Improved Tracking of the Rheological Properties of Max-Bridge Oil-Based Mud Using Artificial Neural Networks-Reference-Cited by-同舟云学术

Improved Tracking of the Rheological Properties of Max-Bridge Oil-Based Mud Using Artificial Neural Networks

Published:2021-06-11 Issue:24 Volume:6 Page:15816-15826
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Alsabaa Ahmed¹,Elkatatny Salaheldin¹^ORCID

Affiliation:

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

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.1c01230

Reference69 articles.

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2. Selecting a Drilling Fluid

3. Power, D.; Zamora, M. In Drilling Fluid Yield Stress: Measurement Techniques for Improved Understanding of Critical Drilling Fluid Parameters, AADE Technical Conference, Houston, 2003; pp 1–3.

4. An Improved Water-in-Oil Emulsion Mud

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