首页|Researchers from Yangtze University Describe Findings in Machine Learning (Ident ification of Reservoir Types In Deep Carbonates Based On Mixed-kernel Machine Le arning Using Geophysical Logging Data)
Researchers from Yangtze University Describe Findings in Machine Learning (Ident ification of Reservoir Types In Deep Carbonates Based On Mixed-kernel Machine Le arning Using Geophysical Logging Data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingfrom Hubei, People’s Republic of Ch ina, by NewsRx journalists, research stated, “Identification of reservoirtypes in deep carbonates has always been a great challenge due to complex logging resp onses caused bythe heterogeneous scale and distribution of storage spaces. Trad itional cross-plot analysis and empiricalformula methods for identifying reserv oir types using geophysical logging data have high uncertaintyand low efficienc y, which cannot accurately reflect the nonlinear relationship between reservoir types andlogging data.”
HubeiPeople’s Republic of ChinaAsiaAlkaliesAnionsCarbonatesCarbonic AcidCyborgsEmerging TechnologiesFi sher’s Discriminant AnalysisMachine LearningYangtze University
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