Reliability assessment of ultra-deep oil and gas wellbore casing using data statistics and numerical simulations

Journal Article (2020)
Author(s)

Shangyu Yang (State Key Laboratory of Performance and Structural Safety for Petroleum Tubular Goods and Equipment Materials)

Renren Zhang (Xi'an University of Architecture and Technology)

Jianjun Wang (State Key Laboratory of Performance and Structural Safety for Petroleum Tubular Goods and Equipment Materials)

Xinhong Li (Xi'an University of Architecture and Technology)

Heng Fan (Xi'an Shiyou University)

Ming Yang (TU Delft - Technology, Policy and Management)

Research Group
Safety and Security Science
DOI related publication
https://doi.org/10.1016/j.jlp.2020.104369 Final published version
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Publication Year
2020
Language
English
Research Group
Safety and Security Science
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Journal title
Journal of Loss Prevention in the Process Industries
Volume number
69
Article number
104369
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Institutional Repository
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Abstract

Ultra-deep oil and gas wells have become a new development trend in onshore oil and gas exploitation. However, Ultra-deep oil and gas wellbore casing is with high failure risk due to the harsh environment. It is essential to evaluate the reliability of wellbore casing. This paper assesses the operational reliability of wellbore casing using data statistics and numerical simulation. Firstly, the theoretical model for reliability analysis of wellbore casing is established, and the variables in the model are determined, including rock mechanics, cement ring, and casing string strength factors. Subsequently, considering the random distribution of model variables, many statistics and analyses are performed to determine the distribution parameters of the model variables. Eventually, Monte Carlo based numerical simulations are carried out to obtain the residual strength distribution and the reliability of wellbore casing. The production casing in the ultra-deep well with a depth of 6.5 km in China as an industrial case is used to illustrate the present study. It is observed that this study can be useful to guide a more accurate assessment of the reliability of ultra-deep wellbore casing.

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