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Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation
Casing wear is a serious problem in highly-deviated wells because serious wear will lead to casing deformation, drilling tool sticking and failure of subsequent operations. The purpose of this paper is to predict casing wear depth and evaluate its effect on casing strength degradation in highly-devi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450893/ https://www.ncbi.nlm.nih.gov/pubmed/33225844 http://dx.doi.org/10.1177/0036850420969577 |
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author | Ding, Liangliang Xian, Miao Zhang, Qiang |
author_facet | Ding, Liangliang Xian, Miao Zhang, Qiang |
author_sort | Ding, Liangliang |
collection | PubMed |
description | Casing wear is a serious problem in highly-deviated wells because serious wear will lead to casing deformation, drilling tool sticking and failure of subsequent operations. The purpose of this paper is to predict casing wear depth and evaluate its effect on casing strength degradation in highly-deviated well drilling operation. Special attention has been given to the algorithm to achieve the prediction and evaluation. The effect of tool joint on contact force distribution is considered in contact force model. Then a wear depth prediction model and its solution method are proposed based on crescent-shaped wear morphology and wear-efficiency model. Besides, strength degradation of worn casing is analyzed in bipolar coordinate system and the model is verified by finite element method. Therefore, the technology of casing wear prediction and residual strength evaluation is completed systematically. Then, to apply casing wear prediction and residual strength evaluation technologies to an actual highly-deviated well, casing wear experiment and friction coefficient experiment are carried out to obtain wear coefficient and friction coefficient. Finally, based on the established models as well as experimental results, the distribution of casing wear is predicted and residual strength is evaluated. The method presented in this paper will contribute greatly to casing wear prediction and evaluation in highly-deviated wells. |
format | Online Article Text |
id | pubmed-10450893 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-104508932023-08-26 Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation Ding, Liangliang Xian, Miao Zhang, Qiang Sci Prog Article Casing wear is a serious problem in highly-deviated wells because serious wear will lead to casing deformation, drilling tool sticking and failure of subsequent operations. The purpose of this paper is to predict casing wear depth and evaluate its effect on casing strength degradation in highly-deviated well drilling operation. Special attention has been given to the algorithm to achieve the prediction and evaluation. The effect of tool joint on contact force distribution is considered in contact force model. Then a wear depth prediction model and its solution method are proposed based on crescent-shaped wear morphology and wear-efficiency model. Besides, strength degradation of worn casing is analyzed in bipolar coordinate system and the model is verified by finite element method. Therefore, the technology of casing wear prediction and residual strength evaluation is completed systematically. Then, to apply casing wear prediction and residual strength evaluation technologies to an actual highly-deviated well, casing wear experiment and friction coefficient experiment are carried out to obtain wear coefficient and friction coefficient. Finally, based on the established models as well as experimental results, the distribution of casing wear is predicted and residual strength is evaluated. The method presented in this paper will contribute greatly to casing wear prediction and evaluation in highly-deviated wells. SAGE Publications 2020-11-22 /pmc/articles/PMC10450893/ /pubmed/33225844 http://dx.doi.org/10.1177/0036850420969577 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Article Ding, Liangliang Xian, Miao Zhang, Qiang Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
title | Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
title_full | Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
title_fullStr | Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
title_full_unstemmed | Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
title_short | Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
title_sort | prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450893/ https://www.ncbi.nlm.nih.gov/pubmed/33225844 http://dx.doi.org/10.1177/0036850420969577 |
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