{"id":"https://openalex.org/W2939587785","doi":"https://doi.org/10.1190/int-2018-0235.1","title":"SaltSeg: Automatic 3D salt segmentation using a deep convolutional neural network","display_name":"SaltSeg: Automatic 3D salt segmentation using a deep convolutional neural network","publication_year":2019,"publication_date":"2019-04-08","ids":{"openalex":"https://openalex.org/W2939587785","doi":"https://doi.org/10.1190/int-2018-0235.1","mag":"2939587785"},"language":"en","primary_location":{"id":"doi:10.1190/int-2018-0235.1","doi":"https://doi.org/10.1190/int-2018-0235.1","is_oa":false,"landing_page_url":"https://doi.org/10.1190/int-2018-0235.1","pdf_url":null,"source":{"id":"https://openalex.org/S4210239846","display_name":"Interpretation","issn_l":"2324-8858","issn":["2324-8858","2324-8866"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-1","ki-jl-1","norway-1","poland-40","russia-white-list-2"],"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":"Interpretation","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/A5102022576","display_name":"Yunzhi Shi","orcid":"https://orcid.org/0000-0001-7941-0499","observed_orcids":["https://orcid.org/0000-0001-7941-0499","https://orcid.org/0009-0005-2758-0898"]},"institutions":[{"id":"https://openalex.org/I4403928371","display_name":"Bureau of Economic Geology","ror":"https://ror.org/034bxn811","country_code":"US","type":"facility","lineage":["https://openalex.org/I4403928371","https://openalex.org/I86519309"]},{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunzhi Shi","raw_affiliation_strings":["The University of Texas at Austin, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, Box X, Austin, Texas 78713-8924, USA.(corresponding author); "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Austin, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, Box X, Austin, Texas 78713-8924, USA.(corresponding author); ","institution_ids":["https://openalex.org/I4403928371","https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058640298","display_name":"Xinming Wu","orcid":"https://orcid.org/0000-0002-4910-8253","observed_orcids":["https://orcid.org/0000-0002-4910-8253"]},"institutions":[{"id":"https://openalex.org/I4403928371","display_name":"Bureau of Economic Geology","ror":"https://ror.org/034bxn811","country_code":"US","type":"facility","lineage":["https://openalex.org/I4403928371","https://openalex.org/I86519309"]},{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinming Wu","raw_affiliation_strings":["The University of Texas at Austin, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, Box X, Austin, Texas 78713-8924, USA.(corresponding author); "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Austin, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, Box X, Austin, Texas 78713-8924, USA.(corresponding author); ","institution_ids":["https://openalex.org/I4403928371","https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005237932","display_name":"Sergey B. Fomel","orcid":"https://orcid.org/0000-0002-9024-5137","observed_orcids":["https://orcid.org/0000-0002-9024-5137"]},"institutions":[{"id":"https://openalex.org/I4403928371","display_name":"Bureau of Economic Geology","ror":"https://ror.org/034bxn811","country_code":"US","type":"facility","lineage":["https://openalex.org/I4403928371","https://openalex.org/I86519309"]},{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergey Fomel","raw_affiliation_strings":["The University of Texas at Austin, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, Box X, Austin, Texas 78713-8924, USA.(corresponding author); "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Austin, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, Box X, Austin, Texas 78713-8924, USA.(corresponding author); ","institution_ids":["https://openalex.org/I4403928371","https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.947,"has_fulltext":false,"cited_by_count":195,"citation_normalized_percentile":{"value":0.99784715,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"7","issue":"3","first_page":"SE113","last_page":"SE122"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.7792999744415283,"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":0.7792999744415283,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1386999934911728,"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/T13193","display_name":"Geological Studies and Exploration","score":0.010499999858438969,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"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/salt-tectonics","display_name":"salt tectonics","score":0.8259999752044678},{"id":"https://openalex.org/keywords/3d-seismic-interpretation","display_name":"3D seismic interpretation","score":0.8109999895095825},{"id":"https://openalex.org/keywords/encoder-decoder-architecture","display_name":"encoder-decoder architecture","score":0.6949999928474426},{"id":"https://openalex.org/keywords/deep-convolutional-neural-networks","display_name":"deep convolutional neural networks","score":0.7080000042915344},{"id":"https://openalex.org/keywords/velocity-model-building","display_name":"velocity model building","score":0.6029999852180481},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.6449999809265137}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7623165845870972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.706186830997467},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7021189332008362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6868327856063843},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6303847432136536},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5573486685752869},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5378363132476807},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5323296785354614},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5159919261932373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5104528665542603},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5055935382843018},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4848078787326813},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4418722093105316},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42812061309814453},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38918963074684143},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1056494414806366},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1190/int-2018-0235.1","doi":"https://doi.org/10.1190/int-2018-0235.1","is_oa":false,"landing_page_url":"https://doi.org/10.1190/int-2018-0235.1","pdf_url":null,"source":{"id":"https://openalex.org/S4210239846","display_name":"Interpretation","issn_l":"2324-8858","issn":["2324-8858","2324-8866"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-1","ki-jl-1","norway-1","poland-40","russia-white-list-2"],"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":"Interpretation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W119973362","https://openalex.org/W639708223","https://openalex.org/W845365781","https://openalex.org/W1487746374","https://openalex.org/W1522301498","https://openalex.org/W1536680647","https://openalex.org/W1677182931","https://openalex.org/W1745334888","https://openalex.org/W1832973934","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1904365287","https://openalex.org/W1910657905","https://openalex.org/W2103554575","https://openalex.org/W2112751836","https://openalex.org/W2162931300","https://openalex.org/W2237747187","https://openalex.org/W2304648132","https://openalex.org/W2504830112","https://openalex.org/W2521278198","https://openalex.org/W2592421213","https://openalex.org/W2592517375","https://openalex.org/W2601307685","https://openalex.org/W2613056341","https://openalex.org/W2619324788","https://openalex.org/W2783909991","https://openalex.org/W2810470036","https://openalex.org/W2886381392","https://openalex.org/W2891111066","https://openalex.org/W2891255706","https://openalex.org/W2892266157","https://openalex.org/W2895663205","https://openalex.org/W2911424749","https://openalex.org/W2949117887","https://openalex.org/W2963150697","https://openalex.org/W4362597616","https://openalex.org/W4389076767"],"related_works":["https://openalex.org/W4393073990","https://openalex.org/W3009330615","https://openalex.org/W4285207230","https://openalex.org/W2891932361","https://openalex.org/W4367317938","https://openalex.org/W2967277092","https://openalex.org/W2968989248","https://openalex.org/W2904391632","https://openalex.org/W4291717940","https://openalex.org/W4221161296"],"abstract_inverted_index":{"Salt":[0],"boundary":[1],"interpretation":[2],"is":[3,127],"important":[4],"for":[5,15,145],"the":[6,32,56,86,96,105,113,118,136,151,159],"understanding":[7],"of":[8,21,83,129,161],"salt":[9,23,27,133],"tectonics":[10],"and":[11,25,38,111],"velocity":[12,97],"model":[13,98,106,152],"building":[14],"seismic":[16,138],"migration.":[17],"Conventional":[18],"methods":[19],"consist":[20],"computing":[22],"attributes":[24],"extracting":[26],"boundaries.":[28],"We":[29,103,148],"have":[30],"formulated":[31],"problem":[33],"as":[34,99],"3D":[35,70,137],"image":[36,139],"segmentation":[37],"evaluated":[39],"an":[40,51],"efficient":[41],"approach":[42],"based":[43],"on":[44,107,153],"deep":[45,163],"convolutional":[46],"neural":[47],"networks":[48],"(CNNs)":[49],"with":[50,117,140],"encoder-decoder":[52],"architecture.":[53],"To":[54],"train":[55],"model,":[57],"we":[58],"design":[59],"a":[60,80,154],"data":[61,72,76,109,168],"generator":[62],"that":[63,124],"extracts":[64],"randomly":[65],"positioned":[66],"subvolumes":[67,84],"from":[68,135],"large-scale":[69],"training":[71],"set":[73],"followed":[74],"by":[75,94],"augmentation,":[77],"then":[78],"feed":[79],"large":[81],"number":[82],"into":[85],"network":[87],"while":[88],"using":[89],"salt/nonsalt":[90],"binary":[91],"labels":[92],"generated":[93],"thresholding":[95],"ground":[100,119],"truth":[101],"labels.":[102],"test":[104,115,150],"validation":[108],"sets":[110],"compare":[112],"blind":[114],"predictions":[116],"truth.":[120],"Our":[121],"results":[122],"indicate":[123,158],"our":[125],"method":[126,165],"capable":[128],"automatically":[130],"capturing":[131],"subtle":[132],"features":[134],"less":[141],"or":[142],"no":[143],"need":[144],"manual":[146],"input.":[147],"further":[149],"field":[155],"example":[156],"to":[157],"generalization":[160],"this":[162],"CNN":[164],"across":[166],"different":[167],"sets.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":53},{"year":2021,"cited_by_count":31},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":7}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2019-04-25T00:00:00"}