By Topic

Analysis of the method of Black box modeling of drill string dynamics by least squares method

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Fesmi Abdul Majeed ; Mechanical Engineering Department, Petroleum Institute, Abu Dhabi, UAE ; Hamad Karki ; Youssef Lotfy Abdel Magid ; Mansour Karkoub

The high dependency on oil and gas, leads the exploration and efficiency of the drilling process to be very demanding. Most of the tests conducted to study drill string nonlinearities and failures are performed by simulations on models derived for the purpose. Hence, mathematical modeling of a process is usually the first step taken to understand and analyze the dynamics of any process. Most of the mathematical models of the small scale experimental set ups of drilling rigs are developed by analytical modeling. This paper intends to project the use of Black box modelling procedure as a better, simpler and accurate alternate to analytical modeling. An auto regressive moving average exogenous (ARMAX) model is designed for the drill string experimental set up. The method of converging to the selected model using correlation tests and analyzing the prediction error graphs are discussed in the paper in detail. The least squares method provides unbiased estimates of the process model coefficients. The attraction of the method lies in the fact that the nonlinearities exhibited by the process will also be included in the model, without increasing the complexity or a change in the method used to converge to obtain the model.

Published in:

Mechanical and Electrical Technology (ICMET), 2010 2nd International Conference on

Date of Conference:

10-12 Sept. 2010