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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| creator | VALLABHANENI, Sridharan ROY, Samiran VERMA, Shashwat HOBBERSTAD, Rune |
| description | 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.
Système de forage de trou de forage pouvant générer un modèle d'apprentissage automatique formé à l'aide de données historiques d'opération de forage aux fins de la surveillance d'un événement de perte de circulation. Des données en temps réel pour une opération de forage peuvent être reçues et le modèle d'apprentissage automatique peut être appliqué aux données en temps réel pour identifier un événement de perte de circulation qui survient. Une alarme peut ensuite être émise pour indiquer un événement de perte de circulation qui survient lors de l'opération de forage. |
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Système de forage de trou de forage pouvant générer un modèle d'apprentissage automatique formé à l'aide de données historiques d'opération de forage aux fins de la surveillance d'un événement de perte de circulation. Des données en temps réel pour une opération de forage peuvent être reçues et le modèle d'apprentissage automatique peut être appliqué aux données en temps réel pour identifier un événement de perte de circulation qui survient. Une alarme peut ensuite être émise pour indiquer un événement de perte de circulation qui survient lors de l'opération de forage.</description><language>eng ; fre</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; EARTH DRILLING ; EARTH DRILLING, e.g. DEEP DRILLING ; FIXED CONSTRUCTIONS ; MINING ; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS ; PHYSICS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210916&DB=EPODOC&CC=WO&NR=2021183165A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210916&DB=EPODOC&CC=WO&NR=2021183165A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>VALLABHANENI, Sridharan</creatorcontrib><creatorcontrib>ROY, Samiran</creatorcontrib><creatorcontrib>VERMA, Shashwat</creatorcontrib><creatorcontrib>HOBBERSTAD, Rune</creatorcontrib><title>EARLY WARNING AND AUTOMATED DETECTION FOR LOST CIRCULATION IN WELLBORE DRILLING</title><description>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.
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Système de forage de trou de forage pouvant générer un modèle d'apprentissage automatique formé à l'aide de données historiques d'opération de forage aux fins de la surveillance d'un événement de perte de circulation. Des données en temps réel pour une opération de forage peuvent être reçues et le modèle d'apprentissage automatique peut être appliqué aux données en temps réel pour identifier un événement de perte de circulation qui survient. Une alarme peut ensuite être émise pour indiquer un événement de perte de circulation qui survient lors de l'opération de forage.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING EARTH DRILLING EARTH DRILLING, e.g. DEEP DRILLING FIXED CONSTRUCTIONS MINING OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS PHYSICS |
| title | EARLY WARNING AND AUTOMATED DETECTION FOR LOST CIRCULATION IN WELLBORE DRILLING |
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