## 4 Conclusions  
In the field of rock pore structure characterization, MICP and NMR are two widely adopted key techniques. This study delves into a comprehensive comparison and analysis of the applicability of these two methods in depicting rock pore structures. By leveraging the discrepancies between NMR and MICP measurements, we have established the Winland F\({}_{\text{rc}}\) method. Sandstone samples from Tuha and shale samples from Hechuan were selected for the experimental analysis. After a series of experiments and data evaluations, the following primary conclusions were drawn:  
Figure 16: The relationship between F\({}_{\text{rc}}\), K\({}_{\text{a}}\), and \(\Phi\): (**a**) sandstone and (**b**) shale.  
In MICP experiments, excessive mercury injection pressures might damage the integrity of the rock's pore structure, particularly affecting smaller pore sizes and thereby constraining its applicability in micro-pore analysis. Conversely, NMR offers a non-destructive approach to pore structure detection, presenting a distinct advantage in the identification and characterization of micro-pores;
2. The heterogeneity of shale and tight sandstone has a noticeable impact on the results obtained from the MICP method. In heterogeneous rocks where large pores are connected to small throats, MICP might overestimate the proportion of small throats and underestimate that of large throats. Due to NMR's ability to detect all pores containing hydrogen-bearing fluids, it more accurately reflects the rock's pore distribution;
3. In shale, specific signals in NMR are provided by kerogen, asphaltene, and bound water. These signals predominantly appear in the region of smaller pore sizes, potentially causing NMR to overestimate the proportion of these small pores;
4. Based on the Winland r\({}_{35}\) method, by integrating information from both NMR and MICP measurements, we established the Winland F\({}_{\text{rc}}\) method. This approach surpasses the fitting accuracy of the traditional Winland method. It represents a potential high-precision, comprehensive tool for rock quality analysis, enhancing the precision of analysis and offering a novel perspective for an in-depth understanding of rock properties.  
Conceptualization, Z.G., S.W. and P.G.; methodology, Z.G., S.W. and W.Z.; software, Z.G. and S.W.; validation, Z.G. and S.W.; formal analysis, Z.G. and S.W.; investigation, Z.G. and W.Z.; resources, S.W.; data curation, Z.G.; writing--original draft preparation, Z.G.; writing--review and editing, S.W.; visualization, S.W. and P.G.; supervision, S.W. and P.G.; project administration, P.G.; funding acquisition, P.G. All authors have read and agreed to the published version of the manuscript.  
This research work was partly supported by the Sichuan Natural Science Foundation, China [grant number 2022 NSFSC1029].  
Not applicable.  
The data presented in this study are available in the article.  
The authors declare no conflict of interest.  
The surface relaxation time, ms  
The diffusion relaxation time, ms  
The bulk relaxation time, ms  
The transverse relaxation rate, um/ms  
The specific surface area of a single pore, um\({}^{2}\)/um\({}^{3}\)  
The pore shape factor, dimensionless  
The pore radius, um  
The conversion coefficient, dimensionless  
Controlled throat radius, um  
The volume controlled by pore throat r\({}_{\text{c}}\), %  
The radius corresponding to the point at which mercury intrusion volume reaches 35% of the total pore volume, um  
The absolute permeability, mD  
The porosity of the core, %