Determination of mechanical properties of a geological formation using deep learning applied to data acquired while drilling

Methods for determination of mechanical properties of geological formations using deep learning include receiving, by a computer system, data acquired during drilling a geological formation. The computer system generates features of the data acquired during drilling. The features are indicative of m...

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Bibliographische Detailangaben
Hauptverfasser:	Kanfar, Rayan, Bakulin, Andrey, AlbinHassan, Nasher Muqbel, Nivlet, Philippe, Smith, Robert
Format:	Patent
Sprache:	eng
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:	Methods for determination of mechanical properties of geological formations using deep learning include receiving, by a computer system, data acquired during drilling a geological formation. The computer system generates features of the data acquired during drilling. The features are indicative of mechanical properties of the geological formation. The computer system segments the features of the data acquired during drilling into sequences readable by a trained temporal convolutional network (TCN). The computer system determines the mechanical properties of the geological formation using the TCN based on the sequences obtained from the features of the data. A display device of the computer system generates a graphical representation of the mechanical properties of the geological formation.