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Proceedings Papers

Cuttings Return Analysis by Visual Imaging: Novel Technology to Support Drilling Automation

Caroline D Grossi, Yuri H Hummels, Luiz Augusto da Cruz Meleiros, Claudia Miriam Scheid, Luís Américo Calçada, Alex Tadeu Almeida Waldmann, Carlos De Sa, André Leibsohn Martins
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 7–9, 2023
Paper Number: SPE-212441-MS
DOI: https://doi.org/10.2118/212441-MS
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Field Deployment of a LSTM Neural Network Tool for the Rock Formation Consolidation Inference of Brazilian Sandstone Reservoirs

Fabio Rodrigues Gonçalves da Silva, Victor Hugo Ribeiro Carriço, Alexandre Zacarias Ignácio Pereira, André Leibsohn Martins
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 7–9, 2023
Paper Number: SPE-212486-MS
DOI: https://doi.org/10.2118/212486-MS
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IADC Dull Code Upgrade: Photometric Classification and Quantification of the New Dull Codes

Ole Gjertsen, Ryan Mushinski, Preston Wolfram, Jeffrey Leisey, Mani Bandi, Roberta Santana, Gregory Andreasen, Paul Pastusek, Dustin Daechsel
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 7–9, 2023
Paper Number: SPE-212533-MS
DOI: https://doi.org/10.2118/212533-MS
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Automatic Classification of PDC Cutter Damage Using a Single Deep Learning Neural Network Model

Abdulbaset Ali, Harnoor Singh, Daniel Kelly, Donald Hender, Alan Clarke, Mohammad Mahdi Ghiasi, Ronald Haynes, Lesley James
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 7–9, 2023
Paper Number: SPE-212503-MS
DOI: https://doi.org/10.2118/212503-MS
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Real-Time Estimation of Downhole Equivalent Circulating Density ECD Using Machine Learning and Applications

Tim Robinson, Dalila Gomes, Meor M. Hakeem Meor Hashim, M. Hazwan Yusoff, M. Faris Arriffin, Azlan Mohamad, Tengku Ezharuddin, Eswadi Othman
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208675-MS
DOI: https://doi.org/10.2118/208675-MS
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Coupling Psychological Factors With Machine Learning to Improve Rig Technical Training

Francesco Curina, Elia Abdo, Ajith Asokan, Hadi Mustapha
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208689-MS
DOI: https://doi.org/10.2118/208689-MS
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Development of Automatic Recognition and Recording System for Rig Jobs

Yunhua Ge, Yanlong zhang, Su Ge, Yunyi Mei, Wenzhi Wang, Fengwei Yong, David He, Josh Zhang, Zhenyu Wang, Yuxin Wang
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208726-MS
DOI: https://doi.org/10.2118/208726-MS
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How Deep Learning can Provide Consistent Improvement on ROP Through Different Drilling Environments

Diego Alberto Junca Rivera, Julian Ricardo Bohorquez Gutierrez, Evgeniya Dontsova, John Estrada Giraldo, Jesus Martinez Ferreira, Jerry Webb
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208743-MS
DOI: https://doi.org/10.2118/208743-MS
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Prediction of Stuck Pipe Incidents Using Models Powered by Deep Learning and Machine Learning

Anwesha Mal, Sven Inge Ødegård, Stig Helgeland, Samuel Zulkhifly Sinaga, Morten Svendsen
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 8–10, 2022
Paper Number: SPE-208778-MS
DOI: https://doi.org/10.2118/208778-MS
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Real-Time Classification of Drilled Lithology from Drilling Data Using Deep Learning with Online Calibration

Mikkel Arnø, John-Morten Godhavn, Ole Morten Aamo
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 8–12, 2021
Paper Number: SPE-204093-MS
DOI: https://doi.org/10.2118/204093-MS
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Hybrid Physics-Based and Data-Driven Modeling for Improved Standpipe Pressure Prediction

Oney Erge, Eric van Oort
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 8–12, 2021
Paper Number: SPE-204094-MS
DOI: https://doi.org/10.2118/204094-MS
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Determining Rig State from Computer Vision Analytics

Crispin Chatar, Suhas Suresha, Laetitia Shao, Soumya Gupta, Indranil Roychoudhury
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 8–12, 2021
Paper Number: SPE-204086-MS
DOI: https://doi.org/10.2118/204086-MS
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Drill Bit Failure Forensics using 2D Bit Images Captured at the Rig Site

Pradeepkumar Ashok, Jian Chu, Ysabel Witt-Doerring, Zeyu Yan, Dongmei Chen, Eric van Oort
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 8–12, 2021
Paper Number: SPE-204124-MS
DOI: https://doi.org/10.2118/204124-MS
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Better Automatic Interpretation of Cement Evaluation Logs through Feature Engineering

Erlend Magnus Viggen, Lasse Løvstakken, Ioan Alexandru Merciu, Svein-Erik Måsøy
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 8–12, 2021
Paper Number: SPE-204057-MS
DOI: https://doi.org/10.2118/204057-MS
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The Development and Application of Real-Time Deep Learning Models to Drive Directional Drilling Efficiency

Dingzhou Cao, Don Hender, Sam Ariabod, Chris James, Yuxing Ben, Micheal Lee
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 3–5, 2020
Paper Number: SPE-199584-MS
DOI: https://doi.org/10.2118/199584-MS
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A Physics Model Embedded Hybrid Deep Neural Network for Drillstring Washout Detection

Cheolkyun Jeong, Yingwei Yu, Darine Mansour, Velizar Vesslinov, Richard Meehan
Paper presented at the IADC/SPE International Drilling Conference and Exhibition, March 3–5, 2020
Paper Number: SPE-199629-MS
DOI: https://doi.org/10.2118/199629-MS
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Prediction of Penetration Rate Ahead of the Bit through Real-Time Updated Machine Learning Models

Yuanjun Li, Robello Samuel
Paper presented at the SPE/IADC International Drilling Conference and Exhibition, March 5–7, 2019
Paper Number: SPE-194105-MS
DOI: https://doi.org/10.2118/194105-MS
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Recorded Well Data Enriches the Testing of Automation Systems by Using a Deep Neural Network Approach

Yingwei Yu, Sylvain Chambon, Qiuhua Liu, James Philip Belaskie
Paper presented at the IADC/SPE Drilling Conference and Exhibition, March 6–8, 2018
Paper Number: SPE-189591-MS
DOI: https://doi.org/10.2118/189591-MS
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Stuck Pipe Prediction and Avoidance: A Convolutional Neural Network Approach

C. Siruvuri, S. Nagarakanti, R. Samuel
Paper presented at the IADC/SPE Drilling Conference, February 21–23, 2006
Paper Number: SPE-98378-MS
DOI: https://doi.org/10.2118/98378-MS
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Optimization of Spacer Rheology Using Neural Network Technology

B. E. Théron, D. Bodin, J. Fleming
Paper presented at the IADC/SPE Drilling Conference, February 26–28, 2002
Paper Number: SPE-74498-MS
DOI: https://doi.org/10.2118/74498-MS
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