## 3 Results
### Analysis of Co-Occurrence Networks and Functional Prediction in Different Displacement Blocks  
The modularization index (MD) is used to measure the tightness of a community. The higher the MD value, the better the community is divided and the closer the community is. In this study, the modularization index was 0.606 and 0.647 in the networks of ASP-flooded (ASP) blocks and water flooding after ASP-flooded (WF) blocks, respectively, where MD > 0.4 suggests that the network had a modular structure, indicating that the network structure was non-random [20]. In addition, the average clustering coefficient of WF was 0.363, while the average clustering coefficient of ASP was only 0.258, which is 0.105 lower than WF. The difference in the network density (Table 1) between the two blocks was 0.19. These results indicate that the ASP flooding technique reduced the tightness between the reservoir microorganisms. The complexity of the network structure can be identified by the co-occurrence of nodes and the average degree in the network [21]. The network of the ASP block consisted of 220 nodes connected by 944 edges, and the network of the WF block consisted of 239 nodes with 1252 edges. The average degree of WF was 11.382, while that  
Figure 3: Beta diversity of bacterial communities in ASP and WF blocks. Figure 2: **(a)** The box plot shows the distribution of the Alpha diversity Chao1l index within two blocks and the inter-group statistics and (**b**) the box plot shows the distribution of the Alpha diversity Shannon index within two blocks and the inter-group statistics; different letters indicate significant differences between the blocks (\(p\) < 0.05, ANOVA, Tukey-HSD test). of ASP was only 7.9. This study shows that the network complexity of WF was higher than that of ASP. The higher the network complexity (Figure 4), the more complex and diverse the microbial community structure [22]. Therefore, the microbial community structure in the WF block was more complex and diverse than the ASP block, which is consistent with the results of the alpha analysis in the previous text. Furthermore, potential functional predictions (Figure 5) about the microbial communities of both blocks were made. In several sets of samples from the WF and ASP blocks fermentation, hydrocarbon degradation, atomic degradation, nitrate respiration, nitrogen respiration, nitrate reduction, sulphide respiration, chemotherapy, and acute chemotherapy were the main functions of the microorganisms, and there were significant differences in the microbial functions between the two blocks in different samples. For functions related to nitrogen metabolism, including nitrate respiration, nitrogen respiration, and nitrate reduction, the degree of functional redundancy was higher in the WF block samples. The term 'functional redundancy' refers to the presence of several different taxa or genomes capable of performing the same essential biochemical functions [23; 24]. The functional redundancy of sulphide respiration, chemotherapy, and antibacterial chemotherapy in the ASP samples was higher than that in the WF samples (Figure S1). Both of these block samples had potential functions such as fertilization and hydrocarbon degradation, but exhibited higher redundancy in the WF samples. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Topological Properties** & **ASP** & **WF** \\ \hline Total nodes & 220 & 239 \\ Total edges & 944 & 1252 \\ Average degree & 7.9 & 11.382 \\ Average clustering coefficient & 0.258 & 0.363 \\ Average path length & 4.333 & 4.709 \\ Network density & 0.033 & 0.052 \\ Modularity index & 0.606 & 0.647 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The co-occurrence network topology properties of ASP and WF. Figure 4: The co-occurrence patterns of ASV revealed by network analysis. Nodes were arranged according to Fruchterman–Reingold and coloured according to different types of modular classes.