{"id":"https://openalex.org/W4409985973","doi":"https://doi.org/10.1109/tgrs.2025.3565601","title":"Robust Low-Rank Reconstruction of Seismic Data","display_name":"Robust Low-Rank Reconstruction of Seismic Data","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409985973","doi":"https://doi.org/10.1109/tgrs.2025.3565601"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3565601","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3565601","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/A5056872955","display_name":"Weilin Huang","orcid":"https://orcid.org/0000-0003-1692-4868"},"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":"Weilin Huang","raw_affiliation_strings":["Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1692-4868","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101991648","display_name":"Jieli Li","orcid":"https://orcid.org/0000-0002-6700-6381"},"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":"Jieli Li","raw_affiliation_strings":["Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6700-6381","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100771722","display_name":"Jidong Li","orcid":"https://orcid.org/0000-0003-0503-5467"},"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":"Jidong Li","raw_affiliation_strings":["Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668789","display_name":"Weijie Liu","orcid":"https://orcid.org/0000-0003-3653-3637"},"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":"Weijie Liu","raw_affiliation_strings":["Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063081130","display_name":"Faliang Wang","orcid":"https://orcid.org/0000-0002-8603-736X"},"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":"Faliang Wang","raw_affiliation_strings":["Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10726817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9968000054359436,"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":0.9968000054359436,"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/T11801","display_name":"Reservoir Engineering and Simulation Methods","score":0.984000027179718,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9793999791145325,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.5274168252944946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46765416860580444},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3923352360725403}],"concepts":[{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.5274168252944946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46765416860580444},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3923352360725403}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3565601","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3565601","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":[{"display_name":"Climate action","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G6559739997","display_name":null,"funder_award_id":"2022056","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"},{"id":"https://openalex.org/G6906885450","display_name":null,"funder_award_id":"42374133","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"},{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1822012234","https://openalex.org/W1910501430","https://openalex.org/W1981607562","https://openalex.org/W1990498189","https://openalex.org/W2013913026","https://openalex.org/W2015207482","https://openalex.org/W2022575621","https://openalex.org/W2030144655","https://openalex.org/W2034555868","https://openalex.org/W2043147867","https://openalex.org/W2048023990","https://openalex.org/W2050551672","https://openalex.org/W2076513090","https://openalex.org/W2081576211","https://openalex.org/W2086288874","https://openalex.org/W2090319605","https://openalex.org/W2113740359","https://openalex.org/W2133015712","https://openalex.org/W2139663179","https://openalex.org/W2141953966","https://openalex.org/W2163654892","https://openalex.org/W2165412225","https://openalex.org/W2328740995","https://openalex.org/W2403089413","https://openalex.org/W2409136587","https://openalex.org/W2468203014","https://openalex.org/W2518468762","https://openalex.org/W2564709795","https://openalex.org/W2608562242","https://openalex.org/W2614683497","https://openalex.org/W2744992965","https://openalex.org/W2776535170","https://openalex.org/W2791941428","https://openalex.org/W2913170515","https://openalex.org/W2970155362","https://openalex.org/W2970679026","https://openalex.org/W2975778935","https://openalex.org/W2989851576","https://openalex.org/W2999119012","https://openalex.org/W3008461831","https://openalex.org/W3024236808","https://openalex.org/W3087783885","https://openalex.org/W3088270202","https://openalex.org/W3091383239","https://openalex.org/W3159622829","https://openalex.org/W3198159016","https://openalex.org/W3198733619","https://openalex.org/W3210927864","https://openalex.org/W4285214622","https://openalex.org/W4285288115","https://openalex.org/W4292266653","https://openalex.org/W4296672479","https://openalex.org/W4307140417","https://openalex.org/W4307280057","https://openalex.org/W4313333247","https://openalex.org/W4318832435","https://openalex.org/W4321502853","https://openalex.org/W4378230912","https://openalex.org/W4388948718"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2324615561","https://openalex.org/W2086120259","https://openalex.org/W2390279801","https://openalex.org/W2245170124","https://openalex.org/W2076393078","https://openalex.org/W4391913857","https://openalex.org/W2358668433"],"abstract_inverted_index":{"Seismic":[0],"reconstruction":[1,41,72,142],"is":[2,85,173],"an":[3,56],"essential":[4],"pre-processing":[5],"step":[6],"aimed":[7],"at":[8],"recovering":[9],"missing":[10,62,96,136],"traces":[11,63,97],"and":[12,61,95,121,131,143,168,172,179,198,222,227,235],"suppressing":[13],"incoherent":[14,88],"noise.":[15,237],"The":[16],"low-rank":[17],"(LR)":[18],"method":[19,36,197,217],"has":[20],"been":[21],"demonstrated":[22],"to":[23,65,109,116,138,175,233],"be":[24,53,74],"one":[25],"of":[26,135,156,204],"the":[27,38,67,163,176,180,213],"most":[28],"effective":[29],"methods":[30],"for":[31,193],"seismic":[32,39,50,71,113,125,164,170,206,225],"data":[33,40,126,171,207,226],"reconstruction.":[34],"This":[35],"considers":[37],"as":[42,55,99,102],"a":[43,77,92,153,189,229],"matrix":[44,68],"completion":[45],"problem,":[46],"assuming":[47],"that":[48,212],"noise-free":[49],"signals":[51,165],"can":[52,73,160,218],"represented":[54],"LR":[57,82,141,157,196,216],"matrix.":[58],"Incoherent":[59],"noise":[60,89,130,178,231],"contribute":[64],"increasing":[66],"rank.":[69],"Consequently,":[70],"accomplished":[75],"by":[76,184],"rank-reduction":[78],"operation.":[79],"For":[80],"successful":[81],"reconstruction,":[83,158],"it":[84,200],"ideal":[86],"if":[87],"closely":[90],"follows":[91],"Gaussian":[93],"distribution":[94],"are":[98,107],"randomly":[100],"distributed":[101],"possible.":[103],"However,":[104],"these":[105],"conditions":[106],"challenging":[108],"meet":[110],"in":[111,140],"field":[112],"acquisition":[114],"due":[115],"dependencies":[117],"on":[118],"operational":[119],"equipment":[120],"environmental":[122],"factors.":[123],"Field":[124],"often":[127],"contain":[128],"erratic":[129,177,236],"exhibit":[132],"regular":[133,185],"patterns":[134],"traces,leading":[137],"instability":[139],"limiting":[144],"its":[145],"practical":[146],"application.":[147],"In":[148],"this":[149,194],"study,":[150],"we":[151],"propose":[152],"robust":[154,195,215],"version":[155],"which":[159],"accurately":[161],"estimate":[162],"from":[166],"noisy":[167],"undersampled":[169,224],"insensitive":[174],"spatial":[181],"aliasing":[182],"caused":[183],"undersampling.":[186],"We":[187],"present":[188],"detailed":[190],"algorithmic":[191],"framework":[192],"validate":[199],"through":[201],"comprehensive":[202],"analyses":[203],"various":[205],"examples.":[208],"Our":[209],"results":[210],"demonstrate":[211],"proposed":[214],"reconstruct":[219],"both":[220],"regularly":[221],"irregularly":[223],"exhibits":[228],"good":[230],"immunity":[232],"strong":[234]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
