Skip to main navigation
Skip to search
Skip to main content
King Fahd University of Petroleum & Minerals Home
Help & FAQ
Link opens in a new tab
Search content at King Fahd University of Petroleum & Minerals
Home
Profiles
Research units
Projects
Research output
Prizes
Student theses
Real-Time GR logs Estimation While Drilling Using Surface Drilling Data; AI Application
Salaheldin Mahmoud Elkatatny
,
Ahmed Mohamed Farid Ibrahim
Department of Petroleum Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Real-Time GR logs Estimation While Drilling Using Surface Drilling Data; AI Application'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Earth and Planetary Sciences
Accuracy
14%
Artificial Intelligence
100%
Average
57%
Bit
14%
Correlation Coefficient
14%
Distance
14%
Drill Bit
14%
Drilling
100%
Engineers
14%
Error
57%
Forest
42%
Gamma Radiation
100%
Gas Reservoir
14%
Investigation
14%
Lithology
28%
Middle East
14%
Model
85%
Oil
14%
Parameter
14%
Petrography
28%
Proving
14%
Ratio
57%
Real Time
100%
Set
28%
Support Vector Machine
57%
Tools
14%
Train
14%
Training
14%
Utilization
100%
Engineering
Application
100%
Artificial Intelligence
100%
Artificial Intelligence Technique
14%
Correlation
14%
Data Entry
14%
Data Point
14%
Drill Bit
14%
Drilling
100%
Drilling Parameter
14%
Error
57%
Estimation
100%
Gamma Ray
100%
Gas Reservoir
14%
High Accuracy
14%
Logging While Drilling
28%
Measurement
42%
Models
85%
Oil Reservoir
14%
Performance
14%
Prediction
14%
Random Forest
42%
Support Vector Machine
57%
Surface
100%
Test Train
14%
Testing Set
14%