## 4 Discussion  
Tripping operations refer to lowering or withdrawing a drill string into a wellbore hole. The literature indicates that approximately 18% of drilling time is spent performing tripping operations, and is considered non-productive according to [PERSON] et al. (2020) [29]. Tripping is performed, for example, to replace worn-out drill bits. Tripping string at a lower speed is safer concerning wellbore instability; however, it will increase the non-productive time and cost. Tripping at a higher speed will minimize the non-productive time, but pulling the strings above their optimum values will create undesired surging and swabing pressures that could lead to wellbore fracture and collapse/kick, respectively. For safe and efficient operation, it is imperative to predict the appropriate swab surge pressure precisely associated with the optimized tripping speeds. [PERSON] et al. (2022) [39] presented an extensive literature review on surge/swab pressure models, which were developed based on physical laws (analytical models) and experimental works (empirical models). The developed analytical models were based on several \begin{table}
\begin{tabular}{c c c c} \hline \hline
**ML Model** & \multirow{2}{*}{**Dataset**} & \multicolumn{2}{c}{**Model Performance Accuracy**} \\
**Algorithms** & & **MSE** & **R\({}^{2}\)** \\ \hline \multirow{2}{*}{ANN} & Training & \(2.94\times 10^{-5}\) & 0.7921 \\  & Testing & \(3.43\times 10^{-5}\) & 0.7836 \\ \hline \multirow{2}{*}{RF} & Training & \(1.95\times 10^{-6}\) & 0.9879 \\  & Testing & \(1.45\times 10^{-5}\) & 0.8921 \\ \hline \multirow{2}{*}{LightGBM} & Training & \(1.05\times 10^{-5}\) & 0.9256 \\  & Testing & \(1.88\times 10^{-5}\) & 0.8884 \\ \hline \multirow{2}{*}{XGBoost} & Training & \(7.01\times 10^{-6}\) & 0.9504 \\  & Testing & \(1.52\times 10^{-5}\) & 0.9098 \\ \hline \multirow{2}{*}{LSTM} & Training & \(3.60\times 10^{-5}\) & 0.7449 \\  & Testing & \(4.56\times 10^{-5}\) & 0.7299 \\ \hline \multirow{2}{*}{Multivariable} & Training & \(3.87\times 10^{-5}\) & 0.7264 \\  & Testing & \(4.86\times 10^{-5}\) & 0.7120 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Performance accuracy analysis of the ML models with the tripping-out dataset. Figure 27: (a) Scatter plot of 70% training tripping-out data vs. multivariable model prediction. (b) Scatter plot of 30% test tripping-out data vs. multivariable model prediction. presumptions, and simulated in laboratory-controlled experimental setup conditions. However, it is difficult to precisely quantify the degree of drill string eccentricity, wellbore roughness, sizes, and fluid properties in actual drilling well operation conditions. Hence, model predictions with uncertain inputs will not be correct. Moreover, the model predictions also varied. This indicates the uncertainty of the parametric-based modeling for swab and surge models. In this study, first, we conducted a physics-based swab and surge simulation to evaluate the model prediction in different well trajectories filled with drilling fluids exhibiting different rheological and physical properties. The models tested were Bingham plastic, power law, and Robertson-Stiff. Four oil-based drilling fluids with various viscosities were considered for the simulations, under both vertical and deviated well profiles. Observations based on the considered drilling fluids and simulation setup revealed that:  
* The model's predictions were inconsistent compared with each other. * As the flow rates increased to approximately 200-300 lpm, surging speeds in the deviated well filled with 90:10 OBM showed an increasing trend, whereas in 80:20 OBM, the surging speed showed a decreasing trend. On the other hand, in both fluid systems, the surging speeds decreased when the flow rate increased above 300 lpm. Even though the trends in surge speeds for the three models' predictions seemed similar, the values were quite different. * Regarding rheology fluid descriptions, the RS model showed a lower error deviation.