Machine Learning Model for Monitoring Rheological Properties of Synthetic Oil-Based Mud-Reference-Cited by-同舟云学术

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Machine Learning Model for Monitoring Rheological Properties of Synthetic Oil-Based Mud

Published:2022-04-29 Issue:18 Volume:7 Page:15603-15614
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Alsabaa Ahmed¹,Gamal Hany¹^ORCID,Elkatatny Salaheldin¹²^ORCID,Abdelraouf Yasmin³

Affiliation:

1. Department of Petroleum Engineering and Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia

2. Center for Integrative Petroleum Research, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia

3. Chemical Engineering Department, Cairo University, 12613 Giza, Egypt

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c00404

Reference78 articles.

1. Knox, D.; Jiang, P. In Drilling Further with Water-Based Fluids – Selecting the Right Lubricant, SPE International Symposium on Oilfield Chemistry Proceedings, Society of Petroleum Engineers, 2005.

2. Selecting a Drilling Fluid

3. Knox, D.; Jiang, P. In Drilling Further with Water-Based Fluids – Selecting the Right Lubricant, SPE International Symposium on Oilfield Chemistry Proceedings, Society of Petroleum Engineers, 2005.

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