## 1 Introduction
We have prepared a schematic diagram to depict this phenomenon, as illustrated in Figure 1.  
Figure 1 illustrates a schematic where the MICP method overestimates meso-pores and underestimates macro-pores. The overestimated part is almost equal to the underestimated part. The occurrence of this phenomenon is commonly ascribed to \"ink-bottle\" phenomenon [32]. Some scholars believe that NMR measures the pore size distribution (PSD), while MICP assesses the pore throat distribution (PTD) [34; 35; 36]. Mercury injection is a dynamic process with recorded pressure, while NMR PSD is a static process where brine pre-saturates the core to almost 100%. NMR PSD could reflect all the pores saturated with brine, while MICP is more sensitive to the throat due to the ink bottle effect [37; 38]. Multiple researchers have reported that MICP overestimates the percentage of the meso-pores, corresponding to the relatively low capillary pressure range [32; 39]. This phenomenon reflects the detailed pore throat matching pattern and is closely linked to the permeability of the core. We believe that this information could be used to gain a better understanding of pore structure. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Author** & **Porous Media Type** & **Crosspoint** & **Overestimated Part** \\ \hline [PERSON] et al. [29] & Shaly sandstone & 170 ms & 100–170 ms \\ [PERSON] et al. [30] & Carbonate & 1300 ms & 700–1300 ms \\ [PERSON] and [PERSON] [31] & Sandstone & 0.25 μm & 0.11–0.25 μm \\ [PERSON] [32] & Wood’s metal & 9 μm & 0.05–9 μm \\ [PERSON] et al. [33] & Tight sandstone & 0.4 μm & 0.1–0.4 μm \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The discrepancy between MICP and NMR methods. In this study, we focused on Tuha tight sandstones and Hechuan shales, performing both NMR and MICP assays on a collection of 16 tight reservoir core specimens. Firstly, the observed difference between mercury injection and NMR PSD is consistent with the reported cases [29; 30; 34]. Furthermore, we integrated information from both methods to explain the reasons behind these discrepancies. Secondly, we proposed a rock quality assessment method to utilize this information from such differences. In the Winland r\({}_{35}\) method, the percolation threshold [40] is determined based on statistical principles. Although our method is also based on the principle of the Winland percolation threshold, our percolation threshold is determined based on the phenomenon of differences in pore size distribution between MICP and NMR, as demonstrated in Table 1. Our defined percolation threshold originates from the difference between MICP and NMR; specifically, it is determined by smaller throats that control the connectivity of larger pores. By applying Winland fitting results that have actual physical significance, we found it to be superior to fitting results based on statistical principles. Our innovation lies in utilizing the differential information between dynamic (NMR) and static (MICP) pore size distributions to find a percolation threshold that can be applied to the Winland method, providing a more effective tool for the analysis of rock pore structures.