14-17 May 2018
New Orleans
US/Central timezone

Storage and recovery of multi-component mixtures in single shale pores

14 May 2018, 10:05
New Orleans

New Orleans

Oral 20 Minutes MS 1.32: Sorption, Phase Behavior, and Fluid Transport in Fractured Black Shales Parallel 1-E


Prof. Rui Qiao (Virginia Tech)


Natural gas production from shale formations has received extensive attention in recent years. While great progress has been made in understanding the adsorption and transport of single-component gas (usually CH$_4$) inside shales’ nanopores, the adsorption and transport of multicomponent shale gas under more realistic reservoir conditions (e.g., considering CH$_4$/C$_2$H$_6$ mixture) only begun to be studied. In this work, we use molecular simulations to compute the storage of CH$_4$/C$_2$H$_6$ mixtures in single nanopores and their subsequent recovery. We show that, surface adsorption contributes greatly to the storage of CH$_4$ and C$_2$H$_6$ inside the pores, and C$_2$H$_6$ is enriched over CH$_4$. The enrichment of C$_2$H$_6$ is enhanced as the pore is narrowed, but is weakened as the pressure increases. These effects are captured by the ideal adsorbed solution (IAS) theory, but the theory overestimates the adsorption of both gases. We show that the recovery of gas mixtures inside the nanopores toward a gas bath approximately follows the diffusive scaling law. The ratio of the production rate of C$_2$H$_6$ and CH$_4$ is close to their initial mole ratio inside the pore despite that the mobility of pure C$_2$H$_6$ is much smaller than that of pure CH$_4$ inside the pores. By using scale analysis and by computing the Onsager coefficients for the transport of binary CH$_4$/C$_2$H$_6$ mixtures inside the nanopores, we show that the strong coupling between the transport of C$_2$H$_6$ and CH$_4$ is responsible for the effective recovery of C$_2$H$_6$ from the nanopores.


H. Wu, Y. He, and R. Qiao, "Recovery of multicomponent shale gas from single nanopores", Energy & Fuels, 31, 7932, 2017

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Primary authors

Mr Haiyi Wu (Virginia Tech) Prof. Rui Qiao (Virginia Tech)

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