Numerical Simulation of Natural Gas Transport in Shale Formation Using Generalized Lattice Boltzmann Method

Abstract

Abstract In shale formations, natural gas flows either through nano-scale pores or fractures during production period. Darcy's law cannot effectively describe such transport phenomena due to its continuum assumption. Alternatively, kinetic-based lattice Boltzmann method (LBM) becomes a strong candidate of simulating organic-rich shale reservoir that contains a large amount of nano-scale pores. Among various LBM models, multiple-Relaxation-Time (generalized) LBM is considered as one of the most efficient models regarding its theories, selections of parameters, and numerical stability. For gas flow in a confined system, its molecular mean free path depends on not only the size of the confined system, but also the distance of gas molecules from solid walls. A large amount of natural gas is believed to be stored in extremely small organic pores, and adsorption in shale has a significant influence for gas transport in production. In this paper, we incorporated adsorption into generalized LBM model in order to capture the natural gas flow in organic nano-pores. Many factors are believed to control the flow mechanism in such pores, such as the size of organic pores, specific surface area, adsorptive strength, and so on. Generalized LBM results shows a great agreement with available data for high Knudsen flows between two-dimensional parallel plates. Accounted the effect of adsorption, flow phenomena are investigated by varying different controlling factors in both simple and complex structures. Introduction Shale gas has been becoming a significant source of unconventional natural gas. The production of shale gas mainly depends on its characteristics, such as the pore distribution, organic richness, natural/factitious fractures, etc. A significant portion of shale gas is stored in kerogen pores that are ranging 2nm to 50 nm [1, 2, 3]. Consequently, it is essential to understand natural gas flow in nanopores to be able to predict long-term shale gas production as well as shale gas reserves.