{"id":"https://openalex.org/W2608653868","doi":"https://doi.org/10.1109/tgrs.2017.2692388","title":"Hybrid Global Stochastic and Bayesian Linearized Acoustic Seismic Inversion Methodology","display_name":"Hybrid Global Stochastic and Bayesian Linearized Acoustic Seismic Inversion Methodology","publication_year":2017,"publication_date":"2017-04-28","ids":{"openalex":"https://openalex.org/W2608653868","doi":"https://doi.org/10.1109/tgrs.2017.2692388","mag":"2608653868"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2017.2692388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2692388","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/A5037040676","display_name":"Fernando Bordignon","orcid":"https://orcid.org/0000-0001-5205-8042"},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fernando Luis Bordignon","raw_affiliation_strings":["Department of Informatics and Statistics, Federal University of Santa Catarina, Florianopolis, Brazil","[Department of Informatics and Statistics - Federal University of Santa Catarina - Florian\u00f3polis, Brazil]"],"raw_orcid":"https://orcid.org/0000-0001-5205-8042","affiliations":[{"raw_affiliation_string":"Department of Informatics and Statistics, Federal University of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]},{"raw_affiliation_string":"[Department of Informatics and Statistics - Federal University of Santa Catarina - Florian\u00f3polis, Brazil]","institution_ids":["https://openalex.org/I4104125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056979330","display_name":"Leandro Passos de Figueiredo","orcid":"https://orcid.org/0000-0002-3694-3938"},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Leandro Passos de Figueiredo","raw_affiliation_strings":["Department of Physics, Federal University of Santa Catarina, Florianopolis, Brazil","Department of Physics, Federal University of Santa Catarina, Florian\u00f3polis, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics, Federal University of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]},{"raw_affiliation_string":"Department of Physics, Federal University of Santa Catarina, Florian\u00f3polis, Brazil","institution_ids":["https://openalex.org/I4104125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041954324","display_name":"Leonardo Azevedo","orcid":"https://orcid.org/0000-0002-0677-079X"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Leonardo Azevedo","raw_affiliation_strings":["CERENA/IST, University of Lisbon, Lisbon, Portugal","[CERENA/IST, University of Lisbon, Lisbon, Portugal]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CERENA/IST, University of Lisbon, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103"]},{"raw_affiliation_string":"[CERENA/IST, University of Lisbon, Lisbon, Portugal]","institution_ids":["https://openalex.org/I141596103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100659227","display_name":"A. Soares","orcid":"https://orcid.org/0000-0001-5232-2376"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Amilcar Soares","raw_affiliation_strings":["CERENA/IST, University of Lisbon, Lisbon, Portugal","[CERENA/IST, University of Lisbon, Lisbon, Portugal]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CERENA/IST, University of Lisbon, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103"]},{"raw_affiliation_string":"[CERENA/IST, University of Lisbon, Lisbon, Portugal]","institution_ids":["https://openalex.org/I141596103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090517396","display_name":"Mauro Roisenberg","orcid":"https://orcid.org/0000-0001-9707-0360"},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Mauro Roisenberg","raw_affiliation_strings":["Department of Informatics and Statistics, Federal University of Santa Catarina, Florianopolis, Brazil","[Department of Informatics and Statistics - Federal University of Santa Catarina - Florian\u00f3polis, Brazil]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics and Statistics, Federal University of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]},{"raw_affiliation_string":"[Department of Informatics and Statistics - Federal University of Santa Catarina - Florian\u00f3polis, Brazil]","institution_ids":["https://openalex.org/I4104125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110668623","display_name":"Guenther Schwedersky Neto","orcid":"https://orcid.org/0000-0002-3835-5179"},"institutions":[{"id":"https://openalex.org/I32393484","display_name":"Petrobras (Brazil)","ror":"https://ror.org/0235kyq22","country_code":"BR","type":"company","lineage":["https://openalex.org/I32393484"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Guenther Schwedersky Neto","raw_affiliation_strings":["E&P, PETROBRAS, Rio de Janeiro, Brazil","[E&P, PETROBRAS, Rio de Janeiro, Brazil]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"E&P, PETROBRAS, Rio de Janeiro, Brazil","institution_ids":["https://openalex.org/I32393484"]},{"raw_affiliation_string":"[E&P, PETROBRAS, Rio de Janeiro, Brazil]","institution_ids":["https://openalex.org/I32393484"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6833,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.68363086,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"55","issue":"8","first_page":"4457","last_page":"4464"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9997000098228455,"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/T10635","display_name":"Hydraulic Fracturing and Reservoir Analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/seismic-inversion","display_name":"Seismic inversion","score":0.8064979314804077},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.7709143161773682},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6063311696052551},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5908704996109009},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.5859611630439758},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5188337564468384},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5016508102416992},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.49756959080696106},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4562758505344391},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.421034038066864},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.41788241267204285},{"id":"https://openalex.org/keywords/inverse-transform-sampling","display_name":"Inverse transform sampling","score":0.4178692102432251},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4154205322265625},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3605501651763916},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2209482491016388},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.19799011945724487},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12812134623527527},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12228921055793762},{"id":"https://openalex.org/keywords/surface-wave","display_name":"Surface wave","score":0.07722276449203491}],"concepts":[{"id":"https://openalex.org/C39267094","wikidata":"https://www.wikidata.org/wiki/Q7446968","display_name":"Seismic inversion","level":3,"score":0.8064979314804077},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7709143161773682},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6063311696052551},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5908704996109009},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.5859611630439758},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5188337564468384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5016508102416992},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.49756959080696106},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4562758505344391},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.421034038066864},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.41788241267204285},{"id":"https://openalex.org/C143606050","wikidata":"https://www.wikidata.org/wiki/Q1377019","display_name":"Inverse transform sampling","level":3,"score":0.4178692102432251},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4154205322265625},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3605501651763916},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2209482491016388},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.19799011945724487},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12812134623527527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12228921055793762},{"id":"https://openalex.org/C84174578","wikidata":"https://www.wikidata.org/wiki/Q889796","display_name":"Surface wave","level":2,"score":0.07722276449203491},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C77928131","wikidata":"https://www.wikidata.org/wiki/Q193343","display_name":"Tectonics","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2017.2692388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2692388","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":"Industry, innovation and infrastructure","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2183666291","display_name":null,"funder_award_id":"4041/15-1","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"}],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322468","display_name":"Petrobras","ror":"https://ror.org/0235kyq22"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W59925474","https://openalex.org/W240582380","https://openalex.org/W1512208174","https://openalex.org/W1513885533","https://openalex.org/W1875418078","https://openalex.org/W1981018513","https://openalex.org/W1983647203","https://openalex.org/W2008933362","https://openalex.org/W2027355076","https://openalex.org/W2027381054","https://openalex.org/W2038648432","https://openalex.org/W2060119783","https://openalex.org/W2079728072","https://openalex.org/W2082667383","https://openalex.org/W2088547815","https://openalex.org/W2111244470","https://openalex.org/W2168225771","https://openalex.org/W2171680516","https://openalex.org/W2328836344","https://openalex.org/W2503924009","https://openalex.org/W3145074154"],"related_works":["https://openalex.org/W1993696404","https://openalex.org/W2166809960","https://openalex.org/W4384644066","https://openalex.org/W3174868297","https://openalex.org/W2136359851","https://openalex.org/W4206189322","https://openalex.org/W2347721273","https://openalex.org/W4285150540","https://openalex.org/W2611645596","https://openalex.org/W4385433491"],"abstract_inverted_index":{"Seismic":[0],"inversion":[1,33,45,93,106,119],"is":[2,55,73,108,145],"an":[3,102,111],"important":[4],"technique":[5,54],"for":[6],"reservoir":[7],"modeling":[8,171],"and":[9,38,46,167],"characterization":[10],"due":[11],"to":[12,57,127],"its":[13],"potential":[14],"in":[15,67,147],"inferring":[16],"the":[17,21,29,36,52,59,64,80,100,129,132,160,163,168,172,175],"spatial":[18],"distribution":[19],"of":[20,25,28,98,131,138,162,170,174],"subsurface":[22],"elastic":[23],"properties":[24],"interest.":[26],"Two":[27],"most":[30],"common":[31],"seismic":[32,44,49,92,105],"methodologies":[34],"within":[35],"oil":[37],"gas":[39],"industry":[40],"are":[41],"iterative":[42,103],"geostatistical":[43,104],"Bayesian":[47,81,118],"linearized":[48,82],"inversion.":[50],"Although":[51],"first":[53],"able":[56],"explore":[58],"uncertainty":[60,130,173],"space":[61],"related":[62],"with":[63,79,153],"inverse":[65,134,165,177],"solution":[66,135],"a":[68,89,117,124],"more":[69],"comprehensive":[70],"way,":[71],"it":[72],"also":[74],"very":[75],"computationally":[76],"expensive":[77],"compared":[78],"approach.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87,122],"introduce":[88],"novel":[90],"hybrid":[91,164],"procedure":[94],"that":[95],"takes":[96],"advantage":[97],"both":[99],"frameworks:":[101],"methodology":[107,166],"started":[109],"from":[110],"initial":[112],"guess":[113],"model":[114,128],"provided":[115],"by":[116,136],"solution.":[120,178],"Also,":[121],"propose":[123],"new":[125],"approach":[126,144],"retrieved":[133,176],"means":[137],"kernel":[139],"density":[140],"estimation.":[141],"The":[142,157],"proposed":[143],"implemented":[146],"two":[148],"different":[149,154],"real":[150],"data":[151],"sets":[152],"signal-to-noise":[155],"ratios.":[156],"results":[158],"show":[159],"robustness":[161],"usefulness":[169]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2019,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}