Methane Adsorption Rate and Diffusion Characteristics in Marine Shale Samples from Yangtze Platform, South China

Wei Dang, Jinchuan Zhang, Xiaoliang Wei, Xuan Tang, Chenghu Wang, Qian Chen and Yue Lei
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Wei Dang: School of Energy Resources, China University of Geosciences, Beijing 100083, China
Jinchuan Zhang: School of Energy Resources, China University of Geosciences, Beijing 100083, China
Xiaoliang Wei: School of Energy Resources, China University of Geosciences, Beijing 100083, China
Xuan Tang: School of Energy Resources, China University of Geosciences, Beijing 100083, China
Chenghu Wang: Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, China Earthquake Administration, Beijing 100085, China
Qian Chen: School of Energy Resources, China University of Geosciences, Beijing 100083, China
Yue Lei: School of Energy Resources, China University of Geosciences, Beijing 100083, China

Energies, 2017, vol. 10, issue 5, 1-23

Abstract: Knowledge of the gas adsorption rate and diffusion characteristics in shale are very important to evaluate the gas transport properties. However, research on methane adsorption rate characteristics and diffusion behavior in shale is not well established. In this study, high-pressure methane adsorption isotherms and methane adsorption rate data from four marine shale samples were obtained by recording the pressure changes against time at 1-s intervals for 12 pressure steps. Seven pressure steps were selected for modelling, and three pressure steps of low (~0.4 MPa), medium (~4.0 MPa), and high (~7.0 MPa) were selected for display. According to the results of study, the methane adsorption under low pressure attained equilibrium much more quickly than that under medium and high pressure, and the adsorption rate behavior varied between different pressure steps. By fitting the diffusion models to the methane adsorption rate data, the unipore diffusion model based upon unimodal pore size distribution failed to describe the methane adsorption rate, while the bidisperse diffusion model could reasonably describe most of the experimental adsorption rate data, with the exception of sample YY2-1 at high pressure steps. This phenomenon may be related to the restricted assumption on pore size distribution and linear adsorption isotherm. The diffusion parameters ? and ?/? obtained from the bidisperse model indicated that both macro- and micropore diffusion controlled the methane adsorption rate in shale samples, as well as the relative importance and influence of micropore diffusion and adsorption to adsorption rate and total adsorption increased with increasing pressure. This made the inflection points, or two-stage process, at higher pressure steps not as evident as at low pressure steps, and the adsorption rate curves became less steep with increasing pressure. This conclusion was also supported by the decreasing difference values with increasing pressures between macro- and micropore diffusivities obtained using the bidisperse model, which is roughly from 10 ?3 to 10 0 , and 10 ?3 to 10 ?1 , respectively. Additionally, an evident negative correlation between macropore diffusivities and pressure lower than 3–4 MPa was observed, while the micropore diffusivities only showed a gentle decreasing trend with pressure. A mirror image relationship between the variation in the value of macropore diffusivity and adsorption isotherms was observed, indicating the negative correlation between surface coverage and gas diffusivity. The negative correlation of methane diffusivity with pressure and surface coverage may be related to the increasing degree of pore blockage and the decreasing concentration gradient of methane adsorption. Finally, due to the significant deviation between the unipore model and experimental adsorption rate data, a new estimation method based upon the bidisperse model is proposed here.

Keywords: marine shale; adsorption rate characteristics; methane diffusivity; diffusion model; lost gas content estimation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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