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What is Machine Learning for Lost Circulation Prediction about?

This research article focuses on characterizing lost circulation intensity in drilling operations using machine learning models applied to well log data from a gas field in northern Iran. The study identifies the best-performing machine learning methods, including Random Forest and Extra Trees, to predict lost circulation intensity across six classes, thereby enhancing drilling efficiency and safety. The findings emphasize the potential of data-driven approaches to mitigate operational risks and improve dec

Author

Shiva Shrivastava

Language

EN