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Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

2019

Missouri University of Science and Technology

Petroleum Engineering

Artificial neural networks

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Full-Text Articles in Engineering

Application Of Artificial Neural Networks In The Drilling Processes: Can Equivalent Circulation Density Be Estimated Prior To Drilling?, Husam Hasan Alkinani, Abo Taleb Al-Hameedi, Shari Dunn-Norman, David Lian Dec 2019

Application Of Artificial Neural Networks In The Drilling Processes: Can Equivalent Circulation Density Be Estimated Prior To Drilling?, Husam Hasan Alkinani, Abo Taleb Al-Hameedi, Shari Dunn-Norman, David Lian

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

As the drilling environment became more challenging nowadays, managing equivalent circulating density (ECD) is a key factor to minimize non-productive time (NPT) due to many drilling obstacles such as stuck pipe, formation fracturing, and lost circulation. The goal of this work was to predict ECD prior to drilling by using artificial neural network (ANN). Once ECD is recognized, the crucial drilling variables impact ECD can be modified to control ECD within the acceptable ranges. Data from over 2000 wells collected worldwide were used in this study to create an ANN to predict ECD prior to drilling. Into training, validation, and …