Factors influencing methane diffusion behaviors in micro-nano coal pores: a comprehensive study

doi:10.1007/s11707-022-0992-3

Front. Earth Sci.

2023, Vol. 17

Issue (1) : 71-86 https://doi.org/10.1007/s11707-022-0992-3

RESEARCH ARTICLE

Factors influencing methane diffusion behaviors in micro-nano coal pores: a comprehensive study

Xianglong FANG^1,², Dameng LIU^1,², Yingfang ZHOU³, Xiaobo LIU⁴(

), Yidong CAI^1,²(

)

¹. School of Energy Resources, China University of Geosciences, Beijing 100083, China
². Coal Reservoir Laboratory of National Engineering Research Center of CBM Development & Utilization, China University of Geosciences, Beijing 100083, China
³. School of Engineering, Fraser Noble Building, King's College, University of Aberdeen, AB24 3UE Aberdeen, UK
⁴. Postdoctoral Workstation of Applied Technology Research Institute, Northeast Petroleum University, Daqing 163318, China

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Abstract

Gas diffusion in the coal matrix plays a significant role in forecasting the production performance of coalbed methane (CBM) wells. To better understand methane diffusion behavior, a systematic study was performed on various rank coals with vitrinite reflectance (R_o,m) ranging from 0.46% to 2.79%. Multiple experiments, including coal petrographic analysis, field emission scanning electron microscopy (FESEM), low-temperature N₂ adsorption/desorption, and mercury intrusion porosimetry (MIP), were conducted to quantitatively characterize the multiscale micro-nano pore system in different rank coals, which showed that the pore structure of coals exhibited a multimodal pore size and volume distribution. Isothermal adsorption-diffusion experiments using the volumetric method were also performed to understand the methane diffusion characteristics in the micro-nano pores of the coal reservoir. The applicability of the multiporous diffusion model is verified, and methane diffusion in the multi-scale pores of coal reservoirs exhibits the characteristics of early fast diffusion, transitional diffusion in the medium term, and slow diffusion in the later period. In addition, the factors affecting methane diffusion in coals were systematically analyzed, and gray relational analysis (GRA) was employed to analyze and identify the importance of these factors on methane diffusion. The results show the impact ranking of factors, in order from the most important to the least: particle size > moisture > surface area > pore volume > pressure > coal rank > temperature in all of three diffusion stages. These findings are helpful for forecasting production performance and enhancing the production efficiency of CBM.

Keywords coalbed methane reservoir micro-characteristic diffusion coefficient grey relational analysis

Corresponding Author(s): Xiaobo LIU,Yidong CAI

About author:

^* These authors contributed equally to this work.

Online First Date: 15 March 2023 Issue Date: 03 July 2023

Cite this article:

Xianglong FANG,Dameng LIU,Yingfang ZHOU, et al. Factors influencing methane diffusion behaviors in micro-nano coal pores: a comprehensive study[J]. Front. Earth Sci., 2023, 17(1): 71-86.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-022-0992-3
https://academic.hep.com.cn/fesci/EN/Y2023/V17/I1/71

Tab.1 Sample basic information and structure analysis results of the selected coals

Fig.1 Oil-immersed photographs of maceral and minerals and FESEM images of pore structure in different rank coals. (a) HJG 5#, R_o,m = 1.34%, 200 × ; (b) DQ 4#, R_o,m = 1.52%, 200 × ; (c) DY 6#, R_o,m = 2.56%, 200 × ; (d) GZ 15#, R_o,m = 2.79%, 200 × ; (e) YT 5#, R_o,m = 1.19%, 10650 × ; (f) SY 15#, R_o,m = 2.05%, 4140 × ; (g) XY 15#, R_o,m = 2.54%, 6350 × ; (h) DY 6#, R_o,m = 2.56%, 14940 × .

Fig.2 (a) The relationship between pore surface area and coal rank; (b) The relationship between total pore volume and pore surface area.

Fig.3 The mercury intrusion-extrusion curves of different rank coals.

Fig.4 Fitting curves of experimental data using bidisperse and multiporous diffusion model.

Fig.5 Schematic of diffusion influencing factors (a) morphology of pore-fractures from FESEM images; (b) relationship between coal rank and adsorption capacity or pore surface area; (c) diffusivity in coals with different particle size; (d) clay minerals swelling when absorbing moisture; (e) molecular motion at high temperature; (f) molecular motion at high pressure.

Tab.2 The integrated data of pore volume and pore surface area by MIP and low-temperature nitrogen analysis

Fig.6 (a) Composite graph of diffusion coefficient ratio and pore volume fraction of different diffusion stage; (b) redraw the micropore diffusion stage in (a); (c) composite graph of diffusion coefficient ratio and pore surface area fraction of different diffusion stage.

Fig.7 (a) Methane diffusivities of different rank coal samples using multiporous model; (b) methane diffusivities with pressure using multiporous model. Notes: D_ae: the macropore effective diffusion coefficient; D_ee: the transition pore and mesopore effective diffusion coefficient; D_ie: the micropore effective diffusion coefficient.

Fig.8 (a) Methane diffusivities with particle size; (b) methane diffusivities with moisture content; (c) methane diffusivities with temperature using multiporous model. Notes: D_ae: macropore effective diffusion coefficient; D_ee: transition pore and mesopore effective diffusion coefficients; D_ie: micropore effective diffusion coefficient.

Tab.3 Methane diffusion coefficients and test data of each influencing factor

Fig.9 The gray relational grade for seven comparability sequences with three diffusion stage.

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