## 4 Result
### Domain Knowledge Embedding  
The research findings in Section 4.1 indicate that while the current model has achieved a certain level of accuracy in predicting cement bond quality, its recognition rate for poor cementing conditions is only around 80%, which is precisely our primary concern. This level of accuracy remains insufficient for practical engineering applications, highlighting the need for further model optimization to enhance its ability to identify poor-cement bond quality, thereby improving engineering reliability and applicability. The flowability of cement slurry is crucial to the quality of well cementing [27; 28]. During the static phase, as the slurry undergoes hydration, changes in shear stress directly influence its thixotropy, suspension stability, and further affect drilling fluid displacement efficiency and final cementing quality [29; 30]. If the shear stress is too low, the cement slurry may fail to effectively scour the wellbore, leading to residual mud cake, which in turn degrades the cement bond and reduces cementing quality. Conversely, excessively high shear stress may result in uneven slurry flow, causing poor laminar flow control and ultimately reducing displacement  
Figure 8: Recall, precision, and F1-score generated (**a**) cement bond quality at the casing–cement sheath and (**b**) cement bond quality at the cement sheath–formation interface, using the Wide & Deep model. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Good** & **Moderate** & **Poor** \\ \hline Recall & 85.12\% & 85.46\% & 83.55\% \\ Precision & 88.83\% & 81.34\% & 81.19\% \\ F1-score & 0.8693 & 0.8335 & 0.8235 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Recall, Precision, and F1-score generated for predicting cement bond quality at the cement sheath–formation interface using the Wide & Deep model. efficiency. Therefore, an optimal shear stress level is essential, as it promotes the formation of a stable helical flow, enhances annular displacement efficiency, and effectively removes drilling fluid, thereby ensuring superior cement bond quality. According to research, cement slurry systems generally exhibit Bingham plastic or power-law rheological behavior, as detailed below:  
Bingham Plastic Model [31]:  
\[\tau=\tau_{y}+\mu_{p}\hat{\gamma} \tag{10}\]  
where the following are used:  
\(\tau\): shear stress (Pa);  
\(\tau_{y}\): yield stress (Pa);  
\(\mu_{p}\): plastic viscosity (Pa\(\cdot\)s);  
\(\hat{\gamma}\): shear rate (s\({}^{-1}\)). Power-law Model [32]:  
\[\tau=k\hat{\gamma}^{n} \tag{11}\]  
where the following are used:  
\(k\): consistency coefficient (Pa\(\cdot\)s\({}^{n}\));  
\(n\): flow behavior index (dimensionless). This study analyzes the field test results of cement slurry, utilizing a five-speed rotational viscometer to conduct rheological experiments under both ambient and high-temperature conditions. By analyzing the experimental data, the flow pattern of the cement slurry can be determined, enabling a more accurate characterization of its rheological properties. Figure 9 presents the rheological test results of cement slurry used in the second and third casing sections of a well. Based on the experimental data, curve fitting is performed to further quantify the rheological parameters of the cement slurry. In Figure 9, the blue dashed line represents the Bingham model fitting curve, while the orange dashed line represents the power-law model fitting curve. By comparing Figure 9a,b, the following conclusion can be drawn: At 25 \({}^{\circ}\)C, the power-law model achieves a fitting accuracy of \(R^{2}\) = 1.000, which is higher than that of the Bingham model (\(R^{2}\) = 0.997), indicating that the power-law model provides better fitting precision at this temperature. At 93 \({}^{\circ}\)C, the power-law model still maintains \(R^{2}\) = 1.000, outperforming the Bingham model in terms of fitting accuracy.