These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs. (3.04 MB)

Methane/Carbon Dioxide Partitioning in Clay Nano- and Meso-Pores: Molecular Dynamics Modeling with Constant Reservoir Composition

submitted on 28.01.2019, 17:08 and posted on 29.01.2019, 15:56 by A. Ozgur Yazaydin, Narasimhan Loganathan, Geoffrey Bowers, Andrey Kalinichev, Brice Firmin Ngouana Wakou, R. Jim Kirkpatrick
The interactions among fluid species such as H2O, CO2, and CH4 confined in nano- and meso-pores in shales and other rocks is of central concern to understanding the chemical behavior and transport properties of these species in the earth’s subsurface and is of special concern to geological C-sequestration and enhanced production of oil and natural gas. The behavior of CO2, and CH4 are less well understood than that of H2O. This paper presents the
results of a computational modeling study of the partitioning of CO2 and CH4 between bulk fluid and nano- and meso-pores bounded by the common clay mineral montmorillonite. The calculations were done at 323 K and a total fluid pressure of 124 bars using a novel approach (constant reservoir composition molecular dynamics, CRC-MD) that uses bias forces to maintain a constant composition in the fluid external to the pore. This purely MD approach overcomes the difficulties in making stochastic particle insertion-deletion moves in dense fluids encountered in grand canonical Monte Carlo and related hybrid approaches. The results show that both the basal siloxane surfaces and protonated broken edge surfaces of montmorillonite both prefer CO2 relative to CH4 suggesting that methods of enhanced oil and gas production using CO2 will readily displace CH4 from such pores. This preference for CO2 is due to its preferred interaction with the surfaces and extends to approximately 20 Å from them.


UK Materials and Molecular Modelling Hub, which is partially funded by EPSRC (EP/P020194/1)

National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under ECARP No. m1649

United States Department of Energy, Office of Science, Office of Basic Energy Science, Chemical science, Biosciences, and Geosciences division through the sister grants DE-FG02-10ER16128 (Bowers, P.I.) and DE-FG02-08ER15929 (Kirkpatrick, P.I. and Yazaydin, co-PI)

European Union’s Horizon 2020 research and innovation program under grant agreements No. 640979 and 764810


Email Address of Submitting Author


University College London


United Kingdom

ORCID For Submitting Author


Declaration of Conflict of Interest

No conflict of interest