乐胖代购免代理版

{"id":"https://openalex.org/W4389490212","doi":"https://doi.org/10.1145/3632314.3632347","title":"Convolutional Neural Network and Long Short-Term Memory Integrated ROP Prediction Model Introduced Attention Mechanism","display_name":"Convolutional Neural Network and Long Short-Term Memory Integrated ROP Prediction Model Introduced Attention Mechanism","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4389490212","doi":"https://doi.org/10.1145/3632314.3632347"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3632314.3632347","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/A5103097938","display_name":"Gang Liu","orcid":"https://orcid.org/0009-0006-3651-9076"},"institutions":[{"id":"https://openalex.org/I4210162188","display_name":"Shaanxi Yanchang Petroleum (China)","ror":"https://ror.org/05crb7x25","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210162188"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Liu","raw_affiliation_strings":["Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China"],"affiliations":[{"raw_affiliation_string":"Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China","institution_ids":["https://openalex.org/I4210162188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062884994","display_name":"Ma Fei","orcid":"https://orcid.org/0009-0008-3036-4258"},"institutions":[{"id":"https://openalex.org/I4210162188","display_name":"Shaanxi Yanchang Petroleum (China)","ror":"https://ror.org/05crb7x25","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210162188"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Ma","raw_affiliation_strings":["Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China"],"affiliations":[{"raw_affiliation_string":"Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China","institution_ids":["https://openalex.org/I4210162188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086288173","display_name":"Chaobo Fan","orcid":"https://orcid.org/0009-0002-6089-3237"},"institutions":[{"id":"https://openalex.org/I4210162188","display_name":"Shaanxi Yanchang Petroleum (China)","ror":"https://ror.org/05crb7x25","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210162188"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaobo Fan","raw_affiliation_strings":["Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China"],"affiliations":[{"raw_affiliation_string":"Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China","institution_ids":["https://openalex.org/I4210162188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077035316","display_name":"\u8061 \u5d8b\u8107","orcid":"https://orcid.org/0009-0009-4006-1776"},"institutions":[{"id":"https://openalex.org/I4210162188","display_name":"Shaanxi Yanchang Petroleum (China)","ror":"https://ror.org/05crb7x25","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210162188"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Xie","raw_affiliation_strings":["Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China"],"affiliations":[{"raw_affiliation_string":"Yanchang Gas Field, Shaanxi Yanchang Petroleum Group, China","institution_ids":["https://openalex.org/I4210162188"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108050283","display_name":"Qi Li","orcid":"https://orcid.org/0000-0002-0060-3376"},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["College of Petroleum Engineering, Xi'an Shiyou University, China"],"affiliations":[{"raw_affiliation_string":"College of Petroleum Engineering, Xi'an Shiyou University, China","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045632526","display_name":"Weijun Ni","orcid":"https://orcid.org/0009-0006-4958-3755"},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijun Ni","raw_affiliation_strings":["College of Petroleum Engineering, Xi'an Shiyou University, China"],"affiliations":[{"raw_affiliation_string":"College of Petroleum Engineering, Xi'an Shiyou University, China","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101714851","display_name":"Hong Xu","orcid":"https://orcid.org/0009-0004-5165-4706"},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Xu","raw_affiliation_strings":["College of Petroleum Engineering, Xi'an Shiyou University, China"],"affiliations":[{"raw_affiliation_string":"College of Petroleum Engineering, Xi'an Shiyou University, China","institution_ids":["https://openalex.org/I181903023"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":66},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10892","display_name":"Drilling and Well Engineering","score":1.0,"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/T10892","display_name":"Drilling and Well Engineering","score":1.0,"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/T13050","display_name":"Oil and Gas Production Techniques","score":0.9969,"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/T10635","display_name":"Hydraulic Fracturing and Reservoir Analysis","score":0.9966,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/relevance","display_name":"Relevance","score":0.42091757}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.88085866},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6688944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.57364017},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.5458988},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.53143406},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47891128},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47429067},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4585161},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44936007},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.44755083},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4411016},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.42091757},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.41420078},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.41331968},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3632314.3632347","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":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":16,"referenced_works":["https://openalex.org/W1689711448","https://openalex.org/W1964022399","https://openalex.org/W1968376774","https://openalex.org/W1969515262","https://openalex.org/W1969793285","https://openalex.org/W1974971437","https://openalex.org/W2013345849","https://openalex.org/W2021098490","https://openalex.org/W2108643226","https://openalex.org/W2130416988","https://openalex.org/W2136848157","https://openalex.org/W2151162785","https://openalex.org/W2165171393","https://openalex.org/W2942039255","https://openalex.org/W3146366485","https://openalex.org/W4253822329"],"related_works":["https://openalex.org/W4390245176","https://openalex.org/W4387163678","https://openalex.org/W4385280324","https://openalex.org/W4288108708","https://openalex.org/W3173606726","https://openalex.org/W2984436043","https://openalex.org/W2973430807","https://openalex.org/W2912831041","https://openalex.org/W2912153778","https://openalex.org/W2890685186"],"abstract_inverted_index":{"Accurately":[0],"predicting":[1],"Rate":[2],"of":[3,133,164],"Penetration":[4],"(ROP)":[5],"plays":[6],"a":[7,42],"crucial":[8],"role":[9],"in":[10,162],"optimizing":[11],"and":[12,47,141,159],"controlling":[13],"drilling":[14,64,74],"operations.":[15],"Optimizing":[16],"ROP":[17,33],"not":[18],"only":[19],"enhances":[20],"production":[21],"efficiency":[22],"but":[23],"also":[24],"reduces":[25],"costs":[26],"effectively.":[27],"Therefore,":[28],"we":[29,66,80,109,124,150],"propose":[30],"an":[31,38,126],"integrated":[32],"prediction":[34,144,165],"model":[35],"that":[36,152],"incorporates":[37],"attention":[39,127],"mechanism":[40,128],"into":[41,101],"Convolutional":[43],"Neural":[44],"Network":[45],"(CNN)":[46],"Long":[48],"Short-Term":[49],"Memory":[50],"network":[51],"(LSTM).":[52],"In":[53],"order":[54],"to":[55,71,86,93,129],"fully":[56],"exploit":[57],"the":[58,62,72,102,111,119,131,134,143],"valuable":[59],"information":[60,83],"within":[61],"original":[63],"data,":[65],"first":[67],"apply":[68],"Fourier":[69],"transform":[70],"live":[73],"data":[75,77,89,97],"for":[76,104,113],"denoising.":[78],"Subsequently,":[79],"employ":[81],"mutual":[82],"correlation":[84],"analysis":[85],"select":[87],"input":[88],"with":[90],"high":[91],"relevance":[92],"ROP.":[94],"The":[95],"denoised":[96],"is":[98],"then":[99],"fed":[100],"CNN":[103,158],"feature":[105],"extraction.":[106],"Following":[107],"that,":[108],"utilize":[110],"LSTM":[112,135],"time":[114],"series":[115],"analysis,":[116],"effectively":[117],"leveraging":[118],"long-term":[120],"sequential":[121],"data.":[122],"Moreover,":[123],"introduce":[125],"weigh":[130],"output":[132],"layer,":[136],"thus":[137],"highlighting":[138],"key":[139],"features":[140],"improving":[142],"results.":[145],"Finally,":[146],"through":[147],"empirical":[148],"simulation,":[149],"demonstrate":[151],"our":[153],"proposed":[154],"approach":[155],"outperforms":[156],"traditional":[157],"CNN-LSTM":[160],"methods":[161],"terms":[163],"performance,":[166],"showcasing":[167],"its":[168],"practical":[169],"value.":[170]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4389490212","counts_by_year":[],"updated_date":"2025-02-23T02:02:04.633779","created_date":"2023-12-09"}