Multi-scale pore network modelling of fluid mass transfer in nano-micro porous media

摘要

It is widely accepted that pore size distribution and spatial pore connectivity directly impact on the macroscopic porous medium transport properties. Therefore it is indispensable to characterize nano-micro porous media like shale with multi-scale pore structure to accurately assess fluid transport properties. In this study, we propose a multi-scale pore network model to estimate the fluid transport properties. A 3D binary inorganic porous structure model is constructed from a section of scanning electron microscopy (SEM) image which only images large scale inorganic pores and its corresponding inorganic pore network is extracted by the maximal ball fitting method. The nano-porous organic matter is treated as the virtual throat which is embedded in series or parallel connection with the inorganic throat on the original inorganic pore network. Three parameters namely the ratio of total amount of the virtual throat to the total amount of the inorganic throat, the proportion of virtual throat in parallel connection with the inorganic throat and average organic pore radius inside the organic matter are applied to analyze the impact of multi-scale pore structure characteristic on fluid transport properties. The constructed multi-scale pore network model accounts for the organic matter distribution, organic matter total volume, organic pore size, inorganic pore structure and connectivity characteristic between organic and inorganic system all together. Nano-micro scale fluid transport mechanisms are considered in modelling fluid mass transfer. Key analysis results indicate that the fluid mass transfer in nano-micro porous media is influenced by the nano-porous organic matter distribution pattern and it's local volume. The series connection of nano-porous organic matter and the increase of virtual throat amounts significantly decrease the fluid transport ability. Furthermore, the established multi-scale pore network model is used to interpretate laboratory pressure pulse decay response curve. (C) 2019 Elsevier Ltd. All rights reserved.