CONTROLLING WELLBORE EQUIPMENT USING A HYBRID DEEP GENERATIVE PHYSICS NEURAL NETWORK
A system includes equipment for at least one of formation of, stimulation of, or production from a wellbore, a processor, and a non-transitory memory device. The processor is communicatively coupled to the equipment. The non-transitory memory device contains instructions executable by the processor...
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| creator | Madasu, Srinath |
| description | A system includes equipment for at least one of formation of, stimulation of, or production from a wellbore, a processor, and a non-transitory memory device. The processor is communicatively coupled to the equipment. The non-transitory memory device contains instructions executable by the processor to cause the processor to perform operations comprising training a hybrid deep generative physics neural network (HDGPNN), iteratively computing a plurality of projected values for wellbore variables using the HDGPNN, comparing the projected values to measured values, adjusting the projected values using the HDGPNN until the projected values match the measured values within a convergence criteria to produce an output value for at least one controllable parameter, and controlling the equipment by applying the output value for the at least one controllable parameter. |
| format | Patent |
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The non-transitory memory device contains instructions executable by the processor to cause the processor to perform operations comprising training a hybrid deep generative physics neural network (HDGPNN), iteratively computing a plurality of projected values for wellbore variables using the HDGPNN, comparing the projected values to measured values, adjusting the projected values using the HDGPNN until the projected values match the measured values within a convergence criteria to produce an output value for at least one controllable parameter, and controlling the equipment by applying the output value for the at least one controllable parameter.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONTROL OR REGULATING SYSTEMS IN GENERAL ; CONTROLLING ; COUNTING ; EARTH DRILLING ; EARTH DRILLING, e.g. DEEP DRILLING ; ELECTRIC DIGITAL DATA PROCESSING ; FIXED CONSTRUCTIONS ; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS ; MINING ; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS ; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS ; PHYSICS ; REGULATING</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=20211216&DB=EPODOC&CC=US&NR=2021388710A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211216&DB=EPODOC&CC=US&NR=2021388710A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Madasu, Srinath</creatorcontrib><title>CONTROLLING WELLBORE EQUIPMENT USING A HYBRID DEEP GENERATIVE PHYSICS NEURAL NETWORK</title><description>A system includes equipment for at least one of formation of, stimulation of, or production from a wellbore, a processor, and a non-transitory memory device. 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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING COUNTING EARTH DRILLING EARTH DRILLING, e.g. DEEP DRILLING ELECTRIC DIGITAL DATA PROCESSING FIXED CONSTRUCTIONS FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MINING MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR ASLURRY OF MINERALS FROM WELLS PHYSICS REGULATING |
| title | CONTROLLING WELLBORE EQUIPMENT USING A HYBRID DEEP GENERATIVE PHYSICS NEURAL NETWORK |
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