Domain adaptation neural network based prediction of real-time drill bit tooth wear-Reference-Cited by-同舟云学术

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Domain adaptation neural network based prediction of real-time drill bit tooth wear

Published:2024-09 Issue: Volume:240 Page:213041
ISSN:2949-8910
Container-title:Geoenergy Science and Engineering
language:en
Short-container-title:Geoenergy Science and Engineering

Author:

Ye Shanlin,Song Xianzhi^ORCID,Blunt Martin J.,Bijeljic Branko^ORCID

Publisher

Elsevier BV

Reference25 articles.

1. Applied Drilling Engineering;Adam,1986

2. Probabilistic neural network with bayesian-based, spectral torque imaging and deep convolutional autoencoder for PDC bit wear monitoring;Agostini;J. Petrol. Sci. Eng.,2020

3. A robust rate of penetration model for carbonate formation;Al-AbdulJabbar;J. Energy Resour. Technol.,2019

4. Machine learning methods applied to drilling rate of penetration prediction and optimization-A review;Barbosa;J. Petrol. Sci. Eng.,2019

5. A multiple regression approach to optimal drilling and abnormal pressure detection;Bourgoyne;Soc. Petrol. Eng. J.,1974

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