{"id":"https://openalex.org/W4400579238","doi":"https://doi.org/10.1109/tgrs.2024.3427364","title":"A Deep Learning Object Detection Method for Fracture Identification Using Conventional Well Logs","display_name":"A Deep Learning Object Detection Method for Fracture Identification Using Conventional Well Logs","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400579238","doi":"https://doi.org/10.1109/tgrs.2024.3427364"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3427364","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3427364","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"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/A5037654493","display_name":"Shaoqun Dong","orcid":"https://orcid.org/0000-0001-8204-7336"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaoqun Dong","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023979927","display_name":"Jingru Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingru Hao","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058749575","display_name":"Lianbo Zeng","orcid":"https://orcid.org/0000-0002-6470-8206"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianbo Zeng","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055879028","display_name":"Yang Xu","orcid":"https://orcid.org/0000-0003-0177-6348"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Yang","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031436628","display_name":"Leting Wang","orcid":"https://orcid.org/0000-0003-1017-7830"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leting Wang","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073617550","display_name":"Chunqiu Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunqiu Ji","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036872947","display_name":"Zhaohui Zhong","orcid":"https://orcid.org/0000-0001-5050-7182"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohui Zhong","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101639627","display_name":"Shutong Chen","orcid":"https://orcid.org/0000-0003-0330-4192"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutong Chen","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114190338","display_name":"Kaifeng Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaifeng Fu","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5037654493"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":2.4879,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.88094122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10892","display_name":"Drilling and Well Engineering","score":0.9800000190734863,"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":0.9800000190734863,"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/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9049000144004822,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6581062078475952},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6508958339691162},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6063714027404785},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5646654367446899},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5601398944854736},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4515083432197571},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4274088740348816},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42160019278526306},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3965078294277191},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.25524869561195374}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6581062078475952},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6508958339691162},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6063714027404785},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5646654367446899},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5601398944854736},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4515083432197571},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4274088740348816},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42160019278526306},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3965078294277191},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.25524869561195374},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3427364","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3427364","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2106725616","display_name":null,"funder_award_id":"2021T140735","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1754300596","https://openalex.org/W1972936626","https://openalex.org/W2091007025","https://openalex.org/W2282312309","https://openalex.org/W2287024948","https://openalex.org/W2612353157","https://openalex.org/W2809146475","https://openalex.org/W2834213610","https://openalex.org/W2935524202","https://openalex.org/W2943284727","https://openalex.org/W2998530348","https://openalex.org/W3004206781","https://openalex.org/W3006434587","https://openalex.org/W3007266227","https://openalex.org/W3011722050","https://openalex.org/W3026685102","https://openalex.org/W3036477896","https://openalex.org/W3037458206","https://openalex.org/W3048875527","https://openalex.org/W3088667723","https://openalex.org/W3094929171","https://openalex.org/W3103302088","https://openalex.org/W3121502091","https://openalex.org/W3121637738","https://openalex.org/W3123932902","https://openalex.org/W3144804712","https://openalex.org/W3159777636","https://openalex.org/W3167921710","https://openalex.org/W3175509498","https://openalex.org/W3188777946","https://openalex.org/W3189165652","https://openalex.org/W3197867873","https://openalex.org/W3198824468","https://openalex.org/W3201872403","https://openalex.org/W4200343878","https://openalex.org/W4205316494","https://openalex.org/W4220776041","https://openalex.org/W4224216202","https://openalex.org/W4229069375","https://openalex.org/W4280543146","https://openalex.org/W4285186695","https://openalex.org/W4289928578","https://openalex.org/W4291202051","https://openalex.org/W4294675495","https://openalex.org/W4297499177","https://openalex.org/W4297916399","https://openalex.org/W4308641263","https://openalex.org/W4310721002","https://openalex.org/W4313215877","https://openalex.org/W4313420411","https://openalex.org/W4317399220","https://openalex.org/W4317491844","https://openalex.org/W4353096542","https://openalex.org/W4362605699","https://openalex.org/W4367317376","https://openalex.org/W4377027832","https://openalex.org/W4381433614","https://openalex.org/W4383500885","https://openalex.org/W4385154963","https://openalex.org/W4386093983","https://openalex.org/W4386453639","https://openalex.org/W4388681906","https://openalex.org/W4391255531","https://openalex.org/W6847470208"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2588268827","https://openalex.org/W2949096641","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W3034745255","https://openalex.org/W4254103348","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Reservoir":[0],"characterization":[1],"struggles":[2],"with":[3,154,221],"identifying":[4],"fractures,":[5],"a":[6,15,36,78,114,155,222],"typical":[7],"imbalance":[8,91],"classification":[9],"problem.":[10],"To":[11,111,211],"handle":[12],"this":[13],"issue,":[14],"novel":[16],"approach":[17,107],"called":[18],"fracture":[19,46,168,209],"identification":[20,47,169],"by":[21,170,199],"sliding":[22,79,105,171],"windows":[23],"and":[24,38,66,99,136,193],"you":[25],"only":[26],"look":[27],"once":[28],"(YOLO)":[29],"(FISY)":[30],"is":[31],"proposed.":[32],"FISY":[33,166],"utilizes":[34],"YOLO,":[35],"fast":[37],"accurate":[39],"object":[40,142],"detection":[41,51],"neural":[42],"network,":[43],"to":[44],"transform":[45],"into":[48],"an":[49,219],"abnormality":[50,86],"task.":[52],"Conventional":[53],"well":[54,164],"logs":[55],"from":[56,116],"specific":[57],"interval":[58],"formations":[59],"are":[60,75],"used":[61],"as":[62],"the":[63,71,84,100,104,120,149,181,227],"detected":[64],"image,":[65],"adjacent":[67],"depth":[68,94],"intervals":[69],"enhance":[70],"analysis.":[72],"Image":[73],"samples":[74],"generated":[76],"via":[77],"window":[80,106,172],"approach.":[81],"YOLO":[82,179],"detects":[83],"minority":[85,184],"class":[87],"(fractures),":[88],"addressing":[89],"data":[90],"issues.":[92],"Each":[93],"sample":[95],"undergoes":[96],"multiple":[97],"scans,":[98],"probability":[101],"superposition":[102],"of":[103,159],"reduces":[108],"forecast":[109],"uncertainty.":[110],"assess":[112,213],"FISY,":[113,146],"dataset":[115,225],"carbonate":[117],"reservoirs":[118],"in":[119,141,180,202,208,226,230],"Asmari":[121],"Formation,":[122],"Middle":[123],"East,":[124],"was":[125],"used.":[126],"The":[127],"mean":[128],"average":[129],"precision":[130,135],"(mAP)":[131],"evaluation":[132],"metric,":[133],"combining":[134],"recall,":[137],"assesses":[138],"FISY\u2019s":[139,214,233],"performance":[140,235],"detection.":[143],"Among":[144],"five-scaled":[145],"XLarge":[147],"demonstrates":[148],"highest":[150],"mAP":[151],"at":[152],"99.16%,":[153],"rapid":[156],"prediction":[157],"time":[158],"4":[160],"ms/image.":[161],"In":[162],"blind":[163],"tests,":[165],"surpasses":[167],"(FIS)":[173],"+":[174,188,195],"Transformer":[175],"(TF)":[176],"(TF":[177],"replacing":[178],"FISY),":[182],"synthetic":[183],"oversampling":[185],"technique":[186],"(SMOTE)":[187],"support":[189],"vector":[190],"machine":[191],"(SVM),":[192],"SMOTE":[194],"random":[196],"forests":[197],"(RFs)":[198],"over":[200],"13%":[201],"F1":[203],"score,":[204],"showcasing":[205],"its":[206],"efficacy":[207],"identification.":[210],"further":[212],"generalization":[215],"across":[216],"various":[217],"lithologies,":[218],"experiment":[220],"clastic":[223],"reservoir":[224],"Ordos":[228],"Basin":[229],"China":[231],"reveals":[232],"good":[234],"(mAP":[236],"87.5%).":[237]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
