Mud loss estimation using machine learning approach

Author:

Al-Hameedi Abo Taleb T.,Alkinani Husam H.,Dunn-Norman Shari,Flori Ralph E.,Hilgedick Steven A.,Amer Ahmed S.,Alsaba Mortadha

Publisher

Springer Science and Business Media LLC

Subject

General Energy,Geotechnical Engineering and Engineering Geology

Reference26 articles.

1. Al-Ameri KT, Jafar MSA, Pitman J (2011) Modeling hydrocarbon generations of the Basrah Oil Fields, Southern Iraq, based on Petromod with palynofacies evidences. AAPG search and discovery article #90124 © 2011 AAPG Annual Convention and Exhibition, April 10–13, 2011, Houston, Texas

2. Al-Dhafeeri AM, Nasr-El-Din HA, Seright RS, Sydansk RD (2005) High-permeability carbonate zones (Super-K) in Ghawar Field (Saudi Arabia): identified, characterized, and evaluated for gel treatments. Soc Pet Eng. https://doi.org/10.2118/97542-MS

3. Aldhaheri MN, Wei M, Bai B (2016) Comprehensive guidelines for the application of in-situ polymer gels for injection well conformance improvement based on field projects. Soc Pet Eng. https://doi.org/10.2118/179575-MS

4. Al-Hameedi AT, Dunn-Norman S, Alkinani HH, Flori RE, Hilgedick SA (2017a) Limiting drilling parameters to control mud losses in the Dammam formation, South Rumaila Field, Iraq. American rock mechanics association, August 28. http://www.onepetro.org/

5. Al-Hameedi AT, Dunn-Norman S, Alkinani HH, Flori RE, Hilgedick SA (2017b) Limiting drilling parameters to control mud losses in the Shuaiba formation, South Rumaila Field, Iraq. Paper AADE-17-NTCE-45, 2017 AADE national technical conference, Houston, Texas, April 11–12, 2017. http://www.AADE.org

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