首页|New Machine Learning Study Findings Have Been Reported from Federal University ( Enhancement of Bayesian Seismic Inversion Using Machine Learning and Sparse Spike Wavelet: Case Study Norne Field Dataset)
New Machine Learning Study Findings Have Been Reported from Federal University ( Enhancement of Bayesian Seismic Inversion Using Machine Learning and Sparse Spike Wavelet: Case Study Norne Field Dataset)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting originating from Belem, Brazil, by NewsR x correspondents, research stated, “The concept of uncertainty is fundamental in seismic inversion modeling, as it pertains to the imprecision or lack of certai nty inherent in the model's results. In this work, we present a comprehensive st udy that integrates machine learning (ML), sensitivity analysis on well data, an d the sparse spike wavelet to enhance to quality of Bayesian linearized inversio n (BLI).”
BelemBrazilSouth AmericaCyborgsE merging TechnologiesMachine LearningFederal University
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