{"id":"https://openalex.org/W7225274361","doi":"https://doi.org/10.1190/geo-2025-1268","title":"Seismic Resolution Enhancement Using a Transformer by Fusing Local and Global Attention","display_name":"Seismic Resolution Enhancement Using a Transformer by Fusing Local and Global Attention","publication_year":2026,"publication_date":"2026-11-04","ids":{"openalex":"https://openalex.org/W7225274361","doi":"https://doi.org/10.1190/geo-2025-1268"},"language":"en","primary_location":{"id":"doi:10.1190/geo-2025-1268","doi":"https://doi.org/10.1190/geo-2025-1268","is_oa":false,"landing_page_url":"https://doi.org/10.1190/geo-2025-1268","pdf_url":null,"source":{"id":"https://openalex.org/S106174089","display_name":"Geophysics","issn_l":"0016-8033","issn":["0016-8033","1942-2156"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-a","jufo-1","norway-2","poland-100","russia-white-list-1"],"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":"Geophysics","raw_type":"journal-article"},"volume":null,"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/A5160587775","display_name":"Kun Li","orcid":"https://orcid.org/0009-0006-2718-0146","observed_orcids":["https://orcid.org/0009-0006-2718-0146"]},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Li","raw_affiliation_strings":["1Shandong Province Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao 266580, China"],"raw_orcid":"https://orcid.org/0009-0006-2718-0146","affiliations":[{"raw_affiliation_string":"1Shandong Province Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134673111","display_name":"Wei Ge","orcid":"https://orcid.org/0009-0008-5691-7914","observed_orcids":["https://orcid.org/0009-0008-5691-7914"]},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Ge","raw_affiliation_strings":["1Shandong Province Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao 266580, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1Shandong Province Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075010438","display_name":"\u5370\u5174\u8000","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyao Yin","raw_affiliation_strings":["1Shandong Province Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao 266580, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1Shandong Province Key Laboratory of Intelligent Oil & Gas Industrial Software, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058951044","display_name":"Danping Cao","orcid":"https://orcid.org/0000-0002-1351-089X","observed_orcids":["https://orcid.org/0000-0002-1351-089X"]},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danping Cao","raw_affiliation_strings":["2School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"2School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80774266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9253000020980835,"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":0.9253000020980835,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.061500001698732376,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.0024999999441206455,"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"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.623199999332428},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.45089998841285706},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.41449999809265137},{"id":"https://openalex.org/C64370902","wikidata":"https://www.wikidata.org/wiki/Q7315329","display_name":"Seismic to simulation","level":4,"score":0.4129999876022339},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4004000127315521},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3440999984741211},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C39267094","wikidata":"https://www.wikidata.org/wiki/Q7446968","display_name":"Seismic inversion","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3221000134944916},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C14641988","wikidata":"https://www.wikidata.org/wiki/Q7315329","display_name":"Reservoir modeling","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1190/geo-2025-1268","doi":"https://doi.org/10.1190/geo-2025-1268","is_oa":false,"landing_page_url":"https://doi.org/10.1190/geo-2025-1268","pdf_url":null,"source":{"id":"https://openalex.org/S106174089","display_name":"Geophysics","issn_l":"0016-8033","issn":["0016-8033","1942-2156"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-a","jufo-1","norway-2","poland-100","russia-white-list-1"],"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":"Geophysics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"High-resolution":[1],"seismic":[2,54,198,205,213],"data":[3,199,214],"is":[4,79,157],"crucial":[5],"for":[6,17],"accurately":[7],"characterizing":[8],"thin":[9],"reservoirs":[10],"and":[11,19,110,117,141,152,164,185],"small-scale":[12],"faults,":[13],"providing":[14],"the":[15,46,104,121,126,149,177],"foundation":[16],"lithology":[18],"fluid":[20],"identification.":[21],"However,":[22],"image":[23],"super-resolution":[24],"techniques":[25],"based":[26],"on":[27],"deep-learning":[28],"methods,":[29],"particularly":[30],"convolutional":[31],"neural":[32],"networks,":[33],"are":[34],"fundamentally":[35],"constrained":[36],"to":[37,44,51,58,88,95,106,159,196],"local":[38,90,108],"receptive":[39,99],"fields.":[40],"Such":[41],"architectures":[42],"struggle":[43],"capture":[45,89],"long-range":[47],"spatial":[48],"dependencies":[49],"required":[50],"model":[52,105],"continuous":[53],"events,":[55],"often":[56],"leading":[57],"oversmoothed":[59],"results":[60],"or":[61],"structural":[62,118,154,165,186],"artifacts.":[63],"To":[64,124],"address":[65],"this":[66],"problem,":[67],"we":[68,132],"develop":[69],"a":[70,80,97,134,144,168],"dual-attention":[71,81],"transformer":[72,82],"termed":[73],"Seis-DAT.":[74],"The":[75],"core":[76],"of":[77,128],"Seis-DAT":[78,202],"block":[83],"that":[84,176,201],"integrates":[85],"window-based":[86],"self-attention":[87],"textures":[91],"with":[92,207],"channel":[93],"attention":[94],"provide":[96],"global":[98,111],"field.":[100],"This":[101],"design":[102],"enables":[103],"learn":[107],"details":[109],"geological":[112],"trends,":[113],"ensuring":[114],"both":[115],"fidelity":[116],"consistency":[119],"in":[120],"reconstructed":[122],"results.":[123],"mitigate":[125],"scarcity":[127],"high-quality":[129],"labeled":[130],"data,":[131],"construct":[133],"large-scale":[135],"synthetic":[136],"dataset":[137],"incorporating":[138],"complex":[139],"faults":[140],"folds.":[142],"Furthermore,":[143],"composite":[145],"loss":[146,151,156],"function":[147],"combining":[148],"?1":[150],"multiscale":[153],"similarity":[155,187],"employed":[158],"dynamically":[160],"balance":[161],"pixel-level":[162],"accuracy":[163],"integrity":[166],"through":[167],"linear":[169],"weight":[170],"scheduling":[171],"strategy.":[172],"Synthetic":[173],"tests":[174],"demonstrate":[175],"proposed":[178],"method":[179],"achieves":[180],"higher":[181],"peak":[182],"signal-to-noise":[183],"ratio":[184],"index":[188],"measure":[189],"values":[190],"than":[191],"conventional":[192],"comparative":[193],"methods.":[194],"Applications":[195],"real":[197],"show":[200],"generates":[203],"clearer":[204],"events":[206],"enhanced":[208],"lateral":[209],"continuity,":[210],"thereby":[211],"improving":[212],"resolution.":[215]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-05T00:00:00"}
