{"id":"https://openalex.org/W4415124475","doi":"https://doi.org/10.1109/icmlt65785.2025.11193235","title":"Intelligent Prediction and Modeling Method for Rock Drillability Based on Support Vector Machine","display_name":"Intelligent Prediction and Modeling Method for Rock Drillability Based on Support Vector Machine","publication_year":2025,"publication_date":"2025-05-23","ids":{"openalex":"https://openalex.org/W4415124475","doi":"https://doi.org/10.1109/icmlt65785.2025.11193235"},"language":"en","primary_location":{"id":"doi:10.1109/icmlt65785.2025.11193235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","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/A5056240323","display_name":"Chengtao Lv","orcid":"https://orcid.org/0000-0001-9599-6557"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Congyue Lv","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103141049","display_name":"Meng Cui","orcid":"https://orcid.org/0000-0003-2916-4618"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Cui","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101867190","display_name":"Yan Ding","orcid":"https://orcid.org/0000-0001-6956-9260"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Ding","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021942997","display_name":"Ziyun Zhao","orcid":"https://orcid.org/0009-0003-8721-8626"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyun Zhao","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386651","display_name":"Shuo Li","orcid":"https://orcid.org/0000-0003-1070-9155"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Li","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015395526","display_name":"Fei Zhao","orcid":"https://orcid.org/0000-0003-1393-3734"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Zhao","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102571217","display_name":"Reyu Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Reyu Gao","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101486334","display_name":"Ge Wang","orcid":"https://orcid.org/0009-0008-6352-3331"},"institutions":[{"id":"https://openalex.org/I98227222","display_name":"China National Petroleum Corporation (China)","ror":"https://ror.org/05269d038","country_code":"CN","type":"company","lineage":["https://openalex.org/I98227222"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Wang","raw_affiliation_strings":["R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Company Limited,CNPC Engineering Technology,Research Department,Beijing,China","institution_ids":["https://openalex.org/I98227222"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98227222"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"77","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.8827999830245972,"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"}},"topics":[{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.8827999830245972,"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/T14392","display_name":"Geoscience and Mining Technology","score":0.8162999749183655,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T14042","display_name":"Technology and Security Systems","score":0.8083000183105469,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4683000147342682},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3898000121116638},{"id":"https://openalex.org/keywords/numerical-modeling","display_name":"Numerical modeling","score":0.30469998717308044},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.30300000309944153},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.28790000081062317}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3806999921798706},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3718999922275543},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35920000076293945},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.32580000162124634},{"id":"https://openalex.org/C2989031253","wikidata":"https://www.wikidata.org/wiki/Q925667","display_name":"Numerical modeling","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C125620115","wikidata":"https://www.wikidata.org/wiki/Q845249","display_name":"Logging","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C41242791","wikidata":"https://www.wikidata.org/wiki/Q17105549","display_name":"Rock mass classification","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.27309998869895935},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlt65785.2025.11193235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321570","display_name":"China National Petroleum Corporation","ror":"https://ror.org/05269d038"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"data-driven":[1,50],"intelligent":[2,51],"modeling":[3,52],"method":[4,53],"for":[5,54,73,98,137,145],"the":[6,26,37,55,62,75,79,95,106,109,113,122,128,138,147],"drillability":[7,27,38,56,77,97,110,130,148],"of":[8,28,39,57,105,112,126,141,149],"formation":[9,29,40,58,150],"rocks":[10,30,41,114],"is":[11],"an":[12],"approach":[13],"that":[14],"utilizes":[15],"machine":[16],"learning":[17],"and":[18,24,42,115,124,132],"artificial":[19],"intelligence":[20],"technologies":[21],"to":[22,68,93],"predict":[23,94],"evaluate":[25],"by":[31],"establishing":[32,101],"a":[33,49,70,102,134,142],"relationship":[34,107],"model":[35,72,104,144],"between":[36,108],"various":[43],"logging":[44],"parameters.":[45],"This":[46,120],"paper":[47],"proposes":[48],"rocks.":[59,151],"It":[60],"uses":[61],"Extreme":[63],"Learning":[64],"Machine":[65],"(ELM)":[66],"algorithm":[67],"establish":[69],"one-dimensional":[71],"predicting":[74,127,146],"rock":[76,96,129],"in":[78,89],"Yu":[80],"well":[81],"block.":[82],"A":[83],"software":[84],"named":[85],"Drillability":[86],"1.0,":[87],"developed":[88],"Matlab,":[90],"was":[91],"used":[92],"five":[99],"wells,":[100],"high-precision":[103],"grade":[111,131],"some":[116],"important":[117],"influencing":[118],"factors.":[119],"improves":[121],"accuracy":[123],"efficiency":[125],"lays":[133],"data":[135],"foundation":[136],"subsequent":[139],"establishment":[140],"three-dimensional":[143]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-14T00:00:00"}