An uncertainty approach for Electric Submersible Pump modeling through Deep Neural Network

An uncertainty approach for Electric Submersible Pump modeling through Deep Neural Network

This work proposes a new methodology to identify and validate deep learning models for artificial oil lift systems that use submersible electric pumps. The proposed methodology allows for obtaining the models and evaluating the prediction's uncertainty jointly and systematically. The methodolog...

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Bibliographic Details
Main Authors: Erbet Almeida Costa, Carine de Menezes Rebello, Vinicius Viena Santana, Galdir Reges, Tiago de Oliveira Silva, Odilon Santana Luiz de Abreu, Marcos Pellegrini Ribeiro, Bernardo Pereira Foresti, Marcio Fontana, Idelfonso Bessa dos Reis Nogueira, Leizer Schnitman
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Heliyon
Subjects:
Electric submersible pump
Deep neural networks
Uncertainty assessment
MCMC
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024000781

Internet

http://www.sciencedirect.com/science/article/pii/S2405844024000781

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