{"id":"https://openalex.org/W7143394635","doi":"https://doi.org/10.3390/app16073341","title":"Sandbody Prediction Based on Fusion of Seismic Multi-Attributes and Machine Learning Under Sedimentary Facies Constraint\u2014A Case Study of Chenguanzhuang Area in Dongying Depression, Bohai Bay Basin","display_name":"Sandbody Prediction Based on Fusion of Seismic Multi-Attributes and Machine Learning Under Sedimentary Facies Constraint\u2014A Case Study of Chenguanzhuang Area in Dongying Depression, Bohai Bay Basin","publication_year":2026,"publication_date":"2026-03-30","ids":{"openalex":"https://openalex.org/W7143394635","doi":"https://doi.org/10.3390/app16073341"},"language":"en","primary_location":{"id":"doi:10.3390/app16073341","doi":"https://doi.org/10.3390/app16073341","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app16073341","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Sciences","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/app16073341","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042302979","display_name":"Jinshuai Liu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinshuai Liu","raw_affiliation_strings":["National Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China","School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China","Shandong Provincial Key Laboratory of Reservoir Geology, Qingdao 266580, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Reservoir Geology, Qingdao 266580, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030308886","display_name":"Chengyan Lin","orcid":"https://orcid.org/0000-0002-2848-9755","observed_orcids":["https://orcid.org/0000-0002-2848-9755","https://orcid.org/0000-0002-5291-802X"]},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengyan Lin","raw_affiliation_strings":["National Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China","School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China","Shandong Provincial Key Laboratory of Reservoir Geology, Qingdao 266580, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Reservoir Geology, Qingdao 266580, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083262939","display_name":"Chris Elders","orcid":"https://orcid.org/0000-0003-3317-6734","observed_orcids":["https://orcid.org/0000-0003-3317-6734"]},"institutions":[{"id":"https://openalex.org/I205640436","display_name":"Curtin University","ror":"https://ror.org/02n415q13","country_code":"AU","type":"education","lineage":["https://openalex.org/I205640436"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chris Elders","raw_affiliation_strings":["School of Earth and Planetary Sciences, Curtin University, Perth, WA 6102, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Earth and Planetary Sciences, Curtin University, Perth, WA 6102, Australia","institution_ids":["https://openalex.org/I205640436"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039061991","display_name":"Faris Azhari","orcid":"https://orcid.org/0000-0001-7515-6171","observed_orcids":["https://orcid.org/0000-0001-7515-6171"]},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Azhari Faris","raw_affiliation_strings":["School of Electrical Engineering and Robotics, Queensland University of Technology, Brisbane, QLD 4072, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7515-6171","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Robotics, Queensland University of Technology, Brisbane, QLD 4072, Australia","institution_ids":["https://openalex.org/I160993911"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030308886","https://openalex.org/A5042302979"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2896},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2896},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18854972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"7","first_page":"3341","last_page":"3341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.5425000190734863,"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":0.5425000190734863,"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/T10399","display_name":"Hydrocarbon exploration and reservoir analysis","score":0.23250000178813934,"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/T13067","display_name":"Geological Modeling and Analysis","score":0.07729999721050262,"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/shahejie-formation","display_name":"Shahejie Formation","score":0.8270000219345093},{"id":"https://openalex.org/keywords/machine-learning","display_name":"machine learning","score":0.5600000023841858},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":0.753000020980835},{"id":"https://openalex.org/keywords/ridge-regression","display_name":"ridge regression","score":0.7459999918937683},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.7009999752044678},{"id":"https://openalex.org/keywords/dongying-depression","display_name":"Dongying Depression","score":0.656000018119812},{"id":"https://openalex.org/keywords/petroleum-exploration","display_name":"petroleum exploration","score":0.824999988079071}],"concepts":[{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.8284000158309937},{"id":"https://openalex.org/C146588470","wikidata":"https://www.wikidata.org/wiki/Q742139","display_name":"Facies","level":3,"score":0.7264999747276306},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5425000190734863},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.5138999819755554},{"id":"https://openalex.org/C6494504","wikidata":"https://www.wikidata.org/wiki/Q82480","display_name":"Sedimentary rock","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C2781294565","wikidata":"https://www.wikidata.org/wiki/Q5711131","display_name":"Seismic attribute","level":2,"score":0.3912000060081482},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C2776662147","wikidata":"https://www.wikidata.org/wiki/Q3241434","display_name":"Hydrocarbon exploration","level":3,"score":0.3553999960422516},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.351500004529953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3440000116825104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33730000257492065},{"id":"https://openalex.org/C5900021","wikidata":"https://www.wikidata.org/wiki/Q163082","display_name":"Petrology","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C200646496","wikidata":"https://www.wikidata.org/wiki/Q785020","display_name":"Sedimentary basin","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C39267094","wikidata":"https://www.wikidata.org/wiki/Q7446968","display_name":"Seismic inversion","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C5072461","wikidata":"https://www.wikidata.org/wiki/Q49506","display_name":"Delta","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/app16073341","doi":"https://doi.org/10.3390/app16073341","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app16073341","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Sciences","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0330a91d287c464f8c3606a019dd15da","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/0330a91d287c464f8c3606a019dd15da","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Sciences, Vol 16, Iss 7, p 3341 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/app16073341","doi":"https://doi.org/10.3390/app16073341","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app16073341","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Sciences","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1860694095","display_name":null,"funder_award_id":"42372156","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2299474652","display_name":null,"funder_award_id":"202106450061","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"complex":[1,211],"sedimentary":[2,60,212],"environments,":[3],"the":[4,10,27,31,35,40,44,80,143,185,190],"identification":[5],"of":[6,13,30,34,43,138,173,192],"thin":[7],"sandbodies":[8],"and":[9,76,93,109,112,122,140,145,175,204],"accurate":[11],"prediction":[12,56],"their":[14],"thickness":[15],"remain":[16],"challenging,":[17],"particularly":[18],"when":[19],"relying":[20],"on":[21,70],"a":[22,48,54,197],"single":[23],"analytical":[24],"approach.":[25],"Taking":[26],"lower":[28],"sub-member":[29],"fourth":[32],"member":[33],"Shahejie":[36],"Formation":[37],"(Es4L)":[38],"in":[39],"Chenguanzhuang":[41],"area":[42,82],"Dongying":[45],"Depression":[46],"as":[47],"case":[49],"study,":[50],"this":[51],"study":[52,81],"proposes":[53],"quantitative":[55,193],"method":[57],"that":[58],"integrates":[59],"facies":[61],"constraints":[62],"with":[63,153,178],"machine":[64,114],"learning-based":[65],"seismic":[66,78],"multi-attribute":[67],"fusion.":[68],"Based":[69],"core":[71],"observations,":[72],"well":[73,168],"log":[74],"data,":[75,169],"3D":[77],"datasets,":[79],"is":[83,130,157],"subdivided":[84],"into":[85],"two":[86],"zones:":[87],"Zone":[88,94,133,160],"I":[89],"(shallow-water":[90],"delta":[91],"front)":[92],"II":[95,161],"(shore\u2013shallow":[96],"lake).":[97],"Sensitive":[98],"attributes":[99],"for":[100,132,142,159,201,209],"each":[101],"zone":[102],"are":[103],"optimized":[104],"using":[105],"Pearson":[106],"correlation":[107],"analysis":[108],"hierarchical":[110],"clustering,":[111],"five":[113],"learning":[115],"models\u2014SVR,":[116],"Random":[117],"Forest,":[118],"MLP,":[119],"Ridge":[120,150],"Regression,":[121],"Lasso":[123],"Regression\u2014are":[124],"systematically":[125],"evaluated.":[126],"The":[127],"MLP":[128],"model":[129],"selected":[131],"I,":[134],"achieving":[135],"R2":[136,171],"values":[137,172],"0.856":[139],"0.936":[141],"training":[144],"test":[146],"sets,":[147],"respectively,":[148],"whereas":[149],"Regression":[151],"combined":[152],"leave-one-out":[154],"cross-validation":[155],"(LOOCV)":[156],"adopted":[158],"to":[162],"mitigate":[163],"overfitting":[164],"caused":[165],"by":[166],"limited":[167],"yielding":[170],"0.864":[174],"0.779.":[176],"Compared":[177],"conventional":[179],"linear":[180],"regression":[181],"(R2":[182],"=":[183],"0.45),":[184],"proposed":[186],"approach":[187],"significantly":[188],"improves":[189],"accuracy":[191],"sandbody":[194],"prediction,":[195],"providing":[196],"reliable":[198],"geological":[199],"basis":[200],"hydrocarbon":[202],"exploration":[203],"an":[205],"effective":[206],"technical":[207],"framework":[208],"similar":[210],"environments.":[213]},"counts_by_year":[],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2026-03-31T00:00:00"}