{"id":"https://openalex.org/W4380231007","doi":"https://doi.org/10.1190/geo2022-0599.1","title":"Surface-related multiple attenuation based on a self-supervised deep neural network with local wavefield characteristics","display_name":"Surface-related multiple attenuation based on a self-supervised deep neural network with local wavefield characteristics","publication_year":2023,"publication_date":"2023-05-11","ids":{"openalex":"https://openalex.org/W4380231007","doi":"https://doi.org/10.1190/geo2022-0599.1"},"language":"en","primary_location":{"id":"doi:10.1190/geo2022-0599.1","doi":"https://doi.org/10.1190/geo2022-0599.1","is_oa":false,"landing_page_url":"https://doi.org/10.1190/geo2022-0599.1","pdf_url":null,"source":{"id":"https://openalex.org/S106174089","display_name":"Geophysics","issn_l":"0016-8033","issn":["0016-8033","1942-2156"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-a","jufo-1","norway-2","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310316678","host_organization_name":"Society of Exploration Geophysicists","host_organization_lineage":["https://openalex.org/P4310316678"],"host_organization_lineage_names":["Society of Exploration Geophysicists"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geophysics","raw_type":"journal-article"},"volume":null,"type":"article","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":"https://openalex.org/A5064266753","display_name":"Kunxi Wang","orcid":"https://orcid.org/0000-0002-5446-2185","observed_orcids":["https://orcid.org/0000-0002-5446-2185"]},"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":"Kunxi Wang","raw_affiliation_strings":["Peking University 1 , Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China. kxwang@stu.pku.edu.cn","Peking University, Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5446-2185","affiliations":[{"raw_affiliation_string":"Peking University 1 , Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China. kxwang@stu.pku.edu.cn","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University, Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, 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","observed_orcids":["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":["Peking University 1 , Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China. tianyue@pku.edu.cn (corresponding author)","Peking University, Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China. (corresponding author)"],"raw_orcid":"https://orcid.org/0000-0002-7144-6240","affiliations":[{"raw_affiliation_string":"Peking University 1 , Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China. tianyue@pku.edu.cn (corresponding author)","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University, Institute of Energy, Institute for Artificial Intelligence, School of Earth and Space Sciences, Beijing, China. (corresponding author)","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100729862","display_name":"Bangliu Zhao","orcid":"https://orcid.org/0009-0008-2788-2839","observed_orcids":["https://orcid.org/0009-0008-2788-2839"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bangliu Zhao","raw_affiliation_strings":["PetroChina 2 , Petroleum and New Resources Company, Beijing, China. blzhao@petrochina.com.cn","PetroChina, Petroleum and New Resources Company, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-2788-2839","affiliations":[{"raw_affiliation_string":"PetroChina 2 , Petroleum and New Resources Company, Beijing, China. blzhao@petrochina.com.cn","institution_ids":[]},{"raw_affiliation_string":"PetroChina, Petroleum and New Resources Company, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021088424","display_name":"Shangxu Wang","orcid":"https://orcid.org/0000-0003-0265-5679","observed_orcids":["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":["China University of Petroleum 3 , State Key Laboratory of Petroleum Resources and Prospecting, Beijing, China. wangsx@cup.edu.cn","China University of Petroleum, State Key Laboratory of Petroleum Resources and Prospecting, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0265-5679","affiliations":[{"raw_affiliation_string":"China University of Petroleum 3 , State Key Laboratory of Petroleum Resources and Prospecting, Beijing, China. wangsx@cup.edu.cn","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"China University of Petroleum, State Key Laboratory of Petroleum Resources and Prospecting, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.143,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.8704142,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"88","issue":"5","first_page":"V387","last_page":"V402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9887999892234802,"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":0.9887999892234802,"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/T11757","display_name":"Seismic Waves and Analysis","score":0.0071000000461936,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.0006000000284984708,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptive-subtraction","display_name":"adaptive subtraction","score":0.6539999842643738},{"id":"https://openalex.org/keywords/seismic-data-processing","display_name":"seismic data processing","score":0.7009999752044678},{"id":"https://openalex.org/keywords/amplitude-and-phase-correction","display_name":"amplitude and phase correction","score":0.6650000214576721}],"concepts":[{"id":"https://openalex.org/C164680029","wikidata":"https://www.wikidata.org/wiki/Q1055293","display_name":"Multiple","level":2,"score":0.8754984140396118},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.5752851366996765},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.5470651984214783},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.541770875453949},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5281686186790466},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4973471462726593},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.46542567014694214},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4576706886291504},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.43210554122924805},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4117831587791443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39610356092453003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3955734968185425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2744353115558624},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.24738553166389465},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.24103200435638428},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.18461614847183228},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.10810357332229614},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1190/geo2022-0599.1","doi":"https://doi.org/10.1190/geo2022-0599.1","is_oa":false,"landing_page_url":"https://doi.org/10.1190/geo2022-0599.1","pdf_url":null,"source":{"id":"https://openalex.org/S106174089","display_name":"Geophysics","issn_l":"0016-8033","issn":["0016-8033","1942-2156"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-a","jufo-1","norway-2","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310316678","host_organization_name":"Society of Exploration Geophysicists","host_organization_lineage":["https://openalex.org/P4310316678"],"host_organization_lineage_names":["Society of Exploration Geophysicists"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geophysics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"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"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W1535820637","https://openalex.org/W1778793853","https://openalex.org/W1901129140","https://openalex.org/W1930495907","https://openalex.org/W1965348273","https://openalex.org/W1970673802","https://openalex.org/W1976884569","https://openalex.org/W1978695719","https://openalex.org/W1995756241","https://openalex.org/W1999703861","https://openalex.org/W2000088183","https://openalex.org/W2000865652","https://openalex.org/W2008857867","https://openalex.org/W2013174738","https://openalex.org/W2019961656","https://openalex.org/W2021734622","https://openalex.org/W2024012253","https://openalex.org/W2039240409","https://openalex.org/W2041812800","https://openalex.org/W2048388640","https://openalex.org/W2050854738","https://openalex.org/W2055906523","https://openalex.org/W2057062665","https://openalex.org/W2079583594","https://openalex.org/W2080760085","https://openalex.org/W2093970039","https://openalex.org/W2098916701","https://openalex.org/W2107613097","https://openalex.org/W2111226360","https://openalex.org/W2135683518","https://openalex.org/W2139984951","https://openalex.org/W2141532067","https://openalex.org/W2142518768","https://openalex.org/W2144824461","https://openalex.org/W2150476357","https://openalex.org/W2150581164","https://openalex.org/W2154222811","https://openalex.org/W2154902062","https://openalex.org/W2155132709","https://openalex.org/W2162411041","https://openalex.org/W2162964384","https://openalex.org/W2167233414","https://openalex.org/W2168917711","https://openalex.org/W2170856713","https://openalex.org/W2595113605","https://openalex.org/W2771839145","https://openalex.org/W2794829853","https://openalex.org/W2883930576","https://openalex.org/W2884585870","https://openalex.org/W2899283552","https://openalex.org/W2911085481","https://openalex.org/W2946430724","https://openalex.org/W2963697299","https://openalex.org/W2966965831","https://openalex.org/W2968181925","https://openalex.org/W2980514319","https://openalex.org/W2995916458","https://openalex.org/W3011806874","https://openalex.org/W3032837604","https://openalex.org/W3109749236","https://openalex.org/W3121528525","https://openalex.org/W3141986466","https://openalex.org/W3154575637","https://openalex.org/W3156609952","https://openalex.org/W3161445736","https://openalex.org/W3161670808","https://openalex.org/W3176116059","https://openalex.org/W3180490621","https://openalex.org/W3193146026","https://openalex.org/W3198791443","https://openalex.org/W3201062030","https://openalex.org/W3208006381","https://openalex.org/W3212348580","https://openalex.org/W3213542976","https://openalex.org/W3213920301","https://openalex.org/W4210486125","https://openalex.org/W4214598741","https://openalex.org/W4225016379","https://openalex.org/W4226169735","https://openalex.org/W4229081567","https://openalex.org/W4280541831","https://openalex.org/W4282028826","https://openalex.org/W4283689645","https://openalex.org/W4312282716"],"related_works":["https://openalex.org/W4312282716","https://openalex.org/W4415707017","https://openalex.org/W4225784827","https://openalex.org/W4410069280","https://openalex.org/W4417525777","https://openalex.org/W7123558007","https://openalex.org/W4225016379","https://openalex.org/W4319303218","https://openalex.org/W4408428912","https://openalex.org/W7222257065"],"abstract_inverted_index":{"ABSTRACT":[0],"Multiple":[1],"suppression":[2,263],"is":[3,70,142,265],"a":[4,18,26,122],"very":[5],"important":[6],"step":[7],"in":[8,84,207,233],"seismic":[9],"data":[10,38,42,249],"processing.":[11],"To":[12],"suppress":[13,257],"surface-related":[14,53,62,93,97,104,114,186,211,227,259],"multiples,":[15,54,63,94,228,260],"we":[16],"develop":[17],"self-supervised":[19,45],"deep":[20,46],"neural":[21,47],"network":[22,48],"method":[23,215,254,273,277],"based":[24,278],"on":[25,279],"local":[27,123,149,159],"wavefield":[28,124],"characteristic":[29,125],"loss":[30,127,140,153,173,177,195,283],"function":[31,128,141,178,196],"(SDNN-LWCLF).":[32],"The":[33,65,119,138],"first":[34],"and":[35,39,58,86,91,106,148,165,181,192,199,204,225,247,261,274],"second":[36],"input":[37],"the":[40,44,51,55,59,68,73,89,95,102,111,117,134,145,158,162,166,171,175,184,193,201,208,237,240,258,268,275,281],"output":[41],"of":[43,67,77,144,183,242],"(SDNN)":[49],"are":[50,82,230],"predicted":[52,90,96,185],"full-wavefield":[56],"data,":[57,220],"estimated":[60,112,163,167,209],"true":[61,92,103,113,190,210,223,226],"respectively.":[64],"role":[66],"SDNN":[69,276],"to":[71,101,110,132,188],"replace":[72],"convolutional":[74],"filter":[75],"part":[76],"adaptive":[78,271],"subtraction.":[79],"Although":[80],"there":[81],"differences":[83],"amplitudes":[85,180],"phases":[87,182],"between":[88,161],"multiples":[98,105,115,164,187,203],"correspond":[99],"kinematically":[100],"can":[107,156,255],"be":[108],"mapped":[109],"by":[116],"SDNN.":[118],"SDNN-LWCLF":[120,214,238],"uses":[121],"(LWC)":[126],"with":[129],"physical":[130],"properties":[131],"constrain":[133],"nonlinear":[135],"optimization":[136],"process.":[137],"LWC":[139,172],"composed":[143],"mean-absolute-error":[146],"(MAE)":[147],"normalized":[150],"crosscorrelation":[151],"(LNCC)":[152],"functions.":[154],"LNCC":[155,194],"measure":[157],"similarity":[160],"primaries.":[168],"By":[169],"minimizing":[170],"function,":[174],"MAE":[176,282],"corrects":[179],"their":[189],"values,":[191],"automatically":[197],"checks":[198],"reduces":[200],"leaked":[202],"residual":[205],"primaries":[206,224],"multiples.":[212],"Our":[213],"does":[216],"not":[217],"need":[218],"label":[219],"such":[221],"as":[222],"which":[229],"usually":[231],"unavailable":[232],"real-world":[234],"applications.":[235],"Therefore,":[236],"solves":[239],"problem":[241],"missing":[243],"training":[244],"data.":[245],"Synthetic":[246],"field":[248],"examples":[250],"demonstrate":[251],"that":[252],"our":[253],"well":[256],"its":[262],"effect":[264],"better":[266],"than":[267],"traditional":[269],"L1-norm":[270],"subtraction":[272],"only":[280],"function.":[284]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2023-06-12T00:00:00"}
