{"id":"https://openalex.org/W7220972041","doi":"https://doi.org/10.48550/arxiv.2610.09282","title":"Self-attention summary networks for subsurface velocity-model building from common-image gathers","display_name":"Self-attention summary networks for subsurface velocity-model building from common-image gathers","publication_year":2026,"publication_date":"2026-10-07","ids":{"openalex":"https://openalex.org/W7220972041","doi":"https://doi.org/10.48550/arxiv.2610.09282"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.09282","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.09282","pdf_url":"https://arxiv.org/pdf/2610.09282","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.09282","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017565703","display_name":"Shiqin Zeng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeng, Shiqin","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027664698","display_name":"Yunlin Zeng","orcid":"https://orcid.org/0000-0003-4594-4331","observed_orcids":["https://orcid.org/0000-0003-4594-4331"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeng, Yunlin","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015570383","display_name":"Abhinav Prakash Gahlot","orcid":"https://orcid.org/0009-0008-7580-1220","observed_orcids":["https://orcid.org/0009-0008-7580-1220"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gahlot, Abhinav Prakash","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132691925","display_name":"Zijun Deng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deng, Zijun","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010780250","display_name":"Felix J. Herrmann","orcid":"https://orcid.org/0000-0003-1180-2167","observed_orcids":["https://orcid.org/0000-0003-1180-2167"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Herrmann, Felix J.","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"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":0.9970999956130981,"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":0.9970999956130981,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.0003000000142492354,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/common-image-gathers","display_name":"common image gathers","score":0.8180000185966492},{"id":"https://openalex.org/keywords/velocity-model-building","display_name":"velocity model building","score":0.6740000247955322},{"id":"https://openalex.org/keywords/flow-matching","display_name":"flow matching","score":0.8920000195503235},{"id":"https://openalex.org/keywords/residual-moveout","display_name":"residual moveout","score":0.9419999718666077},{"id":"https://openalex.org/keywords/multiscale-attention","display_name":"multi-scale attention","score":0.675000011920929}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6410999894142151},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.6391000151634216},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.536300003528595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5257999897003174},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.49799999594688416},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4291999936103821},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.41760000586509705},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.37880000472068787},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3382999897003174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3264000117778778},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31189998984336853},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.27000001072883606},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C45262634","wikidata":"https://www.wikidata.org/wiki/Q5159291","display_name":"Conditioning","level":2,"score":0.26100000739097595}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.09282","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.09282","pdf_url":"https://arxiv.org/pdf/2610.09282","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.2610.09282","doi":"https://doi.org/10.48550/arxiv.2610.09282","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.09282","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.09282","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.09282","pdf_url":"https://arxiv.org/pdf/2610.09282","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310224","display_name":"Georgia Research Alliance","ror":"https://ror.org/030689123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220972041.pdf","grobid_xml":"https://content.openalex.org/works/W7220972041.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W2028189898","https://openalex.org/W2045642993"],"related_works":["https://openalex.org/W3200644853","https://openalex.org/W4292451846","https://openalex.org/W4394786712","https://openalex.org/W7212058166","https://openalex.org/W4386432247","https://openalex.org/W3183846096","https://openalex.org/W2419191618","https://openalex.org/W2967345984","https://openalex.org/W7147401093","https://openalex.org/W3158997631"],"abstract_inverted_index":{"Common-image":[0],"gathers":[1],"(CIGs)":[2],"contain":[3],"physically":[4],"meaningful":[5],"information":[6],"about":[7],"velocity-model":[8],"errors":[9],"through":[10],"reflector":[11],"focusing":[12],"and":[13,61,131],"residual":[14],"moveout,":[15],"but":[16],"in":[17],"conventional":[18],"imaging":[19],"workflows":[20],"they":[21],"are":[22],"typically":[23],"used":[24],"only":[25],"as":[26],"diagnostic":[27],"tools.":[28],"In":[29,114],"this":[30],"work,":[31],"we":[32],"propose":[33],"a":[34,76,80,83],"multiscale":[35,117],"self-attention":[36],"summary":[37,74,108],"network":[38,109],"that":[39],"maps":[40],"high-dimensional":[41],"3D":[42],"CIG":[43],"volumes":[44],"into":[45],"compact":[46],"conditioning":[47,102],"embeddings":[48,56],"for":[49],"probabilistic":[50],"subsurface":[51],"velocity":[52,93,112],"inversion.":[53],"These":[54],"learned":[55],"preserve":[57],"offset-dependent":[58],"kinematic":[59],"structure":[60],"spatial":[62],"coherence":[63],"while":[64],"reducing":[65],"variability":[66],"caused":[67],"by":[68],"background-velocity":[69],"mismatch.":[70],"Conditioned":[71],"on":[72,103],"these":[73],"embeddings,":[75],"flow-matching":[77],"model":[78],"learns":[79],"transport":[81],"from":[82],"Gaussian":[84],"source":[85],"distribution":[86,90],"to":[87,123],"the":[88,106,116],"posterior":[89,111,129],"of":[91],"plausible":[92],"fields.":[94],"Numerical":[95],"experiments":[96],"show":[97],"that,":[98],"compared":[99],"with":[100],"direct":[101],"raw":[104],"CIGs,":[105],"proposed":[107],"improves":[110],"inference.":[113],"particular,":[115],"attention":[118],"design":[119],"provides":[120],"greater":[121],"robustness":[122],"background-model":[124],"mismatch,":[125],"yielding":[126],"more":[127],"accurate":[128],"reconstructions":[130],"lower":[132],"predictive":[133],"uncertainty.":[134]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-09T00:00:00"}