The exploration and development of shale gas require accurate modeling and characterization of shale samples. Digital rocks have been widely used to characterize the shale samples, predict their petrophysical properties, and understand the pore-scale transport mechanisms in micrometer and nanometer pore systems. Previous studies from numerous geologists have indicated that the shale samples involve multitype minerals and multiscale pore systems. Therefore, such factors must be considered when shale models are constructed and characterized. Nevertheless, the imaging techniques such as X-ray CT scanners and FIB-SEM have to make a balance between high resolution and large field of view. In other words, current 3D imaging techniques either cover the large-scale structures at a low resolution or cover a small region at a high resolution. To address this issue, this study proposes a novel modeling technique, called process-based modeling, which combines the discrete element modeling method, quartet structure generation set algorithm, and morphology operation techniques. The proposed technique can generate various types of minerals (such as quartz, feldspar, calcite clay minerals, and pyrite) and pore structures (interparticle pores, intraparticle pores, and organic-matter pores) in shale samples. In order to evaluate the performance of the algorithm, multiple shale models were constructed. By analyzing the volume fraction of each component in the models and the pore/throat size distribution, average coordination number, and fractal dimension, and the tortuosity of the pore structures, the shale models were characterized. The modeling accuracy of the method was tested by comparing the petrophysical properties from the constructed digital models and experimental data. Based on the constructed shale models, the single-phase flow simulation of the gas was carried out using pore network modeling. In summary, this study presents a powerful digital core modeling algorithm. Compared with other modeling algorithms, the advantage of this method is that it fully considers multitype minerals and multiscale pore systems, and the constructed multicomponent and multiscale digital cores can be applied to the study of various petrophysical properties.