Enhanced gas recovery (EGR) by carbon dioxide (CO2) injection to gas-bearing shale formations is proven to be feasible and beneficial both computationally and experimentally from pore scale to field scale. In addition to the improved recovery factor, CO2 is trapped in the geological formation, which provides an alternative approach to mitigate the CO2 emission problem. When supercritical CO2 is injected, the preferential adsorption and dissolution of CO2 in nanopores and organic matter enables the displacement of shale gas by CO2. This mechanism has been investigated by molecular simulation, but not much has been done by classical density functional theory (DFT). In this work, we apply molecular DFT to study the competitive adsorption of CO2 with shale gas at various conditions. The DFT model is firstly verified by grand canonical Monte Carlo (GCMC) simulation in graphite slit pores for pure and binary component systems at different temperatures, pressures, pore sizes and bulk compositions for methane/ethane/ CO2. Then the model is utilized to predict the CO2 adsorption selectivity in multicomponent systems which include two different shale gases. We demonstrate the sensitivity of CO2 selectivity to temperature, pressure, nanopore size and shale gas average molecular weight. Subsequently, we model the CO2/CH4 adsorption in pores at more realistic conditions, in which we consider different levels of moisture in the pore and the gas dissolution in organic matrix. We show the presence of water inside a nanopore greatly reduces the CO2 adsorption but improves the CO2 selectivity with respect to methane. The presence of organic matter kerogen also increases the CO2 selectivity. In summary, molecular DFT is a promising and efficient method that facilitates understanding the fundamental mechanism and predicting the increased gas recovery by CO2 injection.

Understanding enhanced gas recovery from CO2 competitive sorption in shale nanopores by molecular density functional theory

2019 Spring National Meeting

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