Applying artificial neural networks with bourgoyne and young model to predict rate of penetration in al-garraf oil field

HIGHLIGHTS

• What: This study proposes an approach that combines the benefits of Feedforward Neural Networks (FNN) from the ANN model and BYM equations to enhance ROP prediction. This study proposes integrating FNN with BYM equations to predict ROP in Al-Garraf oil wells in southern Iraq. The experiment showed that using fewer data points as a dataset made the results more accurate, but using more data points as much as possible reflected the actual drilling circumstances in the well.
• Who: Eng.Ali and samuel adegbemileke from the Department of Petroleum Engineering, College of Engineering, University of . . .
  

   

  

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