Due to the multi-scale pore size and complex gas-bound water distribution, it is challenging to accurately predict gas transport property in shale. Given the known heterogeneities, single-resolution pore-scale imaging is not reliable for representative pore structure characterization. In this study, the image-based shale multi-scale pore network model (MPNM) is proposed and the impacts of pore structure and relative humidity (RH) on gas transport are analyzed in detail. 3D binary images are constructed by the multiple-point statistics method from a section of low-resolution SEM image which covers the large-scale pore structure and fine-scale SEM images with the same physical size at high resolution. The maximal ball fitting method is applied to extract large-scale pore network model (LPNM) and fine-scale pore network models (FPNMs) from the 3D binary images, respectively. MPNM is obtained by merging the LPNM and FPNMs based on the proposed procedure. The confined gas-bound water distribution at different RH is calculated considering the disjoining pressure resulting from van der Waals force, electric double-layer interactions and structural force. Gas slippage in irregular pores is considered for gas transport. Pore structure parameters and gas permeabilities are calculated based on the MPNM, LPNM and FPNMs. Study results indicate that the gas permeability of MPNM is more close to the laboratory pressure pulse decay measured gas permeability of studied sample. Gas permeability decreases with the increasing RH and drops to zero at average pore radius less than 12 nm and RH larger than 0.7. Article Highlights The image-based shale multi scale pore network model (MPNM) is proposed based on low resolution and high resolution SEM images. Permeability of MPNM is more close to the laboratory measured permeability compared with that of fine scale and large scale pore network. Gas permeability drops to zero at average pore radius less than 12 nm and relative humidity larger than 0.7.