干酪根
吸附
油页岩
石油工程
分子动力学
材料科学
化学
地质学
有机化学
计算化学
烃源岩
构造盆地
古生物学
作者
Yuanxiu Sun,Yijie Ma,Bo Yu,Wei Zhang,Liping Zhang,Ping Chen,Lu Xu
出处
期刊:Energy & Fuels
[American Chemical Society]
日期:2024-08-12
卷期号:38 (17): 15935-15971
标识
DOI:10.1021/acs.energyfuels.4c02206
摘要
With the increasing global energy demand, unconventional oil and gas, especially shale gas, have become an important natural gas resource. In the modern petroleum engineering field, CO2 is commonly used to displace shale gas. CH4 is the main component of shale gas; therefore, understanding the competitive adsorption behavior in the shale matrix is of great significance for optimizing shale gas production. This review explores the competitive adsorption behavior of CH4 and CO2 on a shale matrix from the perspective of molecular simulation and emphasizes the latest research progress in this field. First, several molecular simulation methods for studying gas adsorption are introduced, including density functional theory (DFT), grand canonical Monte Carlo (GCMC), molecular dynamics (MD), coarse-grained molecular dynamics (CGMD), and dissipative particle dynamics (DPD). The competitive adsorption behavior of CO2/CH4 on organic kerogen models, inorganic mineral models, and organic–inorganic composite shale models is discussed, comparing the gas adsorption differences on different shale molecular models. Additionally, the multi-scale simulation methods for shale gas combined with molecular simulations and the application of machine learning (ML) methods are also discussed. Finally, the influence of factors such as the temperature, pressure, moisture content, and pore size on competitive adsorption behavior is analyzed. The challenges and prospects in the current competitive adsorption simulation of CO2/CH4 are summarized, such as constructing shale organic–inorganic composite pore models that combine pore structure and surface chemical heterogeneity and comprehensively considering the multi-scale migration of shale gas from atomic scale to mesoscopic scale to macroscopic scale. This research provides important theoretical support for optimizing the development of natural gas resources and promoting CO2 sequestration technology.
科研通智能强力驱动
Strongly Powered by AbleSci AI