Non-linear gas desorption and transport behavior in coal matrix: Experiments and numerical modeling

Peng Liu, Yueping Qin, Shimin Liu, Yongjiang Hao

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

Gas desorption and transport in coal matrix plays pivot roles to estimate in situ gas content, forecast gas production from coalbed methane (CBM) wellbores, classify the gas/coal outburst proneness of coal seams and estimate gas emission rate for active mine ventilation planning. Only using Fick's law to depict methane transport in coal matrix may result in an erroneous prediction because it uses only adsorbed phase gas to calculate methane concentration gradient. In this study, a series of coal-methane ad/desorption experiments were carried out under different pressure boundary conditions. Following this, an effort is made to propose a semi-empirical desorption model describing the entire methane diffusion process and discuss its superiority and applicability by comparing to various commonly used models. The proposed approach includes two different theoretical models (Fick diffusion model, assuming concentration-difference transports gas; and Density model, assuming density-difference transports gas), to model methane diffusion corresponding to the experimental sections conducted in this study. Afterward a series of comparisons between the experimental desorption data and two sets of simulated desorption data obtained by numerically calculating the two theoretical models were conducted, and it shows that Density model exhibited a higher accuracy over Fick model. The proposed Density model is more effective in describing the non-linear gas diffusion behavior in coal matrix for the experimentally studied coals. Essentially, the Density model covers and promotes the Fick diffusion model, and is competent in mathematically modeling both adsorbing gas and non-adsorbing gas transport behavior in porous media. Moreover, the Density model can be directly incorporated to the existing dual-porosity model to model methane migration in coal matrix in coal seam.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalFuel
Volume214
DOIs
StatePublished - Feb 15 2018

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Organic Chemistry

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