# Data Knowledge Dual-Driven Rate of Penetration Prediction Method for Horizontal Wells
## 2 Horizontal Well Drilling Characteristics
### Data Statistics and Processing Results  
In this section, taking the drilling data of a shale gas cluster horizontal well platform in Sichuan as an example, the drilling data of horizontal wells are calculated and analyzed. Table 1 presents the statistical results of drilling data for both sliding and rotary drilling operations. From Table 1, it is evident that rotary drilling achieves a significantly larger footage compared to sliding drilling, accounting for approximately 80% to 90% of the total, while rotary drilling data only constitute 45% to 60% of the total dataset. This disparity can be attributed to the slower ROP during sliding directional drilling. In the same time interval, sliding drilling accumulates more data points per unit of footage. Consequently, a higher proportion of sliding drilling data leads to increased overall data variability, resulting in greater errors in the predictive models developed for ROP. If this part of the data is directly removed as abnormal data, it will lead to insufficient generalization of the model, so it is necessary to consider correcting this part of the data. Figure 4 illustrates the computed results of the friction coefficients between the drill string and the wellbore wall. Upon observing Figure 4, it becomes evident that the friction coefficients between the drill string and the wellbore wall dynamically fluctuate within the range of 0.07 to 0.32. These fluctuations arise from variations in downhole drilling conditions. As our analysis suggests, friction coefficients are not constants, and therefore, their dynamic variations must be considered when correcting the WOB. In Figure 5, the corrected and surface WOB values, accounting for the friction between the wellbore wall and the drill string, are depicted. As illustrated in Figure 5, in the case of horizontal wells, the maximum discrepancy between the surface WOB and the corrected WOB, factoring in drag between the wellbore wall and the drill string, can be as high as 200 kN. Particularly notable is the substantial disparity between surface WOB and corrected WOB, which is especially pronounced during the sliding drilling phase. Figure 6 showcases the corrected RPM compared to surface RPM values. As indicated in Figure 6, irrespective of whether it is rotary or sliding drilling, the corrected RPM significantly surpasses surface RPM due to the influence of the PDM. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Well** & \multicolumn{2}{c}{**Footage (m)**} & \multicolumn{2}{c}{**Data Amount (Number)**} & \multicolumn{2}{c}{**Percentage (\%)**} \\ \hline  & **Sliding** & **Rotating** & **Sliding** & **Rotating** & **Rotating Data** & **Rotating Footage** \\ \hline A1 & 69.56 & 631.99 & 50,666 & 75,734 & 59.92\% & 90.08\% \\ A2 & 74.44 & 684.04 & 67,026 & 77,130 & 53.50\% & 90.19\% \\ A3 & 93.32 & 697.4 & 62,354 & 73,438 & 54.08\% & 88.20\% \\ A4 & 112.9 & 690.6 & 83,674 & 69,463 & 45.36\% & 85.95\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Results of statistical analyses of drilling data. Figure 7 presents the results of the correlation analysis between drilling data and ROP. From Figure 7, it can be observed that there is a negative correlation between surface WOB and ROP with a correlation coefficient of \(-0.436\). However, after considering drag for WOB correction, the correlation coefficient between the corrected WOB and ROP increases to 0.371. Post-correction, the relationship between WOB and ROP changes from negative to positive, aligning more closely with the theoretical principles of rock break. Furthermore, the correlation coefficient between surface RPM and ROP is 0.532, indicating a positive correlation. After accounting for the influence of the positive displacement motor, the correlation coefficient between the corrected RPM and ROP increases significantly to 0.775.