{"id":"https://openalex.org/W4312309605","doi":"https://doi.org/10.1109/lgrs.2022.3211855","title":"Seismic Internal Multiple Suppression Based on Convolutional Neural Network","display_name":"Seismic Internal Multiple Suppression Based on Convolutional Neural Network","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312309605","doi":"https://doi.org/10.1109/lgrs.2022.3211855"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3211855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3211855","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5101746311","display_name":"Xiaozhou Liu","orcid":"https://orcid.org/0000-0003-2097-2248"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaozhou Liu","raw_affiliation_strings":["School of Earth and Space Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Earth and Space Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048075639","display_name":"Tianyue Hu","orcid":"https://orcid.org/0000-0002-7144-6240"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyue Hu","raw_affiliation_strings":["School of Earth and Space Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Earth and Space Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021088424","display_name":"Shangxu Wang","orcid":"https://orcid.org/0000-0003-0265-5679"},"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":"Shangxu Wang","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071128160","display_name":"Tao Liu","orcid":"https://orcid.org/0000-0002-5212-2806"},"institutions":[{"id":"https://openalex.org/I106994412","display_name":"Sinopec (China)","ror":"https://ror.org/0161q6d74","country_code":"CN","type":"company","lineage":["https://openalex.org/I106994412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Liu","raw_affiliation_strings":["Petroleum Exploration and Production Research Institute, SINOPEC, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Petroleum Exploration and Production Research Institute, SINOPEC, Beijing, China","institution_ids":["https://openalex.org/I106994412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103243750","display_name":"Zhefeng Wei","orcid":"https://orcid.org/0009-0004-2146-9374"},"institutions":[{"id":"https://openalex.org/I106994412","display_name":"Sinopec (China)","ror":"https://ror.org/0161q6d74","country_code":"CN","type":"company","lineage":["https://openalex.org/I106994412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhefeng Wei","raw_affiliation_strings":["Petroleum Exploration and Production Research Institute, SINOPEC, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Petroleum Exploration and Production Research Institute, SINOPEC, Beijing, China","institution_ids":["https://openalex.org/I106994412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101746311"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.7258,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66379458,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10892","display_name":"Drilling and Well Engineering","score":0.9894000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7833250761032104},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6842831373214722},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5534619092941284},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.529539942741394},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5282177925109863},{"id":"https://openalex.org/keywords/multiple","display_name":"Multiple","score":0.5270947217941284},{"id":"https://openalex.org/keywords/internal-model","display_name":"Internal model","score":0.5155982375144958},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4958876073360443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47070786356925964},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44477391242980957},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4418211579322815},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.418887734413147},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3752891719341278},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3723607659339905}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7833250761032104},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6842831373214722},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5534619092941284},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.529539942741394},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5282177925109863},{"id":"https://openalex.org/C164680029","wikidata":"https://www.wikidata.org/wiki/Q1055293","display_name":"Multiple","level":2,"score":0.5270947217941284},{"id":"https://openalex.org/C28427503","wikidata":"https://www.wikidata.org/wiki/Q13580300","display_name":"Internal model","level":3,"score":0.5155982375144958},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4958876073360443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47070786356925964},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44477391242980957},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4418211579322815},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.418887734413147},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3752891719341278},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3723607659339905},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"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/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"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/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3211855","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3211855","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1163816257","display_name":null,"funder_award_id":"2018YFA0702504","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4818780853","display_name":null,"funder_award_id":"42274163","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8191065229","display_name":null,"funder_award_id":"2018YFA0702503","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2037315823","https://openalex.org/W2129556296","https://openalex.org/W2139984951","https://openalex.org/W2154222811","https://openalex.org/W2172044679","https://openalex.org/W2508457857","https://openalex.org/W2883930576","https://openalex.org/W2890833618","https://openalex.org/W2904005001","https://openalex.org/W2966618135","https://openalex.org/W2966965831","https://openalex.org/W3185680294","https://openalex.org/W3185921949","https://openalex.org/W3215008000","https://openalex.org/W4280535417","https://openalex.org/W4284969399"],"related_works":["https://openalex.org/W3093612317","https://openalex.org/W2175746458","https://openalex.org/W2732542196","https://openalex.org/W2760085659","https://openalex.org/W2883200793","https://openalex.org/W2738221750","https://openalex.org/W3012978760","https://openalex.org/W2912288872","https://openalex.org/W2940661641","https://openalex.org/W2758063741"],"abstract_inverted_index":{"Internal":[0,34],"multiple":[1,35,66,98],"suppression":[2,36,67],"remains":[3],"a":[4,58,90,174],"key":[5],"challenge":[6],"in":[7,68,177,186],"seismic":[8,130,140],"processing":[9],"due":[10],"to":[11,77,88,101,128],"the":[12,50,83,103,108,133,138],"tiny":[13],"velocity":[14],"and":[15,21,32,49,74,94,106,125,135,154,161,172,182,190],"periodicity":[16],"difference":[17],"between":[18],"primary":[19,92,191],"reflections":[20],"internal":[22,27,65,97,170],"multiples.":[23],"Existing":[24],"methods":[25,181],"suppress":[26],"multiples":[28,171],"with":[29,179],"poor":[30],"adaptivity":[31],"efficiency.":[33],"based":[37,111,121],"on":[38,112,122,159],"artificial":[39],"intelligence":[40],"(AI)":[41],"faces":[42],"challenges":[43],"about":[44],"highly":[45],"demanded":[46],"computing":[47,152],"resources":[48,153],"lack":[51],"of":[52,70],"sufficient":[53],"labels.":[54],"This":[55],"letter":[56],"redesigns":[57],"convolutional":[59],"neural":[60],"network":[61,109,148],"(CNN)":[62],"scheme":[63],"for":[64,150],"terms":[69],"training":[71,104,134],"set":[72,105],"construction":[73],"input":[75],"strategy":[76,100],"alleviate":[78],"these":[79],"problems.":[80],"We":[81],"adopt":[82],"virtual":[84],"event":[85],"(VE)":[86],"method":[87,167],"generate":[89],"few":[91],"labels":[93],"develop":[95],"an":[96],"augmentation":[99],"expand":[102],"improve":[107],"performance":[110,176],"small":[113],"data":[114,141,163],"set.":[115],"The":[116],"U-shaped":[117],"CNN":[118,185],"is":[119],"trained":[120],"augmented":[123],"datasets":[124],"then":[126],"applied":[127],"new":[129],"data.":[131],"During":[132],"prediction":[136],"process,":[137],"entire":[139],"are":[142],"split":[143],"into":[144],"vertical":[145],"patches":[146],"as":[147],"inputs":[149],"less":[151],"better":[155],"demultipling":[156,184],"performance.":[157],"Tests":[158],"synthetic":[160],"field":[162],"demonstrate":[164],"that":[165],"our":[166],"effectively":[168],"suppresses":[169],"exhibits":[173],"competitive":[175],"comparison":[178],"existing":[180],"original":[183],"efficiency,":[187],"memory":[188],"cost,":[189],"retention":[192],"ability.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}