Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulation Article Swipe
Liangliang Ding
,
Miao Xian
,
Qiang Zhang
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1177/0036850420969577
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1177/0036850420969577
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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/0036850420969577
- https://journals.sagepub.com/doi/pdf/10.1177/0036850420969577
- OA Status
- diamond
- Cited By
- 7
- References
- 12
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3109058881
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3109058881Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1177/0036850420969577Digital Object Identifier
- Title
-
Prediction of casing wear depth and residual strength in highly-deviated wells based on modeling and simulationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-10-01Full publication date if available
- Authors
-
Liangliang Ding, Miao Xian, Qiang ZhangList of authors in order
- Landing page
-
https://doi.org/10.1177/0036850420969577Publisher landing page
- PDF URL
-
https://journals.sagepub.com/doi/pdf/10.1177/0036850420969577Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://journals.sagepub.com/doi/pdf/10.1177/0036850420969577Direct OA link when available
- Concepts
-
Casing, Residual, Drilling, Residual strength, Finite element method, Materials science, Structural engineering, Petroleum engineering, Mechanical engineering, Geotechnical engineering, Engineering, Composite material, Computer science, AlgorithmTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 4, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
12Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2020-10-01 |
| publication_year | 2020 |
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