Return to search

Stick-Slip Prevention of Drill Strings Using Nonlinear Model Reduction and Nonlinear Model Predictive Control

<p>The main focus of this thesis is aspects in the development of a system for prevention of stick-slip oscillations in drill strings that are used for drilling oil wells. Stick-slip is mainly caused by elasticity of the drill string and changing frictional forces at the bit; static frictional forces are higher than the kinetic frictional forces which make the bit act in a manner where it sticks and then slips, called stick-slip. Stick-slip leads to excessive bit wear, premature tool failures and a poor rate of penetration. A model predictive controller (MPC) should be a suitable remedy for this problem; MPC has gained great success in constrained control problems where tight control is needed. Friction is a highly nonlinear phenomenon and for that reason is it obvious that a nonlinear model is preferred to be used in the MPC to get prime control. Obviously it is of great importance that the internal model used in the MPC is of a certain quality, and as National Oilwell Varco (NOV) has developed a nonlinear drill string model in Simulink, it will be useful to check over this model. This model was therefore verified with a code-to-code comparison and validated using logging data provided from NOV. As the model describing the dynamics of the drill string is somewhat large, a nonlinear model reduction is needed due to the computational complexity of solving a nonlinear model predictive control problem. This nonlinear model reduction is based on the technique of balancing the empirical Gramians, a method that has proven to be successful for a variety of systems. A nonlinear drill string model has been reduced and implemented to a nonlinear model predictive controller (NMPC) and simulated for different scenarios; all proven that NMPC is able to cope with the stick-slip problem. Comparisons have been made with a linear MPC and an existing stick-slip prevention system, SoftSpeed, developed by National Oilwell Varco.</p>

Identiferoai:union.ndltd.org:UPSALLA/oai:DiVA.org:ntnu-9112
Date January 2010
CreatorsJohannessen, Morten Krøtøy, Myrvold, Torgeir
PublisherNorwegian University of Science and Technology, Department of Engineering Cybernetics, Norwegian University of Science and Technology, Department of Engineering Cybernetics, Institutt for teknisk kybernetikk
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, text

Page generated in 0.0012 seconds