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What is Predicting ECD in Drilling with ML about?

The paper presents a statistical machine learning model using support vector machines (SVM) and principal components analysis (PCA) to predict equivalent circulation density (ECD) while drilling. By analyzing actual field data, the model aims to improve the accuracy of ECD predictions by incorporating factors like bottom hole temperature and pipe rotation, which traditional mathematical equations often overlook. The results indicate that the PCA-based SVM model can effectively predict ECD, thereby enhancing

Author

mostafavikhatam.mohammadamin

Language

EN