Development and Verification of a Real-Time Drill Bit Wear Prediction Module

2010 ◽  
Author(s):  
Behrad Rashidi ◽  
Geir Hareland ◽  
Mazeda Tahmeen ◽  
M. Anisimov ◽  
S. Abdorazakov
Keyword(s):  
Real Time ◽  
Drill Bit ◽  
Wear Prediction ◽  
Prediction Module ◽  
Bit Wear

New Approach in Real-Time Bit Wear Prediction

2010 ◽  
Author(s):  
Behrad Rashidi ◽  
Geir Hareland ◽  
Andrew Wu
Keyword(s):  
Real Time ◽  
Wear Prediction ◽  
New Approach ◽  
Bit Wear

Real Time Application of Bearing Wear Prediction Model Using Intelligent Drilling Advisory System

2011 ◽  
Author(s):  
Mazeda Tahmeen ◽  
Geir Hareland ◽  
Zebing Wu
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Intelligent System ◽  
International Association ◽  
Oil And Gas Industry ◽  
Wear Prediction ◽  
Gas Drilling ◽  
Advisory System ◽  
Pull Out ◽  
Prediction Module

The real-time prediction of bearing wear for roller cone bits using the Intelligent Drilling Advisory system (IDAs) may result in better performance in oil and gas drilling operations and reduce total drilling cost. IDAs is a real time engineering software and being developed for the oil and gas industry to enhance the performance of complex drilling processes providing meaningful analysis of drilling operational data. The prediction of bearing wear for roller cone bits is one of the most important engineering modules included into IDAs to analyze the drilling data in real time environment. The ‘Bearing Wear Prediction’ module in IDAs uses a newly developed wear model considering drilling parameters such as, weight on bit (WOB), revolution per minute (RPM), diameter of bit and hours drilled as a function of IADC (International Association of Drilling Contractors) bit bearing wear. The drilling engineers can evaluate bearing wear status including cumulative wear of roller cone bit in real time while drilling, using this intelligent system and make a decision on when to pull out the bit in time to avoid bearing failure. The wear prediction module, as well as the intelligent system has been successfully tested and verified with field data from different wells drilled in Western Canada. The estimated cumulative wears from the analysis match close with the corresponding field values.

scholarly journals Real-time bit wear prediction using mud logger data with mathematical approaches

2019 ◽  
Vol 10 (2) ◽  
pp. 587-594
Author(s):  
Hongpeng Yang ◽  
Hongkai Zhao ◽  
Suresh Kottapurath
Keyword(s):  
Real Time ◽  
Wear Prediction ◽  
Bit Wear
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