also compared fractal dimensions determined using different techniques. 26 , 27 Evaluation of different fractal models is helpful to reveal the limitations and advantages of various models, which is crucial for promoting the application and development of the fractal theory in pore structure evaluation.…”

Section: Introductionmentioning

confidence: 99%

Pore Structure Characterization of Eocene Low-Permeability Sandstones via Fractal Analysis and Machine Learning: An Example from the Dongying Depression, Bohai Bay Basin, China

Lü

Liu

2021

ACS Omega

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Poroperm analysis, mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR) measurements were performed to delineate the pore structures and fractal behaviors of the Eocene low-permeability sandstones in the Dongying Depression, Bohai Bay Basin, China. Three types of pore structures (I, II, and III) have been classified by applying the self-organizing map (SOM) clustering model. Comparative analysis of three different fractal models indicates that the MICP tubular model and NMR model are quite effective for pore structure characterization. The results show that the reservoirs generally exhibit high fractal dimensions, indicative of complex pore structures. The presence of small pore throats is primarily responsible for the heterogeneities and complexities in the Eocene low-permeability sandstones. A modified Winland model was established for the permeability estimation using MICP data. Different from high-permeability reservoirs or unconventional (e.g., shale and tight formation) reservoirs, r 10 is the best parameter for permeability estimation, indicating that the permeability of the Eocene low-permeability sandstones is largely controlled by the large pore systems. Additionally, a porosity model derived from movable fluids using NMR data has been established and provided better prediction effect compared with the classic Coates and Schlumberger Doll Research (SDR) models. Fractal analysis and permeability estimation are shown to be quite effective for investigating microscopic behaviors and in predicting the reservoir quality of low-permeability sandstone reservoirs.

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Fractal analysis of high rank coal from southeast Qinshui basin by using gas adsorption and mercury porosimetry

Cited by 81 publications

References 47 publications

Investigation of pore structure characteristics and adsorption characteristics of coals with different destruction types

Investigation of pore structure characteristics and adsorption characteristics of coals with different destruction types

Pore Structure Characterization for a Continental Lacustrine Shale Parasequence Based on Fractal Theory

Pore Structure Characterization of Eocene Low-Permeability Sandstones via Fractal Analysis and Machine Learning: An Example from the Dongying Depression, Bohai Bay Basin, China

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