## 4 Results and Discussion  
Pearson correlation, which is a method that measures the degree of correlation between two variables \(X\) and \(Y\), was adopted to verify the example. The Pearson correlation coefficient between \(X\) and \(Y\) is defined as the quotient of the covariance and standard deviation of the two variables, as shown by Equation (7). The Pearson correlation coefficient ranges between \(-1\) and \(1\), where \(1\) suggests complete positive correlation of variables, \(0\) indicates irrelevance, and \(-1\) means complete negative correlation [34].  
\[\rho_{X,Y}=\frac{\text{cov}(X,Y)}{\sigma_{X}\sigma_{Y}}=\frac{E[(X-\mu_{X})(Y- \mu_{Y})]}{\sigma_{X}\sigma_{Y}} \tag{7}\]  
Figure 6: Prediction results of the four algorithms.  
Figure 7: MRE changes of the four algorithms.  
Equation (7) defines the population correlation coefficient and estimates the sample covariance and standard deviation. The calculation method is expressed by Equation (8).  
\[r=\frac{\sum\limits_{i=1}^{n}{\left({{X_{i}}-\overline{X}}\right)}{{{\left({{Y_{i }}-\overline{Y}}\right)}}}} \tag{8}\]  
The completion depth of a well in the Shunbei block of the Northwest Oilfield is 8725 m, the maximum deviation angle is 86.01\({}^{\circ}\), the maximum angle change rate is 0.6127\({}^{\circ}\)/m, the maximum diameter expansion rate is 12%, the mud density is 1.68 g/cm\({}^{3}\), and the plastic viscosity is 36 mPa\(\cdot\)s. For the 139.7 mm liner cementing of the well, the centralizer cannot be placed in case the straight casing is upset. The casing is close to the lower shaft wall, and the casing is basically zero in the medium range. The displacement flushing fluid (1.05 g/cm\({}^{3}\)) is designed to be 7 m\({}^{3}\), the weighted isolation fluid (1.75 g/cm\({}^{3}\)) is 4 m\({}^{3}\), the cement slurry (1.88 g/cm\({}^{3}\)) is 11 m\({}^{3}\), and the designed injection displacement is 0.6-0.8 m\({}^{3}\)/min. The sound amplitude logging of the 139.7 mm liner well cementing is shown in Figure 8, from which it is evident that the sound amplitude of the CBL logging in the whole sealing section is between 10% and 30%, and the cementing quality for 7850-8000 m is excellent.  
Using GA-SVR to predict the cementing quality of the cementing data, the comparison between the predicted values and the actual values is shown in Figure 9, from which it can be seen that Pearson's correlation coefficient is 0.9781; in addition, the predicted values of GA-SVR have a good correlation with the actual cementing quality values.  
Figure 8: Acoustic amplitude log of cementing quality of a well in the Shunbei block.  
Figure 9: Correlation diagram between the actual value and the predicted value of cementing quality.  
In order to further analyze the deviation between the predicted values of the GA-SVR model and the actual cementing quality values, the relative errors of the prediction results were analyzed, and the results are shown in Figure 10, from which it can be seen that the sixth data group has the largest relative error of 9.16%. The first data group has the smallest relative error of 1.27%. The prediction errors of most subgroups are concentrated around 5.5%, with \(MRE\) of 5.27% and \(RMSE\) of 1.166. The results show that the predicted values of GA-SVR match the actual cementing quality values to the greatest extent and have the smallest errors, which indicates that this method is suitable for predicting the cementing quality of the Shunbei block. GA-SVR is a complex model, which will always have some uncertainty in predicting future situations. For example, many factors, such as the environment, can affect the prediction results. In addition, there is randomness and noise in the data, which will have an impact on the prediction results. This method is more suitable for situations where the environment is similar, and it may not be able to adapt quickly to changes in the data when the conditions differ.