Smarter Well Engineering Concepts Aid in Reducing Planning Time and Increasing ROP

Modern well engineers struggle with digital confusion; they have either too much data or not enough, and the quality is often questionable. Additionally, well engineers are usually operations focused and might not fully appreciate optimization through data-driven insight. This paper illustrates how to optimize the rate of penetration (ROP) in any given field using an automated and timesaving process for designing wells using machine-learning (ML) techniques.

By prescribing optimized ROPs through automated ML of offset well attributes, free from subjective human bias, engineers can push technical limits. Automated analysis, regression, and visualization of high-volume data can reduce planning time significantly and help establish optimized operational parameters to reduce drilling time and costs.

The next step is to build a real-time downhole advisory system to help achieve the predicted ROPs by predicting and prescribing drilling parameters ahead of the bit.