## 4 Discussion
### Fractal Characteristics and Heterogeneity of Pores  
Pore structure parameters (PSDs, pore morphology, pore type, etc.) and physical parameters, such as porosity and permeability, are commonly used for the evaluation of unconventional reservoirs. However, practical problems during exploration show that it is difficult to build a sufficiently accurate reservoir prediction scheme based on these parameters. This is mainly because non-intuitive parameters, such as heterogeneity, are ignored, especially when reservoir evaluation or prediction is carried out in the gas-bearing system composed of layers with different properties or lithology. As a parameter for evaluating the self-similarity of structure, fractal dimension can measure the similarity between different scales and further characterize the complexity and heterogeneity of pore structure to a certain extent. Tables 2 and 3 list the fractal parameters of the samples. Fractal modeling results show that adsorption pores and seepage pores are significantly fractal. The difference between the D\({}_{1}\) value and D\({}_{3}\) value of each sample can reflect the relative complexity of its pore structure. However, we found that the fractal dimension parameters of different lithologic samples are also significantly different. This is mainly manifested in (1) the degree of change between samples of the same lithology and (2) the stability of these data for different lithology samples. D\({}_{1}\) values are calculated based on data from seepage pores (Table 2). Comparing the D\({}_{1}\) values of coal, shale, and tight sandstone samples, it can be seen that the data difference between shale samples and the fluctuation is the smallest. Under the control of reservoir diagenesis, all shale samples mainly preserve nanoscale pores, and the characteristics of \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Pore Size** & **Coal** & **Shale/Mudstone** & **Tight Sandstone** \\ \hline \multirow{3}{*}{\(<\)10 nm} & \multirow{3}{*}{*} & Metamorphic pores & \multirow{3}{*}{*} & \multirow{3}{*}{Intercrystalline pores in clay interstitial substance} \\  & & Intermorthic pores & & \\  & & Intermolecular pores & & \\ \hline \multirow{3}{*}{10–100 nm} & \multirow{3}{*}{*} & Phyteral residual pores & \multirow{3}{*}{*} & \multirow{3}{*}{\begin{tabular}{c} Clay-related pores \\ Pores in \\ mineralogical edge \\ \end{tabular} } & \multirow{3}{*}{*} & \multirow{3}{*}{\begin{tabular}{c} Intercrystalline pores in clay interstitial substance; grain dissolution pores \\ \end{tabular} } \\  & & Microorganic constituents & & \\  & & interparticle nanopores & & \\  & Pores in mineralogical edge & & & \\ \hline \multirow{3}{*}{100–1000 nm} & \multirow{3}{*}{\
\begin{tabular}{c} Thermally pores \\ Mineral related pores \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} Brittle mineral pores \\ Microfractures \\ \end{tabular} } & \multirow{3}{*}{*} & \multirow{3}{*}{Residual interparticle pores; grain dissolution pores} \\  & & & \\ \hline \(>\)10\(\mu\)m & * & Fractures and cleats & Fractures & Fractures \\ \hline \hline \end{tabular}  
* represents the major pore size distribution range.  
\end{table} 
Table 5: The systematic classification and comparison of reservoir space of high-rank coal, shale, and tight reservoirs at nanoscale to fracture scale. pore structure are more stable. This may be affected by the particle size of the material components and the scale effect. Nanoscale pores in unconventional reservoirs have obvious heterogeneity characteristics that significantly affect the enrichment, storage, and transportation of gases as well as the spatial distribution, brittleness, and productivity of reservoirs [30]. Nano-scale pores are the predominant reservoir space for gas absorption and storage in tested samples. The development of transitional and microabsorption pores controls the gas-bearing and microscale seepage capacity of the matrix.