{"id":"https://openalex.org/W2019920211","doi":"https://doi.org/10.2118/174062-ms","title":"Data Driven Approach to Failure Prediction for Electrical Submersible Pump Systems","display_name":"Data Driven Approach to Failure Prediction for Electrical Submersible Pump Systems","publication_year":2015,"publication_date":"2015-04-20","ids":{"openalex":"https://openalex.org/W2019920211","doi":"https://doi.org/10.2118/174062-ms","mag":"2019920211"},"language":"en","primary_location":{"id":"doi:10.2118/174062-ms","doi":"https://doi.org/10.2118/174062-ms","is_oa":false,"landing_page_url":"https://doi.org/10.2118/174062-ms","pdf_url":null,"source":{"id":"https://openalex.org/S4306530718","display_name":"SPE Western Regional Meeting","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPE Western Regional Meeting","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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":null,"display_name":"Dong Guo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Guo","raw_affiliation_strings":["USC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USC","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112293594","display_name":"Cauligi S. Raghavendra","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cauligi S. Raghavendra","raw_affiliation_strings":["USC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USC","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102088852","display_name":"Ke-Thia Yao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ke-Thia Yao","raw_affiliation_strings":["USC ISI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USC ISI","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mark Harding","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210118014","display_name":"Chevron (United States)","ror":"https://ror.org/02jfa8730","country_code":"US","type":"company","lineage":["https://openalex.org/I4210118014"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Harding","raw_affiliation_strings":["Chevron U.S.A., Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chevron U.S.A., Inc","institution_ids":["https://openalex.org/I4210118014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110318285","display_name":"Amir Anvar","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210118014","display_name":"Chevron (United States)","ror":"https://ror.org/02jfa8730","country_code":"US","type":"company","lineage":["https://openalex.org/I4210118014"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir Anvar","raw_affiliation_strings":["Chevron U.S.A., Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chevron U.S.A., Inc","institution_ids":["https://openalex.org/I4210118014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072381348","display_name":"Anil Patel","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210118014","display_name":"Chevron (United States)","ror":"https://ror.org/02jfa8730","country_code":"US","type":"company","lineage":["https://openalex.org/I4210118014"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anil Patel","raw_affiliation_strings":["Chevron U.S.A., Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chevron U.S.A., Inc","institution_ids":["https://openalex.org/I4210118014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6747,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.87862889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2103","display_name":"Fuel Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"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":1.0,"subfield":{"id":"https://openalex.org/subfields/2103","display_name":"Fuel Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":9.999999747378752e-05,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.0,"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/electric-submersible-pumps","display_name":"electric submersible pumps","score":0.9890000224113464},{"id":"https://openalex.org/keywords/failure-prediction","display_name":"failure prediction","score":0.9369999766349792},{"id":"https://openalex.org/keywords/condition-monitoring","display_name":"condition monitoring","score":0.628000020980835},{"id":"https://openalex.org/keywords/artificial-lift","display_name":"artificial lift","score":0.6399999856948853},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.718999981880188},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8090000152587891},{"id":"https://openalex.org/keywords/well-maintenance","display_name":"well maintenance","score":0.5630000233650208},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"predictive maintenance","score":0.6029999852180481}],"concepts":[{"id":"https://openalex.org/C2776873729","wikidata":"https://www.wikidata.org/wiki/Q4801085","display_name":"Artificial lift","level":2,"score":0.8320209980010986},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.7721791863441467},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7294497489929199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5593257546424866},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5230028033256531},{"id":"https://openalex.org/C2777741327","wikidata":"https://www.wikidata.org/wiki/Q1853644","display_name":"Submersible pump","level":2,"score":0.4928012192249298},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48993414640426636},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4128669500350952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4061427712440491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3929429352283478},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.32240307331085205},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.11306089162826538},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2118/174062-ms","doi":"https://doi.org/10.2118/174062-ms","is_oa":false,"landing_page_url":"https://doi.org/10.2118/174062-ms","pdf_url":null,"source":{"id":"https://openalex.org/S4306530718","display_name":"SPE Western Regional Meeting","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPE Western Regional Meeting","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5378999710083008,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1663973292","https://openalex.org/W1979879056","https://openalex.org/W2153635508","https://openalex.org/W2187089797","https://openalex.org/W2483430316","https://openalex.org/W2594639291"],"related_works":["https://openalex.org/W4403576734","https://openalex.org/W4377225018","https://openalex.org/W7172099291","https://openalex.org/W4401349326","https://openalex.org/W7045228143","https://openalex.org/W2964692134","https://openalex.org/W4280501636","https://openalex.org/W7153018967","https://openalex.org/W4307665271","https://openalex.org/W2988917657"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"paper":[2],"presents":[3],"a":[4,120],"data":[5,90],"driven":[6],"approach":[7,129,141],"for":[8,11,52,82],"failure":[9,110],"prediction":[10],"Electrical":[12],"Submersible":[13],"Pumps":[14],"(ESP).":[15],"ESP":[16,54,68,84,99],"system":[17],"is":[18,55,101,125,130],"well":[19,108,143],"known":[20],"as":[21],"an":[22,53],"effective":[23],"artificial":[24,63],"lift":[25,64],"method":[26],"which":[27],"has":[28],"been":[29],"applied":[30],"to":[31,44,103],"about":[32],"20":[33],"percent":[34],"of":[35,61,106,122],"almost":[36],"one":[37],"million":[38],"wells":[39],"worldwide.":[40],"Well":[41],"failures":[42,69,85],"lead":[43],"production":[45],"loss":[46],"and":[47,88,109,127],"generally":[48],"the":[49,92,152],"repair":[50],"cost":[51],"usually":[56],"much":[57],"higher":[58],"than":[59],"those":[60],"other":[62],"systems,":[65],"thus":[66],"predicting":[67,83],"before":[70],"they":[71],"occur":[72],"will":[73],"be":[74],"valuable.":[75],"We":[76],"apply":[77],"advanced":[78],"machine":[79],"learning":[80],"techniques":[81],"using":[86,98],"electrical":[87],"frequency":[89],"from":[91,95,147],"field.":[93],"Data":[94],"real-world":[96],"assets":[97],"systems":[100],"analyzed":[102],"learn":[104],"examples":[105],"normal":[107],"conditions.":[111],"A":[112],"generalized":[113],"Support":[114],"Vector":[115],"Machine":[116],"(SVM)":[117],"trained":[118],"with":[119],"set":[121],"selected":[123],"features":[124],"developed":[126],"this":[128,140],"tested":[131],"on":[132,145,151],"real":[133],"world":[134],"data.":[135],"Our":[136],"results":[137],"show":[138],"that":[139],"works":[142],"based":[144],"feedback":[146],"subject":[148],"matter":[149],"experts":[150],"results.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2016,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}