{"id":"https://openalex.org/W3089585697","doi":"https://doi.org/10.1190/segam2020-3426173.1","title":"Deep prior-based seismic data interpolation via multi-res U-net","display_name":"Deep prior-based seismic data interpolation via multi-res U-net","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3089585697","doi":"https://doi.org/10.1190/segam2020-3426173.1","mag":"3089585697"},"language":"en","primary_location":{"id":"doi:10.1190/segam2020-3426173.1","doi":"https://doi.org/10.1190/segam2020-3426173.1","is_oa":false,"landing_page_url":"https://doi.org/10.1190/segam2020-3426173.1","pdf_url":null,"source":{"id":"https://openalex.org/S4363604378","display_name":"Second International Meeting for Applied Geoscience & Energy","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Meeting for Applied Geoscience & Energy","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5074233749","display_name":"Fantong Kong","orcid":"https://orcid.org/0000-0003-3675-4819","observed_orcids":["https://orcid.org/0000-0003-3675-4819"]},"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":"Fantong Kong","raw_affiliation_strings":["1 China University of Petroleum","China University of Petroleum"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1 China University of Petroleum","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"China University of Petroleum","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037105611","display_name":"Francesco Picetti","orcid":"https://orcid.org/0000-0002-2162-9671","observed_orcids":["https://orcid.org/0000-0002-2162-9671"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Picetti","raw_affiliation_strings":["2 Politecnico di Milano","Politecnico di Milano"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"2 Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020147168","display_name":"Vincenzo Lipari","orcid":"https://orcid.org/0000-0002-6514-8052","observed_orcids":["https://orcid.org/0000-0002-6514-8052"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Lipari","raw_affiliation_strings":["2 Politecnico di Milano","Politecnico di Milano"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"2 Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051370303","display_name":"Paolo Bestagini","orcid":"https://orcid.org/0000-0003-0406-0222","observed_orcids":["https://orcid.org/0000-0003-0406-0222"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Bestagini","raw_affiliation_strings":["2 Politecnico di Milano","Politecnico di Milano"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"2 Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005378965","display_name":"Stefano Tubaro","orcid":"https://orcid.org/0000-0002-1990-9869","observed_orcids":["https://orcid.org/0000-0002-1990-9869"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Stefano Tubaro","raw_affiliation_strings":["2 Politecnico di Milano","Politecnico di Milano"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"2 Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.2509,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.98749362,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"3159","last_page":"3163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9926999807357788,"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":0.9926999807357788,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.0007999999797903001,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/seismic-data-interpolation","display_name":"seismic data interpolation","score":0.9900000095367432},{"id":"https://openalex.org/keywords/deep-image-prior","display_name":"deep image prior","score":0.9679999947547913},{"id":"https://openalex.org/keywords/seismic-data-preprocessing","display_name":"seismic data preprocessing","score":0.4659999907016754},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8140000104904175}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7787357568740845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6814044713973999},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6353364586830139},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6243494153022766},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6243067383766174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5607882738113403},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.48421716690063477},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.43903180956840515},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39660871028900146},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37817469239234924},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35132455825805664},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33283287286758423},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08946648240089417},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08873757719993591},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1190/segam2020-3426173.1","doi":"https://doi.org/10.1190/segam2020-3426173.1","is_oa":false,"landing_page_url":"https://doi.org/10.1190/segam2020-3426173.1","pdf_url":null,"source":{"id":"https://openalex.org/S4363604378","display_name":"Second International Meeting for Applied Geoscience & Energy","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Meeting for Applied Geoscience & Energy","raw_type":"proceedings-article"},{"id":"pmh:oai:re.public.polimi.it:11311/1201551","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/11311/1201551","pdf_url":null,"source":{"id":"https://openalex.org/S4306400312","display_name":"Virtual Community of Pathological Anatomy (University of Castilla La Mancha)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79189158","host_organization_name":"University of Castilla-La Mancha","host_organization_lineage":["https://openalex.org/I79189158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1901129140","https://openalex.org/W1976884569","https://openalex.org/W1981607562","https://openalex.org/W1997850437","https://openalex.org/W2100245965","https://openalex.org/W2124769970","https://openalex.org/W2168396269","https://openalex.org/W2463531433","https://openalex.org/W2593678390","https://openalex.org/W2752006643","https://openalex.org/W2802340267","https://openalex.org/W2890883963","https://openalex.org/W2892183045","https://openalex.org/W2894410771","https://openalex.org/W2928133111","https://openalex.org/W2964013315","https://openalex.org/W2967394486","https://openalex.org/W3121301758","https://openalex.org/W6604009900"],"related_works":["https://openalex.org/W3115624514","https://openalex.org/W4313377970","https://openalex.org/W3089863729","https://openalex.org/W7164884250","https://openalex.org/W3116337151","https://openalex.org/W4281644348","https://openalex.org/W4388145574","https://openalex.org/W4389725053","https://openalex.org/W4316135854","https://openalex.org/W4378229591"],"abstract_inverted_index":{"Interpolation":[0],"of":[1,44,56,78],"seismic":[2,11,29],"data":[3,30],"is":[4,21],"an":[5],"important":[6],"pre-processing":[7],"step":[8],"in":[9,59],"most":[10],"processing":[12],"workflows.":[13],"Through":[14],"the":[15,33,45,74,79],"deep":[16,51],"image":[17],"prior":[18,52],"paradigm,":[19],"it":[20],"possible":[22],"to":[23,53,61],"use":[24,43],"Convolutional":[25],"Neural":[26],"Networks":[27],"for":[28],"interpolation":[31,55],"without":[32],"costly":[34],"and":[35,76],"prone-to-overfitting":[36],"training":[37],"stage.":[38],"The":[39],"proposed":[40,80],"method":[41],"makes":[42],"multi-res":[46],"U-net":[47],"architecture":[48],"as":[49],"a":[50],"perform":[54],"time":[57],"slices":[58],"order":[60],"reconstruct":[62],"3D":[63],"shot":[64],"gathers.":[65],"Numerical":[66],"examples":[67],"on":[68],"different":[69],"corrupted":[70],"synthetic":[71],"datasets":[72],"demonstrate":[73],"validity":[75],"effectiveness":[77],"approach.":[81],"Presentation":[82,93,99],"Date:":[83],"Wednesday,":[84],"October":[85],"14,":[86],"2020":[87],"Session":[88],"Start":[89],"Time:":[90,94],"8:30":[91],"AM":[92,96],"10:35":[95],"Location:":[97],"360D":[98],"Type:":[100],"Oral":[101]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2020-10-08T00:00:00"}