Journal of Petroleum Exploration and Production Technology (Apr 2020)

The influence of moisture content on coal deformation and coal permeability during coalbed methane (CBM) production in wet reservoirs

  • Akash Talapatra,
  • Md. Mostafijul Karim

DOI
https://doi.org/10.1007/s13202-020-00880-x
Journal volume & issue
Vol. 10, no. 5
pp. 1907 – 1920

Abstract

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Abstract Moisture adsorption in the coal seams affects the gas adsorption capacity and can alter the coal deformation and permeability criteria of the coal seam. The effect of dynamic loss of moisture content, both on moisture and gas sorption-induced coal swelling/shrinkage strains, during the coalbed methane (CBM) production, is crucial. This study investigates the interactions among coal matrix, absorbed gas, and moisture content, based on the coal swelling/shrinkage strains and gas adsorption decay criteria. Consequently, a mathematical model of the coal deformation is developed for the proper evaluation of the moisture effect. For developing the model, this paper considers the standard gas flow and moisture loss equations to assess the volumetric content, equilibrium pressure, and density of the moisture. Finally, it comprehensively analyzes the sensitive factors and effects of elemental parameters of moisture content on coal deformation and coal permeability. The results show that moisture content at adsorbed state significantly changes the coal swelling/shrinkage strain and that distorted swelling and shrinkage characteristics can promote the permeability alternation in wet coal reservoirs. Moreover, the intermolecular attraction between the coal structure and the moisture content has a significant effect on methane adsorption/desorption-induced deformation in coal structure. This study also designs the coal deformation strains as a function of moisture content by the Langmuir type model and evaluates the hysteresis rate between the swelling and shrinkage characteristics. The findings of this paper can characterize a wet coal reserve for CBM production and anticipate future production under different operating conditions.

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