{"id":"https://openalex.org/W4206572773","doi":"https://doi.org/10.1109/ist50367.2021.9651426","title":"GeoPixAI: From Pixels to Intelligent, Unbiased and Automated Fast Track Subsurface Characterization","display_name":"GeoPixAI: From Pixels to Intelligent, Unbiased and Automated Fast Track Subsurface Characterization","publication_year":2021,"publication_date":"2021-08-24","ids":{"openalex":"https://openalex.org/W4206572773","doi":"https://doi.org/10.1109/ist50367.2021.9651426"},"language":"en","primary_location":{"id":"doi:10.1109/ist50367.2021.9651426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist50367.2021.9651426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5024037136","display_name":"Shariar Sattarin","orcid":null},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shariar Sattarin","raw_affiliation_strings":["Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039475467","display_name":"Temoor Muther","orcid":"https://orcid.org/0000-0001-9008-1358"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Temoor Muther","raw_affiliation_strings":["Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071900228","display_name":"Amirmasoud Kalantari Dahaghi","orcid":"https://orcid.org/0009-0005-6187-817X"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amirmasoud Kalantari Dahaghi","raw_affiliation_strings":["Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080711760","display_name":"Shahin Negahban","orcid":null},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahin Negahban","raw_affiliation_strings":["Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical and Petroleum Engineering, University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059834550","display_name":"Bryan Bell","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104238","display_name":"Building Engineering and Science Talent","ror":"https://ror.org/00rkxnb56","country_code":"US","type":"other","lineage":["https://openalex.org/I4210104238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Bell","raw_affiliation_strings":["Best Core Services, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Best Core Services, USA","institution_ids":["https://openalex.org/I4210104238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10399","display_name":"Hydrocarbon exploration and reservoir analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10399","display_name":"Hydrocarbon exploration and reservoir analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10491","display_name":"Enhanced Oil Recovery Techniques","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10635","display_name":"Hydraulic Fracturing and Reservoir Analysis","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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":0.6519733667373657},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6496595740318298},{"id":"https://openalex.org/keywords/petrophysics","display_name":"Petrophysics","score":0.5980446934700012},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49479836225509644},{"id":"https://openalex.org/keywords/reservoir-modeling","display_name":"Reservoir modeling","score":0.4927122890949249},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.45346227288246155},{"id":"https://openalex.org/keywords/well-logging","display_name":"Well logging","score":0.4433344602584839},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.44068410992622375},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.4303865134716034},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4208529591560364},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.419084370136261},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3700317442417145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36334460973739624},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.3067535161972046},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.24372082948684692},{"id":"https://openalex.org/keywords/petroleum-engineering","display_name":"Petroleum engineering","score":0.15411138534545898},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.1283278465270996}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6519733667373657},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6496595740318298},{"id":"https://openalex.org/C46293882","wikidata":"https://www.wikidata.org/wiki/Q2080707","display_name":"Petrophysics","level":3,"score":0.5980446934700012},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49479836225509644},{"id":"https://openalex.org/C14641988","wikidata":"https://www.wikidata.org/wiki/Q7315329","display_name":"Reservoir modeling","level":2,"score":0.4927122890949249},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.45346227288246155},{"id":"https://openalex.org/C35817400","wikidata":"https://www.wikidata.org/wiki/Q2383566","display_name":"Well logging","level":2,"score":0.4433344602584839},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.44068410992622375},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.4303865134716034},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4208529591560364},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.419084370136261},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3700317442417145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36334460973739624},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3067535161972046},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.24372082948684692},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.15411138534545898},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.1283278465270996},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C6648577","wikidata":"https://www.wikidata.org/wiki/Q622669","display_name":"Porosity","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ist50367.2021.9651426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist50367.2021.9651426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4000000059604645}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308355","display_name":"American Chemical Society","ror":"https://ror.org/059dqb057"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W33628638","https://openalex.org/W592963477","https://openalex.org/W1601795611","https://openalex.org/W1604933319","https://openalex.org/W1986517446","https://openalex.org/W1990476081","https://openalex.org/W2013691268","https://openalex.org/W2026632831","https://openalex.org/W2028109196","https://openalex.org/W2041258553","https://openalex.org/W2073692842","https://openalex.org/W2134461610","https://openalex.org/W2161987301","https://openalex.org/W2268671383","https://openalex.org/W2544759280","https://openalex.org/W2605620981","https://openalex.org/W2735661315","https://openalex.org/W2766736793","https://openalex.org/W2792952603","https://openalex.org/W2902163909","https://openalex.org/W2904218909","https://openalex.org/W2907131942","https://openalex.org/W2910673922","https://openalex.org/W2916032760","https://openalex.org/W2917169171","https://openalex.org/W2935864595","https://openalex.org/W2974126779","https://openalex.org/W2975558134","https://openalex.org/W2981825398","https://openalex.org/W2988270434","https://openalex.org/W3008518994","https://openalex.org/W3014718874","https://openalex.org/W3023120002","https://openalex.org/W3045623435","https://openalex.org/W3090987467","https://openalex.org/W3095925814","https://openalex.org/W3158448048","https://openalex.org/W4250362969","https://openalex.org/W6682610290","https://openalex.org/W6768663246","https://openalex.org/W6770363499"],"related_works":["https://openalex.org/W2184250192","https://openalex.org/W3034640112","https://openalex.org/W3154509160","https://openalex.org/W336850079","https://openalex.org/W1850913539","https://openalex.org/W2803518343","https://openalex.org/W2094093944","https://openalex.org/W2016243249","https://openalex.org/W2107465851","https://openalex.org/W3035681571"],"abstract_inverted_index":{"The":[0,20,92],"core":[1,66,139,169],"analysis":[2,67],"is":[3,23,142],"one":[4],"of":[5,26,64,113],"the":[6,24,35,62,98,114,123],"current":[7],"inefficacies":[8],"in":[9],"rock":[10],"characterization":[11],"and":[12,54,89,153,165,176],"petrophysical":[13],"evaluation":[14],"practices":[15],"directly":[16],"impacting":[17],"well-completion":[18],"decisions.":[19],"second":[21],"problem":[22],"lack":[25],"an":[27],"intelligent":[28,151],"multi-scale":[29],"image":[30,178],"processor":[31],"essential":[32],"for":[33,50,150],"integrating":[34],"data":[36],"into":[37],"digital":[38],"4.0":[39],"platforms,":[40],"which":[41],"has":[42],"a":[43,111,143],"significant":[44],"impact":[45],"on":[46,137,146],"G&G":[47],"teams’":[48],"decisions":[49],"better":[51],"well":[52],"completion":[53],"reservoir":[55],"evaluation.":[56],"In":[57,73],"this":[58,74,134],"paper,":[59],"we":[60],"discuss":[61],"example":[63],"slab":[65,138],"using":[68],"our":[69],"proposed":[70],"GeoPixAI":[71,141,162],"workflow.":[72],"application,":[75],"two":[76],"different":[77],"Convolution":[78],"Neural":[79],"Networks":[80],"(CNNs)":[81],"are":[82,94,125],"designed":[83],"to":[84,97,118,127],"measure":[85,100],"oil":[86],"saturation,":[87],"lithology,":[88],"fracture":[90],"distributions.":[91],"results":[93,109,124],"then":[95],"compared":[96],"lab":[99,120,131],"values.":[101],"Our":[102],"techniques":[103],"show":[104],"great":[105],"accuracy":[106],"while":[107],"producing":[108],"at":[110,159],"fraction":[112],"time":[115],"it":[116],"takes":[117],"do":[119],"analysis.":[121],"Also,":[122],"found":[126],"be":[128],"consistent":[129],"with":[130],"measurements.":[132],"While":[133],"study":[135],"focuses":[136],"analysis,":[140],"project":[144],"focus":[145],"Digital":[147],"Subsurface":[148],"Processing":[149],"segmentation":[152],"information":[154,167],"extraction":[155],"from":[156,168],"“raw”":[157],"images":[158],"any":[160],"scale.":[161],"can":[163],"analyze":[164],"extract":[166],"Micro-CT":[170],"scans,":[171],"seismic":[172],"data,":[173],"FMI":[174],"logs,":[175],"other":[177],"data.":[179]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}