Molecular simulation of CH4/CO2/N2 ternary mixture competitive adsorption and diffusion dynamics in tight sandstone
Abstract
Injecting impure CO 2 for enhanced gas recovery (CO 2 -EGR) offers a dual benefit by improving natural gas extraction while enabling CO 2 sequestration. However, the interactions between CO 2 , N 2 , and CH 4 under reservoir conditions require further investigation. This study employs Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations to quantify the adsorption and diffusion behaviors of CO 2 , N 2 , and CH 4 in quartz nanopores over a pressure range of 1–24 MPa under varying water saturations and gas compositions. The results indicate that: (1) CO 2 exhibits the broadest energy distribution and the strongest adsorption stability, occupying about 20 %–30 % more adsorption sites than CH 4 or N 2 and showing the least sensitivity to water saturation, with only a 30 % reduction at 50 % saturation, compared to 60 % for CH 4 , giving CO 2 a clear competitive advantage. (2) The adsorption and desorption behaviors are strongly pressure dependent, as increasing pressure reduces the adsorption layer area and shifts gas distribution from adsorption dominated to free phase. Competitive adsorption analysis reveals that while CO 2 dominates displacement at low pressures, mixtures that contain N 2 achieve higher CH 4 desorption efficiency above 13 MPa by mitigating diffusion resistance. (3) A higher N 2 fraction improves CH 4 diffusion coefficients, thereby facilitating gas mobility and ensuring superior recovery performance under high-pressure conditions. This study advances the fundamental knowledge of microscale gas behavior in tight sandstones and supports the feasibility of impure CO 2 injection as a practical strategy for sustainable gas production.
Fields of Study & Subjects
CO2 Sequestration and Geologic Interactions
Enhanced Oil Recovery Techniques
Hydrocarbon exploration and reservoir analysis
Publication details
- Journal / source
- Natural Gas Industry B
- Publisher
- Elsevier BV
- Volume
- 13
- Issue
- 1
- Pages
- 77–92
- Publication date
- 1 February 2026
- Language
- EN