首页|Prediction models of burst strength degradation for casing with considerations of both wear and corrosion

Prediction models of burst strength degradation for casing with considerations of both wear and corrosion

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Casing wear and casing corrosion are serious problems affecting casing integrity failure in deep and ultra-deep wells.This paper aims to predict the casing burst strength with considerations of both wear and corrosion.Firstly,the crescent wear shape is simplified into three categories according to common mathematical models.Then,based on the mechano-electrochemical(M-E)interaction,the prediction model of corrosion depth is built with worn depth as the initial condition,and the prediction models of burst strength of the worn casing and corroded casing are obtained.Secondly,the accuracy of different prediction models is validated by numerical simulation,and the main influence factors on casing strength are obtained.At last,the theoretical models are applied to an ultra-deep well in Northwest China,and the dangerous well sections caused by wear and corrosion are predicted,and the corrosion rate threshold to ensure the safety of casing is obtained.The results show that the existence of wear defects results in a stress concentration and enhanced M-E interaction on corrosion depth growth.The accuracy of different mathematical models is different:the slot ring model is most accurate for predicting corrosion depth,and the eccentric model is most accurate for predicting the burst strength of corroded casing.The burst strength of the casing will be overestimated by more than one-third if the M-E interaction is neglected,so the coupling effect of wear and corrosion should be sufficiently considered in casing integrity evaluation.

Deep wellCasing integrityCasing wearCasing corrosionBurst strength

Jie-Li Wang、Wen-Jun Huang、De-Li Gao

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MOE Key Laboratory of Petroleum Engineering,China University of Petroleum,Beijing,102249,China

State Key Laboratory of Petroleum Resources and Prospecting,China University of Petroleum,Beijing,102249,China

国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金Science Foundation of China University of Petroleum,Beijing

52222401522340025190431751821092ZX20230083

2024

石油科学(英文版)
中国石油大学(北京)

石油科学(英文版)

EI
影响因子:0.88
ISSN:1672-5107
年,卷(期):2024.21(1)
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