{"id":"https://openalex.org/W4396239544","doi":"https://doi.org/10.1109/tgrs.2024.3394592","title":"Salt3DNet: A Self-Supervised Learning Framework for 3-D Salt Segmentation","display_name":"Salt3DNet: A Self-Supervised Learning Framework for 3-D Salt Segmentation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396239544","doi":"https://doi.org/10.1109/tgrs.2024.3394592"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3394592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3394592","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/A5086250883","display_name":"Liuqing Yang","orcid":"https://orcid.org/0000-0002-4064-501X"},"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":true,"raw_author_name":"Liuqing Yang","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the National Engineering Laboratory of Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the National Engineering Laboratory of Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005237932","display_name":"Sergey Fomel","orcid":"https://orcid.org/0000-0002-9024-5137"},"institutions":[{"id":"https://openalex.org/I1288783943","display_name":"Bureau of Economic Analysis","ror":"https://ror.org/03b17a012","country_code":"US","type":"government","lineage":["https://openalex.org/I1288783943","https://openalex.org/I1343035065"]},{"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":["Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I1288783943","https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032285717","display_name":"Shoudong Wang","orcid":"https://orcid.org/0000-0002-2881-831X"},"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":"Shoudong Wang","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the National Engineering Laboratory of Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the National Engineering Laboratory of Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422680","display_name":"Xiaohong Chen","orcid":"https://orcid.org/0000-0003-0578-6009"},"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":"Xiaohong Chen","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting and the National Engineering Laboratory of Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting and the National Engineering Laboratory of Offshore Oil Exploration, China University of Petroleum (Beijing), Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059397010","display_name":"Omar M. Saad","orcid":null},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Omar M. Saad","raw_affiliation_strings":["Division of Physical Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Division of Physical Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019972279","display_name":"Yangkang Chen","orcid":"https://orcid.org/0000-0001-6429-4261"},"institutions":[{"id":"https://openalex.org/I1288783943","display_name":"Bureau of Economic Analysis","ror":"https://ror.org/03b17a012","country_code":"US","type":"government","lineage":["https://openalex.org/I1288783943","https://openalex.org/I1343035065"]},{"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":"Yangkang Chen","raw_affiliation_strings":["Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I1288783943","https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5086250883"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":1.6609,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82265879,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9138000011444092,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9138000011444092,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11609","display_name":"Geophysical Methods and Applications","score":0.9009000062942505,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6162917017936707},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6136438250541687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.562981903553009},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5174204111099243},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3781646192073822},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3389075994491577},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3319008946418762},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32958492636680603},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21775341033935547}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6162917017936707},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6136438250541687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.562981903553009},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5174204111099243},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3781646192073822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3389075994491577},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3319008946418762},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32958492636680603},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21775341033935547}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3394592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3394592","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":[],"awards":[{"id":"https://openalex.org/G1797282941","display_name":null,"funder_award_id":"2019YFC0312003","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4784224183","display_name":null,"funder_award_id":"ZLZX2020-03","funder_id":"https://openalex.org/F4320321570","funder_display_name":"China National Petroleum Corporation"}],"funders":[{"id":"https://openalex.org/F4320321570","display_name":"China National Petroleum Corporation","ror":"https://ror.org/05269d038"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W119973362","https://openalex.org/W1832973934","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1964416421","https://openalex.org/W2045709848","https://openalex.org/W2109401225","https://openalex.org/W2115957863","https://openalex.org/W2156387975","https://openalex.org/W2237747187","https://openalex.org/W2316891541","https://openalex.org/W2325865858","https://openalex.org/W2395234887","https://openalex.org/W2464708700","https://openalex.org/W2522025240","https://openalex.org/W2591948270","https://openalex.org/W2592517375","https://openalex.org/W2619324788","https://openalex.org/W2622263826","https://openalex.org/W2915004230","https://openalex.org/W2922509574","https://openalex.org/W2934427271","https://openalex.org/W2939587785","https://openalex.org/W2945294778","https://openalex.org/W2963446712","https://openalex.org/W2963775778","https://openalex.org/W2963941635","https://openalex.org/W3005680577","https://openalex.org/W3011245630","https://openalex.org/W3023371261","https://openalex.org/W3047855151","https://openalex.org/W3090413222","https://openalex.org/W3091672556","https://openalex.org/W3099006605","https://openalex.org/W3106842161","https://openalex.org/W3128002121","https://openalex.org/W3134652006","https://openalex.org/W3186076733","https://openalex.org/W3193059835","https://openalex.org/W3199334415","https://openalex.org/W3204731106","https://openalex.org/W4200223529","https://openalex.org/W4206002133","https://openalex.org/W4214909396","https://openalex.org/W4220742635","https://openalex.org/W4224040441","https://openalex.org/W4280493540","https://openalex.org/W4282941865","https://openalex.org/W4285207230","https://openalex.org/W4288407605","https://openalex.org/W4313524854","https://openalex.org/W4313534826","https://openalex.org/W4367848668","https://openalex.org/W4385245566","https://openalex.org/W6638667902","https://openalex.org/W6682889407","https://openalex.org/W6739622702","https://openalex.org/W6739901393","https://openalex.org/W6774314701","https://openalex.org/W6791742336"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W4379231730","https://openalex.org/W1987967678","https://openalex.org/W4389858081","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2059707233","https://openalex.org/W2085738998","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Salt":[0],"body":[1,21,60],"segmentation":[2,22,209,245],"is":[3,30,64,235],"a":[4,34,50,94,121,181,189],"critical":[5],"part":[6],"of":[7,37,72,132,154,162,192],"structural":[8],"interpretation":[9],"and":[10,12,70,90,116,128,138,171,219],"oil":[11],"gas":[13],"exploration":[14],"for":[15,43,57,195],"subsalt":[16],"reservoirs.":[17],"Existing":[18],"automatic":[19],"salt":[20,45,59,118,208,244],"techniques":[23],"mostly":[24],"use":[25,80],"supervised":[26],"learning":[27,52,96,124],"strategies.":[28],"It":[29],"challenging":[31],"to":[32,86,98,111,175,179,198,237],"generate":[33],"large":[35],"number":[36,191],"labels":[38],"by":[39],"manual":[40],"labeling,":[41],"especially":[42],"3-D":[44,58,113,134,212],"bodies.":[46],"Here,":[47],"we":[48,79,107],"propose":[49],"self-supervised":[51],"(SSL)":[53],"framework":[54,63],"called":[55],"Salt3DNet,":[56],"segmentation.":[61],"This":[62],"divided":[65],"into":[66],"two":[67,109],"stages:":[68],"pretraining":[69,77,169],"fine-tuning":[71,105],"downstream":[73],"tasks.":[74],"In":[75,103,230],"the":[76,81,88,104,133,143,146,159,168,176,199,202,232],"stage,":[78,106],"Barlow":[82],"twins":[83],"(BTs)":[84],"method":[85],"pretrain":[87],"encoder":[89,127],"reduce":[91],"redundancy":[92],"in":[93,120,167,211],"contrastive":[95],"manner":[97],"learn":[99],"high-level":[100],"data":[101,115,218],"representations.":[102],"construct":[108],"encoders":[110],"reconstruct":[112],"seismic":[114,228],"segment":[117],"bodies":[119],"multitask":[122],"collaborative":[123],"way.":[125],"The":[126],"decoder":[129],"are":[130],"composed":[131],"fully":[135],"convolutional":[136],"DenseNet":[137],"soft":[139],"attention":[140],"mechanism,":[141],"where":[142],"latter":[144],"represents":[145],"selective":[147],"kernel":[148],"block":[149,226],"(SKB)":[150],"with":[151],"multiple":[152],"kernels":[153],"different":[155,165],"sizes.":[156],"Salt3DNet":[157,187],"calculates":[158],"correlation":[160],"matrix":[161,178],"features":[163],"from":[164],"perspectives":[166],"stage":[170],"makes":[172],"it":[173],"close":[174],"identity":[177],"obtain":[180],"more":[182],"prosperous":[183],"feature":[184],"representation.":[185],"Then,":[186],"uses":[188],"limited":[190],"labeled":[193],"samples":[194],"training.":[196],"According":[197],"evaluation":[200],"metrics,":[201],"proposed":[203,233],"network":[204,234],"has":[205],"demonstrated":[206,236],"promising":[207],"performance":[210],"SEG":[213],"advanced":[214],"modeling":[215],"(SEAM)":[216],"synthetic":[217],"<inline-formula":[220],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[221],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[222],"<tex-math":[223],"notation=\"LaTeX\">$F3$":[224],"</tex-math></inline-formula>":[225],"real":[227],"data.":[229],"addition,":[231],"have":[238],"higher":[239],"prediction":[240],"accuracy":[241],"than":[242],"state-of-the-art":[243],"frameworks":[246],"through":[247],"ablation":[248],"experiments.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
