Investigation on dynamics of drillstring systems from random viewpoint

Qiu, Hongyuan (2023) Investigation on dynamics of drillstring systems from random viewpoint. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Drillstrings are one of the critical components used for exploring and exploiting oil and gas reservoirs in the petroleum industry. As being very long and slender, the drillstring experiences various vibrations during the drilling operation, and these vibrations are random in essence. The first part of the thesis focuses on stochastic stick-slip dynamics of the drill bit by a finite element model and a single degree of freedom drillstring model in Chapters 3 and 4, respectively. In the single degree of freedom model, the path integration (PI) method is firstly used to obtain the probability density evolution of the dynamic response. Then Monte Carlo (MC) simulation is used for validating PI results and conducting the parametric study. The second step of my research is to study the stochastic dynamics of a vertical, multiple degrees of freedom drillstring system. The work of this part is presented in Chapter 5. The novelty of this work relies on the fact that it is the first time that the statistic linearization method is applied to a drillstring system in the bit-rock interaction to find an equivalent linear dynamic system which is then solved with the stochastic Newmark algorithm. After that, the stick-slip and bit-bounce phenomena are analyzed from random viewpoint. The third step of my research move on to directional drilling. A static study of directional drillstring from random viewpoint is presented in Chapter 6. The finite element method (FEM) based on the soft string model is employed and built. Then two strategies are taken to model the random component for hoisting drag calculation. The purpose of this work is to analyze the effects of the random component on hoisting drag calculation by the MC simulation method.

Item Type: Thesis (Doctoral (PhD))
Item ID: 15832
Additional Information: Includes bibliographical references (pages 173-199)
Keywords: dynamics, drillstring, random
Department(s): Engineering and Applied Science, Faculty of
Date: May 2023
Date Type: Submission
Digital Object Identifier (DOI):
Library of Congress Subject Heading: Drill stem; Dynamics; Hydrocarbon reservoirs; Monte Carlo method; Stochastic analysis

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