The objective of this paper is to describe the experience of using a machine-learning model prepared by the ensemble method to prevent stuck-pipe events during construction of extendedreach wells. The tasks performed include collecting, analyzing, and cleaning historical data; selecting and preparing a machine-learning model; and testing it on real-time data by means of a desktop application. The idea is to display the solution at the rig floor, allowing the driller to take actions quickly for prevention of stuck-pipe events

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