首页|Findings from China University of Geosciences Wuhan Provides NewData about Mach ine Learning (Machine Learning for SubsurfaceGeological Feature Identification From Seismic Data: Methods,Datasets, Challenges, and Opportunities)
Findings from China University of Geosciences Wuhan Provides NewData about Mach ine Learning (Machine Learning for SubsurfaceGeological Feature Identification From Seismic Data: Methods,Datasets, Challenges, and Opportunities)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting from Hubei, People’s Republ ic of China, by NewsRx journalists, research stated, “Identificationof geologic al features from seismic data such as faults, salt bodies, and channels, is esse ntial for studiesof the shallow Earth, natural disaster forecasting and evaluat ion, carbon capture and storage, hydrogenstorage, geothermal energy development , and traditional resource exploration. However, manual seismicinterpretation i s distinctly subjective and labor-intensive.”Financial supporters for this research include China Scholarship Council, Key Re search and DevelopmentProject of Hubei Province Technology Innovation Plan, Nat ional Key Research & Development Programof China.
HubeiPeople’s Republic of ChinaAsiaCyborgsEmergingTechnologiesMachine LearningChina University of Geoscienc es Wuhan
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