乐胖代购免代理版

{"id":"https://openalex.org/W1993234211","doi":"https://doi.org/10.1109/icdmw.2011.151","title":"Semi-supervised Failure Prediction for Oil Production Wells","display_name":"Semi-supervised Failure Prediction for Oil Production Wells","publication_year":2011,"publication_date":"2011-12-01","ids":{"openalex":"https://openalex.org/W1993234211","doi":"https://doi.org/10.1109/icdmw.2011.151","mag":"1993234211"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw.2011.151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070524866","display_name":"Yintao Liu","orcid":"https://orcid.org/0009-0004-8096-3647"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"funder","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yintao Liu","raw_affiliation_strings":["[Inf. Sci. Inst., Univ. of Southern California, Marina del Rey, CA, USA]"],"affiliations":[{"raw_affiliation_string":"[Inf. Sci. Inst., Univ. of Southern California, Marina del Rey, CA, USA]","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102088852","display_name":"Ke-Thia Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"funder","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ke-Thia Yao","raw_affiliation_strings":["[Inf. Sci. Inst., Univ. of Southern California, Marina del Rey, CA, USA]"],"affiliations":[{"raw_affiliation_string":"[Inf. Sci. Inst., Univ. of Southern California, Marina del Rey, CA, USA]","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111240135","display_name":"Shuping Liu","orcid":"https://orcid.org/0000-0002-7309-0284"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"funder","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuping Liu","raw_affiliation_strings":["Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112293594","display_name":"C.S. Raghavendra","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"funder","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cauligi S. Raghavendra","raw_affiliation_strings":["Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037959901","display_name":"Oluwafemi Balogun","orcid":"https://orcid.org/0000-0002-6578-1851"},"institutions":[{"id":"https://openalex.org/I186131212","display_name":"Chevron (Netherlands)","ror":"https://ror.org/053k40h13","country_code":"NL","type":"company","lineage":["https://openalex.org/I186131212","https://openalex.org/I4210118014"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Oluwafemi Balogun","raw_affiliation_strings":["[Chevron Corporation, Houston, TX, USA]"],"affiliations":[{"raw_affiliation_string":"[Chevron Corporation, Houston, TX, USA]","institution_ids":["https://openalex.org/I186131212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071312607","display_name":"Lanre Olabinjo","orcid":null},"institutions":[{"id":"https://openalex.org/I186131212","display_name":"Chevron (Netherlands)","ror":"https://ror.org/053k40h13","country_code":"NL","type":"company","lineage":["https://openalex.org/I186131212","https://openalex.org/I4210118014"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Lanre Olabinjo","raw_affiliation_strings":["[Chevron Corporation, Houston, TX, USA]"],"affiliations":[{"raw_affiliation_string":"[Chevron Corporation, Houston, TX, USA]","institution_ids":["https://openalex.org/I186131212"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.158,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":19,"citation_normalized_percentile":{"value":0.925578,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":90},"biblio":{"volume":null,"issue":null,"first_page":"434","last_page":"441"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.9989,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.9989,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9878,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14470","display_name":"Advanced Data Processing Techniques","score":0.9795,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/downtime","display_name":"Downtime","score":0.7495551},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.60964215},{"id":"https://openalex.org/keywords/artificial-lift","display_name":"Artificial lift","score":0.4983065},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature Engineering","score":0.4248477}],"concepts":[{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.7495551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6413774},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.60964215},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.509976},{"id":"https://openalex.org/C2776873729","wikidata":"https://www.wikidata.org/wiki/Q4801085","display_name":"Artificial lift","level":2,"score":0.4983065},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4909075},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4248477},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37185407},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35933846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35196227},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.34380656},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26095906},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.19788429},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw.2011.151","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.54,"display_name":"Life below water"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":16,"referenced_works":["https://openalex.org/W1539047752","https://openalex.org/W2001141328","https://openalex.org/W2049877533","https://openalex.org/W2053186076","https://openalex.org/W2058148593","https://openalex.org/W2061122559","https://openalex.org/W2094924503","https://openalex.org/W2096121981","https://openalex.org/W2103448012","https://openalex.org/W2127541971","https://openalex.org/W2133990480","https://openalex.org/W2153635508","https://openalex.org/W2168299027","https://openalex.org/W3120421331","https://openalex.org/W4210997624","https://openalex.org/W4399856703"],"related_works":["https://openalex.org/W4232717613","https://openalex.org/W3188932433","https://openalex.org/W3009187840","https://openalex.org/W2954002293","https://openalex.org/W2892741875","https://openalex.org/W2885083539","https://openalex.org/W2499493201","https://openalex.org/W2391502294","https://openalex.org/W2367839174","https://openalex.org/W2046276983"],"abstract_inverted_index":{"In":[0],"the":[1,13,26,34,49,111,139],"petroleum":[2],"industry,":[3],"multivariate":[4,167],"time":[5,168],"series":[6],"data":[7,106,114],"is":[8],"commonly":[9],"used":[10],"to":[11,33,53,82,89,94,105,156],"monitor":[12],"performance":[14],"of":[15,55,59,110,122,159],"their":[16],"assets,":[17],"in":[18],"which":[19],"wells":[20],"artificial":[21,41,133],"lift":[22,42,98,134],"systems":[23],"are":[24],"among":[25,39,129],"key":[27],"assets":[28],"that":[29,145],"bring":[30],"oil":[31],"up":[32],"surface.":[35],"Failures":[36],"frequently":[37],"occur":[38,70],"these":[40,66],"systems,":[43],"and":[44,57,93,126,152,164,175],"they":[45,69],"can":[46,71],"greatly":[47],"increase":[48],"operational":[50,74],"expense":[51],"due":[52],"loss":[54],"production":[56],"cost":[58],"repairs":[60,92],"(also":[61],"known":[62],"as":[63,77,117],"workovers).":[64],"Predicting":[65],"failures":[67,84,178],"before":[68],"dramatically":[72],"improve":[73],"performance,":[75],"such":[76,116],"by":[78,86],"adjusting":[79],"operating":[80],"parameters":[81],"forestall":[83],"or":[85],"scheduling":[87],"maintenance":[88],"reduce":[90],"unplanned":[91],"minimize":[95],"downtime.":[96],"Artificial":[97],"failure":[99,123],"prediction":[100],"problem":[101],"poses":[102],"interesting":[103],"challenges":[104],"mining":[107],"algorithms,":[108],"because":[109],"many":[112],"real-world":[113,180],"issues,":[115],"noise,":[118],"missing":[119],"data,":[120],"delay":[121],"event":[124],"logs,":[125],"large":[127],"variability":[128],"normally":[130],"functioning":[131],"well":[132],"units.":[135],"This":[136],"paper":[137],"presents":[138],"Smart":[140],"Engineering":[141],"Apprentice":[142],"(SEA)":[143],"framework":[144],"incorporates":[146],"robust":[147],"feature":[148],"extraction":[149],"algorithm,":[150],"clustering":[151],"semi-supervised":[153],"learning":[154,158],"techniques,":[155],"enable":[157],"failure/normal":[160],"patterns":[161],"from":[162],"noisy":[163],"poorly":[165],"labeled":[166],"series,":[169],"while":[170],"achieving":[171],"a":[172],"high":[173],"recall":[174],"precision":[176],"for":[177,179],"dataset.":[181]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1993234211","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2025-03-29T10:58:18.076083","created_date":"2016-06-24"}