{"id":"https://openalex.org/W2534455363","doi":"https://doi.org/10.1109/fskd.2016.7603267","title":"Application of artificial neural network in Geology: Porosity estimation and lithological facies classification","display_name":"Application of artificial neural network in Geology: Porosity estimation and lithological facies classification","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2534455363","doi":"https://doi.org/10.1109/fskd.2016.7603267","mag":"2534455363"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2016.7603267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2016.7603267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-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/A5039053972","display_name":"Suihong Son","orcid":null},"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":"Suihong Son","raw_affiliation_strings":["China University of Petroleum Beijing, Changping-qu, Beijing, CN"],"affiliations":[{"raw_affiliation_string":"China University of Petroleum Beijing, Changping-qu, Beijing, CN","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051064524","display_name":"Jiagen Hou","orcid":"https://orcid.org/0000-0002-0976-7502"},"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":"Jiagen Hou","raw_affiliation_strings":["College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613984","display_name":"Yuming Liu","orcid":"https://orcid.org/0000-0002-9857-5018"},"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":"Yuming Liu","raw_affiliation_strings":["College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110451440","display_name":"Sifan Cao","orcid":null},"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":"Sifan Cao","raw_affiliation_strings":["College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024134386","display_name":"Chenbin Hu","orcid":null},"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":"Chenbin Hu","raw_affiliation_strings":["College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070975441","display_name":"Xixin Wang","orcid":"https://orcid.org/0000-0003-4082-7179"},"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":"Xixin Wang","raw_affiliation_strings":["College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054723866","display_name":"Zhen Chang","orcid":"https://orcid.org/0000-0002-7979-8419"},"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":"Zhen Chang","raw_affiliation_strings":["College of Geoscience, China University of Petroleum, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Geoscience, China University of Petroleum, Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5039053972"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":null,"apc_paid":null,"fwci":0.2862,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60386976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"740","last_page":"744"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10399","display_name":"Hydrocarbon exploration and reservoir analysis","score":0.9980000257492065,"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":0.9980000257492065,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.989300012588501,"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"}},{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"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/facies","display_name":"Facies","score":0.9293028116226196},{"id":"https://openalex.org/keywords/petrophysics","display_name":"Petrophysics","score":0.8808321952819824},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.7805451154708862},{"id":"https://openalex.org/keywords/porosity","display_name":"Porosity","score":0.7521619200706482},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49501746892929077},{"id":"https://openalex.org/keywords/well-logging","display_name":"Well logging","score":0.4903159439563751},{"id":"https://openalex.org/keywords/mineralogy","display_name":"Mineralogy","score":0.46919485926628113},{"id":"https://openalex.org/keywords/geomorphology","display_name":"Geomorphology","score":0.1812393069267273},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.17569103837013245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1409013271331787},{"id":"https://openalex.org/keywords/geophysics","display_name":"Geophysics","score":0.10915163159370422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.05866703391075134}],"concepts":[{"id":"https://openalex.org/C146588470","wikidata":"https://www.wikidata.org/wiki/Q742139","display_name":"Facies","level":3,"score":0.9293028116226196},{"id":"https://openalex.org/C46293882","wikidata":"https://www.wikidata.org/wiki/Q2080707","display_name":"Petrophysics","level":3,"score":0.8808321952819824},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.7805451154708862},{"id":"https://openalex.org/C6648577","wikidata":"https://www.wikidata.org/wiki/Q622669","display_name":"Porosity","level":2,"score":0.7521619200706482},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49501746892929077},{"id":"https://openalex.org/C35817400","wikidata":"https://www.wikidata.org/wiki/Q2383566","display_name":"Well logging","level":2,"score":0.4903159439563751},{"id":"https://openalex.org/C199289684","wikidata":"https://www.wikidata.org/wiki/Q83353","display_name":"Mineralogy","level":1,"score":0.46919485926628113},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.1812393069267273},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.17569103837013245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1409013271331787},{"id":"https://openalex.org/C8058405","wikidata":"https://www.wikidata.org/wiki/Q46255","display_name":"Geophysics","level":1,"score":0.10915163159370422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.05866703391075134},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2016.7603267","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2016.7603267","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1019891831","https://openalex.org/W1515330496","https://openalex.org/W1575476631","https://openalex.org/W1673310716","https://openalex.org/W2035912401","https://openalex.org/W2107946060","https://openalex.org/W2117851878","https://openalex.org/W2120636855","https://openalex.org/W2142838865","https://openalex.org/W2149230623","https://openalex.org/W2150593711","https://openalex.org/W2265166184","https://openalex.org/W6637131181"],"related_works":["https://openalex.org/W2379688619","https://openalex.org/W2986318339","https://openalex.org/W2359442070","https://openalex.org/W4247900746","https://openalex.org/W3154509160","https://openalex.org/W336850079","https://openalex.org/W2016243249","https://openalex.org/W4225150602","https://openalex.org/W2945197122","https://openalex.org/W2957227586"],"abstract_inverted_index":{"Based":[0],"on":[1],"the":[2,51,80,88,99],"relationship":[3],"between":[4],"porosity":[5,21,29,59,92],"(or":[6],"lithological":[7,24,34,62,102],"facies)":[8],"and":[9,23,32,61,68,83,98],"other":[10,121],"petrophysical":[11],"properties,":[12],"Artificial":[13],"neural":[14],"networks":[15],"(ANN)":[16],"are":[17],"respectively":[18],"trained":[19,67],"for":[20,58,72,120],"estimation":[22,60],"facies":[25,35,63,103],"classification,":[26],"using":[27],"core":[28,33,41,70],"(CPOR)":[30],"data":[31],"interpretation":[36],"results":[37,82],"of":[38,40,75,79,90,101,111],"part":[39],"interval":[42],"together":[43],"with":[44],"some":[45],"well":[46],"logs":[47],"(petrophysical":[48],"properties).":[49],"After":[50,85],"ANN":[52,115],"were":[53,56],"constructed,":[54],"they":[55],"used":[57],"identification":[64,104],"in":[65],"both":[66,107],"untrained":[69],"intervals,":[71],"further":[73],"analysis":[74],"errors":[76],"or":[77,124],"accuracies":[78],"estimated":[81,91],"ANN.":[84,112],"careful":[86],"analysis,":[87],"error":[89],"is":[93,105],"from":[94],"\u22120.3":[95],"to":[96],"0.3,":[97],"accuracy":[100],"0.7,":[106],"showing":[108],"high":[109],"reliability":[110],"The":[113],"constructed":[114],"can":[116],"be":[117],"confidently":[118],"applied":[119],"un-cored":[122],"wells":[123],"intervals.":[125]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
