- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- 【Updated on June 30, 2025】Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
Adsorption Factors in Enhanced Coal Bed Methane Recovery: A Review
-
- Theodora Noely Tambaria
- Department of Earth Resources Engineering, Kyushu University Department of Geological Engineering, Universitas Gadjah Mada
-
- Sugai, Yuichi
- Department of Earth Resources Engineering, Kyushu University
-
- Nguele, Ronald
- Department of Earth Resources Engineering, Kyushu University
Search this article
Description
Enhanced coal bed methane recovery using gas injection can provide increased methane extraction depending on the characteristics of the coal and the gas that is used. Accurate prediction of the extent of gas adsorption by coal are therefore important. Both experimental methods and modeling have been used to assess gas adsorption and its effects, including volumetric and gravimetric techniques, as well as the Ono–Kondo model and other numerical simulations. Thermodynamic parameters may be used to model adsorption on coal surfaces while adsorption isotherms can be used to predict adsorption on coal pores. In addition, density functional theory and grand canonical Monte Carlo methods may be employed. Complementary analytical techniques include Fourier transform infrared, Raman spectroscopy, XR diffraction, and C^^<13> nuclear magnetic resonance spectroscopy. This review summarizes the cutting-edge research concerning the adsorption of CO_2, N_2, or mixture gas onto coal surfaces and into coal pores based on both experimental studies and simulations.
Journal
-
- Gases
-
Gases 2 (1), 1-21, 2022-01-14
MDPI (Multidisciplinary Digital Publishing Institute)
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1050017057727078528
-
- ISSN
- 26735628
-
- HANDLE
- 2324/4785193
-
- Text Lang
- en
-
- Article Type
- journal article
-
- Data Source
-
- IRDB
- OpenAIRE