Machine Learning Guide for Oil and Gas Using Python

Rate of penetration (ROP) optimization example

Another regression example that can be illustrated is drilling rate of penetration (ROP) prediction and optimization. There are various important features that are captured when drilling a well. These features include but are not limited to hook load, rpm, torque, weight on bit (WOB), differential pressure, gamma, and ROP. An important output feature that must be predicted or optimized is referred to as ROP. Maximizing ROP is the absolute goal in drilling. Therefore, the key to ROP maximization is building a supervised regression machine learning model where ROP can be used as the output of the model. Once a satisfactory model has been trained, ROP can be easily predicted for new wells. In addition, ...