DRILL STRING STICK/SLIP PREDICTION AND MITIGATION

A method includes generating one or more hybrid physics models each configured to predict a value for a drilling condition based on training data, training a machine learning model to predict a drilling condition severity based on the training data and the value of the drilling condition predicted b...

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Bibliographische Detailangaben
Hauptverfasser:	ROYCHOUDHURY, Indranil, GUPTA, Soumya, DE LA FUENTE, Alfredo, CELAYA GALVAN, Jose R, SHETH, Prasham, CHATAR, Crispin
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DETECTING MASSES OR OBJECTS EARTH DRILLING EARTH DRILLING, e.g. DEEP DRILLING FIXED CONSTRUCTIONS GEOPHYSICS GRAVITATIONAL MEASUREMENTS MEASURING MINING OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS PHYSICS TESTING
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Beschreibung
Zusammenfassung:	A method includes generating one or more hybrid physics models each configured to predict a value for a drilling condition based on training data, training a machine learning model to predict a drilling condition severity based on the training data and the value of the drilling condition predicted by the one or more hybrid physics models, receiving sensor data representing present drilling data, predicting the drilling condition, based at least in part on the sensor data, using the hybrid physics model, and predicting the drilling condition severity, based at least in part on the drilling condition that was predicted and the sensor data, using machine learning model that was trained.