Determination of the Rate of Penetration by Robust Machine Learning Algorithms Based on Drilling Parameters-Reference-Cited by-同舟云学术

Determination of the Rate of Penetration by Robust Machine Learning Algorithms Based on Drilling Parameters

Published:2023-11-28 Issue:49 Volume:8 Page:46390-46398
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Alavi Nezhad Khalil Abad Seyed Vahid¹,Hazbeh Omid²,Rajabi Meysam³,Tabasi Somayeh⁴,Lajmorak Sahar⁵,Ghorbani Hamzeh⁶⁷^ORCID,Radwan Ahmed E.⁸,Mudabbir Mohammad⁷

Affiliation:

1. Department of Civil Engineering, Birjand University of Technology, Birjand 97198 66981, Iran

2. Faculty of Earth Sciences, Shahid Chamran University, Ahwaz 6135743136, Iran

3. Department of Mining Engineering, Birjand University of Technology, Birjand 97198 66981, Iran

4. Faculty of Industry and Mining (Khash), University of Sistan and Baluchestan, Zahedan 1489684511, Iran

5. Department of Earth Sciences, Institute for Advanced Studies in Basic Sciences (IASBS), 444 Prof. Yousef Sobouti Blvd., Zanjan 45137-66731, Iran

6. Young Researchers and Elite Club, Ahvaz Branch, Islamic Azad University, Ahvaz 1477893855, Iran

7. Doctoral School of Materials Science and TechnologiesObuda University, Budapest 1034, Hungary

8. Faculty of Geography and Geology, Institute of Geological Sciences, Jagiellonian University, Gronostajowa 3a, Kraków 30-387, Poland

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.3c02364

Reference65 articles.

1. Application Of Artificial Intelligence Methods In Drilling System Design And Operations: A Review Of The State Of The Art

2. Offshore Geological Storage of Hydrogen: Is This Our Best Option to Achieve Net-Zero?

3. Drilling in Complex Pore Pressure Regimes: Analysis of Wellbore Stability Applying the Depth of Failure Approach

4. Underground energy-related product storage and sequestration: site characterization, risk analysis and monitoring

5. Exploring the influence of rock inherent heterogeneity and grain size on hydraulic fracturing using discrete element modeling