AUTOMATIC SENSOR DATA VALIDATION ON A DRILLING RIG SITE

A method automatically validates sensor data. The method includes extracting a sample from a sample time series using a sample window, generating an input vector from the sample, and generating a context vector from the input vector using an encoder model comprising a first recurrent neural network....

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Bibliographische Detailangaben
Hauptverfasser:	GUPTA, Soumya, CELAYA GALVAN, Jose R, 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 ELECTRIC DIGITAL DATA PROCESSING 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 automatically validates sensor data. The method includes extracting a sample from a sample time series using a sample window, generating an input vector from the sample, and generating a context vector from the input vector using an encoder model comprising a first recurrent neural network. The method further includes generating an output vector from the context vector by a decoder model comprising a second recurrent neural network and generating a reconstruction error from a comparison of the output vector to the input vector. The reconstruction error indicates an error with the sample. The method further includes presenting the reconstruction error.