EARLY WARNING AND AUTOMATED DETECTION FOR LOST CIRCULATION IN WELLBORE DRILLING

A wellbore drilling system can generate a machine-learning model trained using historic drilling operation data for monitoring for a lost circulation event. Real-time data for a drilling operation can be received and the machine-learning model can be applied to the real-time data to identify a lost...

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Bibliographische Detailangaben
Hauptverfasser:	Hobberstad, Rune, Roy, Samiran, Verma, Shashwat, Vallabhaneni, Sridharan
Format:	Patent
Sprache:	eng
Schlagworte:	ADHESIVES CHEMISTRY DYES EARTH DRILLING EARTH DRILLING, e.g. DEEP DRILLING FIXED CONSTRUCTIONS MATERIALS FOR MISCELLANEOUS APPLICATIONS, NOT PROVIDED FORELSEWHERE METALLURGY MINING MISCELLANEOUS APPLICATIONS OF MATERIALS MISCELLANEOUS COMPOSITIONS NATURAL RESINS OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS PAINTS POLISHES
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Beschreibung
Zusammenfassung:	A wellbore drilling system can generate a machine-learning model trained using historic drilling operation data for monitoring for a lost circulation event. Real-time data for a drilling operation can be received and the machine-learning model can be applied to the real-time data to identify a lost circulation event that is occurring. An alarm can then be outputted to indicate a lost circulation event is occurring for the drilling operation.