Fracturing sand plugging risk early warning method based on deep learning and double logarithmic curves

The invention discloses a fracturing sand plugging risk early warning method based on deep learning and a double logarithmic curve. The method comprises the following steps that S1, multiple construction parameter time sequences in the fracturing construction process are collected; s2, on the basis...

Full description

Saved in:
Bibliographic Details
Main Authors WANG LIN, ZHU NAN, WEI MIAN, LIU YIJIA, HUANG QI, WANG FANGXIANG, GENG TENG, YANG XIN, DONG BINGXIANG, LI NAN, LIN CHUNLAI, DU HUIMIN, SHAO JUNLONG
Format Patent
LanguageChinese
English
Published 11.06.2024
Subjects
Online AccessGet full text

Cover

Loading…
Abstract The invention discloses a fracturing sand plugging risk early warning method based on deep learning and a double logarithmic curve. The method comprises the following steps that S1, multiple construction parameter time sequences in the fracturing construction process are collected; s2, on the basis of the time sequence in the step S1, predicting a future time sequence of each construction parameter by using a time sequence time domain analysis algorithm; s3, constructing and training an L-Aresnet network so as to correct the predicted value of each construction parameter in the future time sequence; s4, according to the time sequence change curve of the future sample value of each construction parameter obtained in the step S3, calculating a log value lgK of the slope K of the future change curve of each construction parameter as an early warning judgment value, and comparing the log value lgK with an early warning critical value; according to the method, multiple construction parameters, easy to monitor, of
AbstractList The invention discloses a fracturing sand plugging risk early warning method based on deep learning and a double logarithmic curve. The method comprises the following steps that S1, multiple construction parameter time sequences in the fracturing construction process are collected; s2, on the basis of the time sequence in the step S1, predicting a future time sequence of each construction parameter by using a time sequence time domain analysis algorithm; s3, constructing and training an L-Aresnet network so as to correct the predicted value of each construction parameter in the future time sequence; s4, according to the time sequence change curve of the future sample value of each construction parameter obtained in the step S3, calculating a log value lgK of the slope K of the future change curve of each construction parameter as an early warning judgment value, and comparing the log value lgK with an early warning critical value; according to the method, multiple construction parameters, easy to monitor, of
Author DU HUIMIN
LIN CHUNLAI
WEI MIAN
ZHU NAN
YANG XIN
LIU YIJIA
WANG FANGXIANG
HUANG QI
GENG TENG
WANG LIN
DONG BINGXIANG
LI NAN
SHAO JUNLONG
Author_xml – fullname: WANG LIN
– fullname: ZHU NAN
– fullname: WEI MIAN
– fullname: LIU YIJIA
– fullname: HUANG QI
– fullname: WANG FANGXIANG
– fullname: GENG TENG
– fullname: YANG XIN
– fullname: DONG BINGXIANG
– fullname: LI NAN
– fullname: LIN CHUNLAI
– fullname: DU HUIMIN
– fullname: SHAO JUNLONG
BookMark eNqNizsOwjAQRF1Awe8OywEoDIpCiyIiKir6aGMvjoVjW2sbxO1RpByAajRv3qzFwgdPK2FaRpULW28godcQXTFmamzTCwjZfeGD7Cc0Uh6Chh4TaQgeNFEER_M6vXUovSNwwSDbPIxWgSr8prQVyye6RLs5N2LfXh_N7UAxdJQiKvKUu-Yu5VnWsqqOl9M_zg8iJUHS
ContentType Patent
DBID EVB
DatabaseName esp@cenet
DatabaseTitleList
Database_xml – sequence: 1
  dbid: EVB
  name: esp@cenet
  url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Chemistry
Sciences
Physics
DocumentTitleAlternate 一种基于深度学习和双对数曲线的压裂砂堵风险预警方法
ExternalDocumentID CN118171552A
GroupedDBID EVB
ID FETCH-epo_espacenet_CN118171552A3
IEDL.DBID EVB
IngestDate Fri Sep 06 06:15:51 EDT 2024
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language Chinese
English
LinkModel DirectLink
MergedId FETCHMERGED-epo_espacenet_CN118171552A3
Notes Application Number: CN202211570716
OpenAccessLink https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240611&DB=EPODOC&CC=CN&NR=118171552A
ParticipantIDs epo_espacenet_CN118171552A
PublicationCentury 2000
PublicationDate 20240611
PublicationDateYYYYMMDD 2024-06-11
PublicationDate_xml – month: 06
  year: 2024
  text: 20240611
  day: 11
PublicationDecade 2020
PublicationYear 2024
RelatedCompanies CHINA NATIONAL PETROLEUM CORPORATION
CNPC BOHAI DRILLING ENGINEERING COMPANY LIMITED
RelatedCompanies_xml – name: CHINA NATIONAL PETROLEUM CORPORATION
– name: CNPC BOHAI DRILLING ENGINEERING COMPANY LIMITED
Score 3.680563
Snippet The invention discloses a fracturing sand plugging risk early warning method based on deep learning and a double logarithmic curve. The method comprises the...
SourceID epo
SourceType Open Access Repository
SubjectTerms CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
Title Fracturing sand plugging risk early warning method based on deep learning and double logarithmic curves
URI https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240611&DB=EPODOC&locale=&CC=CN&NR=118171552A
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3dS8MwED_m_HzTqej8IIL0rWg_1o-HIi5dGcK6IVP2Ntok3SbalrVz4F9vknXOF31NyJEc3F1y-f3uAG7pfeJEemypJG4lqqlTV41cg6gGoaZGKHF1SxCFe6HVfTGfRq1RDd7WXBhZJ3QpiyNyiyLc3kvpr_NNEsuX2MriLp7xoewhGHq-Ur2OZXjSFL_tdQZ9v48VjD0cKuGzJ_iVtig39rgF2_wabQv4V-e1LVgp-e-QEhzCzoBLS8sjqH1NG7CP153XGrDXqz68G7ArEZqk4IOVFRbHMAkEtUnyC1ERpRTl7wuROJ4gARRHTNQsRstVygOtWkQjEa0oylJEGctR1StigsRqmvFTM8SdIH83l9OPGUFkMf9kxQncBJ0h7qp87-MfRY1xuDmmcQr1NEvZGSBi6aZxH5s2YS0z0ZkbMz22SeQ6WpI4zDmH5t9ymv9NXsCBULqATmnaJdTL-YJd8SBdxtdSu9_LYJkE
link.rule.ids 230,309,783,888,25578,76884
linkProvider European Patent Office
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3dT8IwEL8gfuCbokbxqyZmb4vsg7E9LEY2FlQYxKDhjWxtBxjdFjYk8a-3LUN90dc2bXptrte73u93ANekHpmBGhoyDhuRrKvEkgNLw7KGia5ggi3V4EDhnm90nvWHUWNUgtc1FkbwhC4FOSLTKMz0PRf3dfoTxHJFbmV2E85YU3LrDW1XKrxjYZ4UyW3Z7UHf7TuS49iOL_lPNsdXNjnd2N0GbLIntsl59tsvLY5KSX-bFG8PtgZstjjfh9LntAoVZ115rQo7veLDuwrbIkMTZ6yx0MLsACYehzYJfCHKgpig9G3BA8cTxBPFEeWcxWi5CnmgVYloxK0VQUmMCKUpKmpFTBAfTRImNUXsEmR-cz59n2GEF_MPmh3CldceOh2ZrX38vVFjx_8RUzuCcpzE9BgQNlRdq4d6E9OGHqnUCqkaNnFgmUoUmdQ8gdrf89T-67yESmfY64679_7jKezyA-BpVIpyBuV8vqDnzGDn4YXY6S8hkpv0
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=Fracturing+sand+plugging+risk+early+warning+method+based+on+deep+learning+and+double+logarithmic+curves&rft.inventor=WANG+LIN&rft.inventor=ZHU+NAN&rft.inventor=WEI+MIAN&rft.inventor=LIU+YIJIA&rft.inventor=HUANG+QI&rft.inventor=WANG+FANGXIANG&rft.inventor=GENG+TENG&rft.inventor=YANG+XIN&rft.inventor=DONG+BINGXIANG&rft.inventor=LI+NAN&rft.inventor=LIN+CHUNLAI&rft.inventor=DU+HUIMIN&rft.inventor=SHAO+JUNLONG&rft.date=2024-06-11&rft.externalDBID=A&rft.externalDocID=CN118171552A