Lost circulation intensity characterization in drilling operations: Leveraging machine learning and well log data
Lost circulation is one of the important challenges in drilling operations and bears financial losses and operational risks. The prime causes of lost circulation are related to several geological parameters, especially in problem-prone formations. Herein, the approach of applying machine learning mo...
Saved in:
Main Author: | Ahmad Azadivash |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
|
Series: | Heliyon |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024170909 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Influence of the Transducer-Mounting Method on the Radiation Performance of Acoustic Sources Used in Monopole Acoustic Logging While Drilling
by: Jiale Wang, et al.
Published: (2025-01-01) -
Sequence-variable attention temporal convolutional network for volcanic lithology identification based on well logs
by: Hanlin Feng, et al.
Published: (2025-01-01) -
Investigation of Geological Diversity Based on the Degree of Sensitivity and the Amount of Equilibrium and Resilience of the Geosystem (Case study: The Eastern Kopet-Dagh Zone)
by: Sima Tavsoli, et al.
Published: (2022-11-01) -
Optimizing polycrystalline diamond compact bit selection and drilling parameters for deviated wells in the Majnoon Field, Iraq
by: Ahmed N. Al-Dujaili, et al.
Published: (2025-01-01) -
A comparative petrophysical evaluation of the Abu Roash, Bahariya, and Kharita reservoirs using well-logging data, East El-Fayoum, Egypt
by: Mohamed Osman Ebraheem, et al.
Published: (2025-01-01)