The components and pore structure of shale are complex due to the heterogeneous distribution of organic matter and the complex distributions of the minerals. The digital core, possessing the advantages of being economical and reusable, can be widely used to directly characterize the three dimensional (3D) micro-pore structure and to numerically simulate its physical properties. During construction of a digital shale core, it is a challenge to solve the multicomponent segmentation for the digital shale core, the contradiction between the sample size and image resolution, and the identification of the pore types in the 3D pore space. Therefore, an automatic workflow based on the gray gradient-maximum entropy-3D morphology was developed. The gray gradient-maximum entropy algorithm was used to segment each sub-image of focused ion beam scanning electron microscope images to generate segmented images. On this basis, the pore size distribution was optimized via 3D morphological erosion. Based on the concept of pore clusters, the organic and inorganic pores were identified using the 3D morphological method for the first time. The construction of a multicomponent digital shale core was realized. The 3D micro-pore structure of the organic and inorganic pores was characterized by pore connectivity, heterogeneity, and pore size distribution. The accuracy of the proposed method was verified using low-temperature N2 adsorption experiment data. The results of this study provide new insight into the multicomponent digital shale core construction and lay the foundation for the characterization of the petrophysical properties and micro-/nano-scale fluid flow simulations of shale.