{"id":"https://openalex.org/W2097739839","doi":"https://doi.org/10.1109/igarss.2008.4779548","title":"Well Log Data Inversion using Higher Order Neural Networks","display_name":"Well Log Data Inversion using Higher Order Neural Networks","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2097739839","doi":"https://doi.org/10.1109/igarss.2008.4779548","mag":"2097739839"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2008.4779548","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","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/A5101537676","display_name":"Kou\u2010Yuan Huang","orcid":"https://orcid.org/0000-0001-9900-8480"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kou-Yuan Huang","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","Department of Computer Science, National Chiao Tung University, Hsinchu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108648018","display_name":"Liang\u2010Chi Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang-Chi Shen","raw_affiliation_strings":["Department of Electrical & Computer Engineering, University of Houston, TX, USA","Dept. of Electr. & Comput. Eng., Univ. of Houston, Houston, TX"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, University of Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Univ. of Houston, Houston, TX","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100347538","display_name":"Chunyu Chen","orcid":"https://orcid.org/0009-0003-2439-3937"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun-Yu Chen","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","Department of Computer Science, National Chiao Tung University, Hsinchu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15986161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"III ","last_page":" 1107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10399","display_name":"Hydrocarbon exploration and reservoir analysis","score":0.9973999857902527,"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":0.9973999857902527,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9968000054359436,"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/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9955000281333923,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.6810224056243896},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.6503187417984009},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.603406548500061},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5950734615325928},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5859757661819458},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5677028298377991},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5347000956535339},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43459534645080566},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42381149530410767},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.385423481464386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36271125078201294}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6810224056243896},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6503187417984009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.603406548500061},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5950734615325928},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5859757661819458},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5677028298377991},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5347000956535339},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43459534645080566},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42381149530410767},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.385423481464386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36271125078201294},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2008.4779548","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","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":12,"referenced_works":["https://openalex.org/W84288433","https://openalex.org/W605211202","https://openalex.org/W1541274513","https://openalex.org/W2011909934","https://openalex.org/W2012638612","https://openalex.org/W2117435895","https://openalex.org/W2129231659","https://openalex.org/W2154642048","https://openalex.org/W2738349735","https://openalex.org/W2766736793","https://openalex.org/W6603457801","https://openalex.org/W6682610290"],"related_works":["https://openalex.org/W2894173309","https://openalex.org/W2115605526","https://openalex.org/W4387932263","https://openalex.org/W2098962763","https://openalex.org/W3093883775","https://openalex.org/W1539246760","https://openalex.org/W2786746258","https://openalex.org/W2371065793","https://openalex.org/W2157746493","https://openalex.org/W1977222966"],"abstract_inverted_index":{"We":[0],"use":[1],"the":[2,17,25,28,33,36,39,47,54,62,78,82,93,107,121,124],"multilayer":[3],"perceptron":[4],"for":[5,53],"well":[6,115],"log":[7,116],"data":[8],"inversion.":[9],"The":[10,22,44,85],"gradient":[11],"descent":[12],"method":[13],"is":[14,27,38],"used":[15,52],"in":[16],"back":[18],"propagation":[19],"learning":[20],"rule.":[21],"input":[23,66,89,94],"of":[24,35],"network":[26,37,86,122],"apparent":[29],"conductivity":[30,42],"(Ca)":[31],"and":[32,46,73,81,91],"output":[34,80,103],"true":[40],"formation":[41],"(Ct).":[43],"original":[45],"higher":[48,64],"order":[49,65],"features":[50,67,95],"are":[51],"training":[55,72],"process.":[56],"According":[57],"to":[58,96,123],"our":[59],"experimental":[60],"results,":[61],"expanding":[63,92],"can":[68,105],"get":[69,106],"a":[70,74],"fast":[71],"smaller":[75],"error":[76,112],"between":[77],"desired":[79],"actual":[83],"output.":[84],"with":[87],"10":[88,102],"nodes":[90],"third":[97],"order,":[98],"8":[99],"hidden":[100],"nodes,":[101,104],"smallest":[108],"average":[109],"mean":[110],"absolute":[111],"on":[113],"simulated":[114],"data.":[117,127],"Then,":[118],"we":[119],"apply":[120],"real":[125],"field":[126]},"counts_by_year":[{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
