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Research Papers: Alternative Energy Sources

Experimental Study on Identification Diffusion Pores, Permeation Pores and Cleats of Coal Samples

[+] Author and Article Information
Mingjun Zou

School of Resource and Environment,
North China University of Water Resources and Electric Power,
Zhengzhou 450045, China
e-mail: zoumingjun2008@163.com

Chongtao Wei

School of Resource and Earth Science,
China University of Mining and Technology,
Xuzhou 221116, China
e-mail: weighct@163.com

Zhiquan Huang

School of Resource and Environment,
North China University of Water Resources and Electric Power,
Zhengzhou 450045, China
e-mail: huangzhiquan@ncwu.edu.cn

Miao Zhang

He'nan Province Research Institute of
Coal Geological Prospecting,
Zhengzhou 450052, China
e-mail: zhangmiaoms@163.com

Xiaochun Lv

School of Resource and Environment,
North China University of Water Resources and Electric Power,
Zhengzhou 450045, China
e-mail: xc66995618@163.com

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received December 12, 2014; final manuscript received September 11, 2015; published online October 15, 2015. Assoc. Editor: Gunnar Tamm.

J. Energy Resour. Technol 138(2), 021201 (Oct 15, 2015) (8 pages) Paper No: JERT-14-1406; doi: 10.1115/1.4031610 History: Received December 12, 2014; Revised September 11, 2015

Coal pore systems can be commonly classified as diffusion pores, permeation pores and cleats. The classification accuracy influences the coalbed methane (CBM) migration processes from diffusion to permeation and then to outflow, and finally affects the predicted CBM recoverability. To classify coal pore systems precisely, measurements of nuclear magnetic resonance (NMR), mercury intrusion porosimetry (MIP), and nitrogen adsorption isotherm (NAI) are conducted in this paper, and then a comprehensive classification method is proposed. The following cognitions are achieved. NMR spectra can be divided into three categories of three-peak, single narrow peak, and non-three/non-single-narrow peak spectra. The former two categories can be directly used to identify coal pore systems as one peak representing one pore system, and pore systems of the last category can be distinguished by using cumulative amplitudes at the fully water-saturated and centrifuged conditions. Fractal theory suggests that the dividing radii of diffusion–permeation pores obtained by MIP and NAI are quite close, which indicates that the two methods are both effective and accurate. Comparisons between mercury intrusive and cumulative amplitudes indicate that the classification results obtained by measurements of MIP and NMR are similar, which can be a base for transforming transverse relaxation time to pore radius. As a result, the dividing radius of diffusion–permeation pores is about 65 nm, and that of permeation–cleat pores is approximately 600–700 nm.

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References

Figures

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Fig. 1

T2 spectra for ten coal samples (F: fully water-saturated; C: centrifuged)

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Fig. 2

Coal pore systems of three-peak spectra (left: sample CS5; right: sample CS8; pore I: diffusion pores; pore II: permeation pores; pore III: cleats)

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Fig. 3

Coal pore systems of single narrow peak spectra (left: sample CS9; right: sample CS10; pore I: diffusion pores; pore II: permeation pores; pore III: cleats)

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Fig. 4

Comparisons between the two classification results for samples CS5 (left) and CS8 (right) (pore I: diffusion pores; pore II: permeation pores; pore III: cleats)

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Fig. 5

Identifying pore systems based on the cumulative amplitudes

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Fig. 6

Relationships between ln(dSPr/dPr) and lnPr

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Fig. 7

Relationships between ln[ln(Po/P)] and ln(V/Vm)

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Fig. 8

Extrusive mercury curves for ten coal samples

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Fig. 9

Comparisons between curves of cumulative amplitudes and extrusive mercury (left: sample CS1; right: sample CS2)

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