{"id":"https://openalex.org/W2952537309","doi":"https://doi.org/10.1145/3325917.3325926","title":"Automatic Seismic Salt Interpretation with Deep Convolutional Neural Networks","display_name":"Automatic Seismic Salt Interpretation with Deep Convolutional Neural Networks","publication_year":2019,"publication_date":"2019-04-06","ids":{"openalex":"https://openalex.org/W2952537309","doi":"https://doi.org/10.1145/3325917.3325926","mag":"2952537309"},"language":"en","primary_location":{"id":"doi:10.1145/3325917.3325926","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3325917.3325926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Information System and Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1812.01101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004287159","display_name":"Yu Zeng","orcid":"https://orcid.org/0009-0004-5335-5873"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yu Zeng","raw_affiliation_strings":["Houston TX"],"affiliations":[{"raw_affiliation_string":"Houston TX","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079583836","display_name":"Kebei Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kebei Jiang","raw_affiliation_strings":["Houston TX"],"affiliations":[{"raw_affiliation_string":"Houston TX","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100756174","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0001-9089-8587"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["Houston TX"],"affiliations":[{"raw_affiliation_string":"Houston TX","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004287159"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.7749,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.98404526,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"16","last_page":"20"},"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/T11757","display_name":"Seismic Waves and Analysis","score":0.9987000226974487,"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":0.9968000054359436,"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/softmax-function","display_name":"Softmax function","score":0.8446195125579834},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7761871814727783},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7424140572547913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6797369718551636},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5661380290985107},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5579880475997925},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48318353295326233},{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.46826890110969543},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4660571217536926},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.44369858503341675},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32615238428115845},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24876797199249268}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8446195125579834},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7761871814727783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7424140572547913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6797369718551636},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5661380290985107},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5579880475997925},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48318353295326233},{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.46826890110969543},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4660571217536926},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44369858503341675},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32615238428115845},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24876797199249268},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3325917.3325926","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3325917.3325926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Information System and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1812.01101","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.01101","pdf_url":"https://arxiv.org/pdf/1812.01101","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1812.01101","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.01101","pdf_url":"https://arxiv.org/pdf/1812.01101","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1677182931","https://openalex.org/W1863660263","https://openalex.org/W1901129140","https://openalex.org/W2110039350","https://openalex.org/W2176412452","https://openalex.org/W2194775991","https://openalex.org/W2557283755","https://openalex.org/W2607662938","https://openalex.org/W2795587607","https://openalex.org/W2810812775","https://openalex.org/W2888931056","https://openalex.org/W2889867094","https://openalex.org/W2890343362","https://openalex.org/W2890633181","https://openalex.org/W2892654670","https://openalex.org/W2963285578","https://openalex.org/W2963446085"],"related_works":["https://openalex.org/W2899027234","https://openalex.org/W4323060069","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W4292054264","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W4287869072","https://openalex.org/W3170224572","https://openalex.org/W3005627584"],"abstract_inverted_index":{"One":[0],"of":[1,34,45,56,75,101,184],"the":[2,13,26,73,82,93,99,115,130,137,151,164,181],"most":[3],"crucial":[4],"tasks":[5],"in":[6,68,92,174],"seismic":[7],"reflection":[8],"imaging":[9],"is":[10,21,80],"to":[11,61,120,148],"identify":[12],"salt":[14,69,122,166,171],"bodies":[15],"with":[16,65,114,124,176],"high":[17,125],"precision.":[18,126],"Traditionally,":[19],"this":[20,97],"accomplished":[22],"by":[23,106],"visually":[24],"picking":[25],"salt/sediment":[27],"boundaries,":[28],"which":[29],"requires":[30],"a":[31,53,89,108],"great":[32,54,182],"amount":[33],"manual":[35],"work":[36],"and":[37,49,86,141,168],"may":[38],"introduce":[39],"systematic":[40],"bias.":[41],"With":[42],"recent":[43],"progress":[44],"deep":[46],"learning":[47,117],"algorithm":[48],"growing":[50],"computational":[51],"power,":[52],"deal":[55],"efforts":[57],"has":[58,87],"been":[59,88,146],"made":[60],"replace":[62],"human":[63],"effort":[64],"machine":[66],"power":[67],"body":[70,123,167],"interpretation.":[71],"Currently,":[72],"method":[74],"Convolutional":[76],"neural":[77],"networks":[78],"(CNN)":[79],"revolutionizing":[81],"computer":[83],"vision":[84],"field":[85],"hot":[90],"topic":[91],"image":[94],"analysis.":[95],"In":[96],"paper,":[98],"benefits":[100],"CNN-based":[102],"classification":[103],"are":[104],"demonstrated":[105],"using":[107,157],"state-of-art":[109],"network":[110],"structure":[111],"U-Net,":[112],"along":[113],"residual":[116],"framework":[118],"ResNet,":[119],"delineate":[121],"Network":[127],"adjustments,":[128],"including":[129],"Exponential":[131],"Linear":[132],"Units":[133],"(ELU)":[134],"activation":[135],"function,":[136,140],"Lovasz-Softmax":[138],"loss":[139],"stratified":[142],"K-fold":[143],"cross-validation,":[144],"have":[145],"deployed":[147],"further":[149],"improve":[150],"prediction":[152],"accuracy.":[153],"The":[154],"preliminary":[155],"result":[156],"SEG-SEAM":[158],"data":[159],"shows":[160],"good":[161],"agreement":[162],"between":[163],"predicted":[165],"manually":[169],"interpreted":[170],"body,":[172],"especially":[173],"areas":[175],"weak":[177],"reflections.":[178],"This":[179],"indicates":[180],"potential":[183],"applying":[185],"CNN":[186],"for":[187],"salt-related":[188],"interpretations.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":7}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-06-27T00:00:00"}
