## 5 Conclusions  
The novel \(\text{CTR}_{\text{m}}\) model takes into account various real-time drilling parameters to evaluate and optimize drilling performance. By utilizing these parameters, the model can provide accurate assessments of hole cleaning efficiency, identify potential issues in real-time, and help to prevent complications such as stuck pipe incidents. The real-time drilling parameters that the \(\text{CTR}_{\text{m}}\) model accounts for may include the drilling fluid flow rate, pump pressure, and drill string rotation speed, among others. By incorporating these parameters into its calculations, the \(\text{CTR}_{\text{m}}\) model provides a comprehensive and reliable assessment of drilling performance, which can help to optimize drilling operations and enhance overall efficiency. The following points can be summarized: \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & & & & \\ \hline
**Items** & **Output** & **Minimum** & **Maximum** & **Average** & **Remark** \\ \hline
1 & \(\text{CTR}_{\text{m}}\) & 0.48 & 0.63 & 0.57 & Proper removal of cuttings from the wellbore \\
2 & ROP & 5.0 & 25.7 & 14.3 & Normal drilling efficiency and performance due to proper \\  & & & & & wellbore cleaning \\ \hline \hline \multicolumn{5}{c}{**Performance of Well-D Employing \(\text{CTR}_{\text{m}}\)**} \\ \hline
**Items** & **Output** & **Minimum** & **Maximum** & **Average** & **Remark** \\ \hline
1 & \(\text{CTR}_{\text{m}}\) & 0.58 & 0.95 & 0.45 & Poor removal of cuttings from the wellbore \\
2 & ROP & 0.552 & 267 & 93.4 & Decreased drilling efficiency and performance attributable \\  & & & & & to inefficient wellbore cleaning and stuck pipes \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Impact of employing \(\text{CTR}_{\text{m}}\) on well performance. 1. The \(\text{CTR}_{\text{m}}\), a crucial hole cleaning indicator, is monitored in real-time using drilling factors such as cuttings features, drilling mechanical parameters, well trajectory profiles (the well path, which contains the inclinations and the azimuths), and fluid rheological properties, with consideration of the LSFP as it is a signal for hole cleaning effectiveness in directional drilling, along with calculated cuttings slip and annular velocities. This monitoring helps engineers identify well cleaning and ROP issues, leading to improved efficiency through fluid optimization, drilling adjustments, and advanced technology use. The novel \(\text{CTR}_{\text{m}}\) model, instead of commercial software, facilitates real-time optimization and interventions, accounting for wellbore shape changes and spontaneous field data. Connecting \(\text{CTR}_{\text{m}}\) to the driller's control panel enables immediate evaluation and remedial actions for hole cleaning. 2. The novel \(\text{CTR}_{\text{m}}\) was tested and validated in the field. The obtained results proved that the efficiency of the drilling wells was enhanced. Drilling practices might be greatly improved by utilizing the novel \(\text{CTR}_{\text{m}}\) and its automation, which would reduce any possible issues brought on by insufficient hole cleaning. 3. Real-time evaluation demonstrated that the model could identify hole cleaning efficiency during normal drilling operations in Well-C and detected stuck pipe issues in Well-D. Furthermore, in comparison to Well-B, the novel \(\text{CTR}_{\text{m}}\) model improved the rate of penetration by 52% in Well-A. Overall, the results indicate that the novel \(\text{CTR}_{\text{m}}\) model is an effective solution for enhancing drilling performance, identifying complications, and improving hole cleaning efficiency.