Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal‐balls‐like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two‐phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

A large amount of nano-pores exists in pore clusters in shale gas reservoirs. In addition to the multiple transport regimes that occur on the nanoscale, the pore space is another major factor that significantly affects the shale gas recoverability. An investigation of the pore-scale shale gas flow is therefore important, and the results can be used to develop an effective cluster-scale pore network model for the convenient examination of the process efficiency. Focused ion beam scanning electron microscope imaging, which enables the acquisition of nanometre-resolution images that facilitate nano-pore identification, was used in conjunction with a high-precision pore network extraction algorithm to generate the equivalent pore network for the simulation of Darcy and shale gas flows through the pores. The characteristic parameters of the pores and the gas transport features were determined and analysed to obtain a deeper understanding of shale gas flow through nanoscale pore clusters, such as the importance of the throat flux–radius distribution and the variation of the tortuosity with pressure. The best parameter scheme for the proposed effective model of shale gas flow was selected out of three derived schemes based on the pore-scale prediction results. The model is applicable to pore-scale to cluster-scale shale gas flows and can be used to avoid the multiple-solution problems in the study of gas flows. It affords a foundation for further study to develop models for shale gas flows on larger scales.

Characterization of shale cores with low and anisotropic permeability is complicated, due to the presence of multiscale pore structure and thin layers, and defies conventional methods. To accurately reproduce the morphology of multiscale pore structure of the shale core, a novel core-scale reconstructing method is proposed to reconstruct 3D digital-experimental models by means of the combination of SEM, EDS images, nitrogen adsorption and pressure pulse decay experiment result. In this method, the multiscale and multicomponent reconstructing algorithm is introduced to build the representative multiscale model for each layer, which can describe the complex 3D structures of nano organic pores, micro-nano inorganic pores, micro slits and several typical minerals. Especially, to reproduce the realistic morphology for shale, the optimization algorithm based on simulated annealing algorithm uses the experimental data as constrain conditions to adjust and optimize the model for each layer. To describe the bedding characteristics of the shale core, bedding fractures are constructed by analysis of the mineral distribution in the interface of two layers, and then the representative models for different layers are integrated together to obtain the final core-scale digital-experimental model. Finally, the model is validated by computing its morphological and flow properties and comparing them with those of the actual 3D shale sample. This method provide a way for systematically and continuously describe the multiscale and anisotropic pore structure (from nm-cm) of the shale core, and will be helpful for understanding the quality of the shale reservoir.

The heterogeneous pore space of porous media strongly affects the storage and migration of oil and gas in the reservoir. In this paper, the cross-correlation-based simulation (CCSIM) is combined with the three-step sample method to reconstruct stochastically 3D models of the heterogeneous porous media. Moreover, the two-point and multiple-point connectivity probability functions are used as vertical constraint conditions to select the boundary points of pore and matrix, respectively. The heterogeneities of pore spaces of four rock samples are investigated, and then our methods are tested on the four samples. Quantitative comparison is made by computing various statistical and petrophysical properties for the original samples, as well as the reconstructed model. It was found that the results from CCSIM-TSS are obviously better than that from CCSIM. Finally, the analysis of the distance (ANODI) was used to measure of the variability between the realizations of the four rock samples. The results demonstrated that the results from CCSIM-TSSmp are better than that from CCSIM-TSStp as the complexity of connectivity and heterogeneities of pore spaces increase.

Organic-rich shales have abundant micronanopores and slits. Most micronanopores exist in organic matter and pyrites. Pore size distribution significantly influences shale gas flow. In micronanopores of organic matter and pyrites, pore size distribution has a self-imitating or fractal property. This property is helpful in upscaling calculation. In this work, intermingled fractal model for organic-rich shale is investigated. First, on the basis of scanning electron microscopy (SEM) images of shale samples in Longmaxi shale formation, fractal units are built-in representative elementary surfaces of organic matter and pyrites. Second, intermingled fractal models (IFMs) are then built considering the organic matter fractal pore units, the pyrite fractal pore units, and slits. Influences of fractal parameters on apparent gas permeability of IFMs are investigated. Third, an upscaled shale model is successfully built using the mirror image method. This upscaling method is verified by comparing the apparent gas permeability between upscaled models and experimental results. The upscaling method based on fractal theory can significantly shorten the calculation time and provide a promising way for apparent gas permeability calculation in the upscaled model.