Rate of penetration prediction in drilling wells from the Hassi Messaoud oil field (SE Algeria): Use of artificial intelligence techniques and environmental implications-Reference-Cited by-同舟云学术

Rate of penetration prediction in drilling wells from the Hassi Messaoud oil field (SE Algeria): Use of artificial intelligence techniques and environmental implications

Published:2022 Issue: Volume: Page:427-439
ISSN:
Container-title:Computers in Earth and Environmental Sciences
language:
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Author:

Ameur-Zaimeche Ouafi,Kechiched Rabah,Aouam Charaf-Eddine

Publisher

Elsevier

Reference65 articles.

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1. Modelling and Simulating Eulerian Venturi Effect of SBM to Increase the Rate of Penetration with Roller Cone Drilling Bit;Energies;2023-05-18

2. Integrating drilling parameters and machine learning tools to improve real-time porosity prediction of multi-zone reservoirs. Case study: Rhourd Chegga oilfield, Algeria;Geoenergy Science and Engineering;2023-04

3. Real-time porosity prediction using gas-while-drilling data and machine learning with reservoir associated gas: Case study for Hassi Messaoud field, Algeria;Marine and Petroleum Geology;2022-06