Automated Real-Time Rate of Penetration Trend and Dynamic Analysis in Drilling Operations

In this study, a moving window trend analysis, is implemented to do stream processing on the realtime data. The benefits of the work will help drillers rapidly detect changes in the data, quickly learn realtime data dynamics, and more easily make decisions for better control and optimization. The qualitative trend analysis (QTA) used in this study is a data-driven method that processes data to extract and analyze the trends from the measured signals. For the rate of penetration (ROP) trend extraction, the key outcome is the classification into stationary, falling, and rising trends. The methodology has been tested in a high-fidelity drilling simulation environment. In realtime simulations, the presented algorithm observes how the ROP is affected by drilling parameters, making it possible to identify, analyze and improve ROP trends. The results reflect the potential of drilling automation based on data analytics toward safer and more efficient drilling systems control. The method can also be incorporated into an advanced drilling control hierarchy, supporting automation and intelligent decision-making for drilling engineering.