A highly accurate and robust prediction framework for drilling rate of penetration based on machine learning ensemble algorithm

An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines

Bahram Choubin, Ehsan Moradi, Mohammad Golshan et al. · The Science of The Total Environment · 2018 · 778 citations

Computing, Hydrology, Flood Hydrology +16

A data-driven Bayesian network learning method for process fault diagnosis

Md. Tanjin Amin, Faisal Khan, Salim Ahmed et al. · Process Safety and Environmental Protection · 2021 · 254 citations

Computing, Computer Science, Systems Engineering +14

The "Perfect - Cleaning" Theory of Rotary Drilling

W.C. Maurer · Journal of Petroleum Technology · 1962 · 246 citations

Engineering, Geological Engineering, Drilling +13

Forecasting fault events for predictive maintenance using data-driven techniques and ARMA modeling

Márcia L. Baptista, Shankar Sankararaman, Ivo Paixão de Medeiros et al. · Computers & Industrial Engineering · 2017 · 243 citations

Engineering, Data Science, Systems Engineering +14

Penetration-Rate Performance of Roller-Cone Bits

T. M. Warren · SPE Drilling Engineering · 1987 · 219 citations

Engineering, Petroleum Engineering, Drilling +14