Casing String Fatigue: No More

Author:

Noshi Christine Ikram1,Amani Mahmood2

Affiliation:

1. Texas A&M University

2. Texas A&M University Qatar

Abstract

Abstract Casing strings are an indispensable component in the design of any well and serve numerous purposes in oil and gas wells, constituting 20-30% of the total well cost. An alarming rate of failures, up to 50%, have been observed yet hushed under the rug, due to reputation, company profile, and privacy. In this work, The designed workflow follows 6 acceptance criteria, namely, (1) identification of potential risk factors amongst different exposures, (2) evaluation of the type and magnitude of the impact for each risk factor, (3) identification of the levels within each potential risk factor that impose the highest risk on casing failure, (4) acknowledgement of the depths most susceptible to casing failure, (5) prediction of the overall probability of casing failure given the information for pre-defined risk factors, and finally (6) have a scheme for mitigating casing failure. Case-control study design was adopted to test the association between the different exposures and the occurrence of casing failure. Impact type and magnitude of identified risk factors were determined through various statistical association measurements. Non-parametric survival analysis techniques were used for identification of the levels within each potential risk factor that impose the highest risk on casing failure and the depths most susceptible to casing failure. The scheme provided quantifiable numeric percentage increase/decrease for significant risk factors at lower, intermediate, and higher depth of casing. One importance of such conclusions is that although the conclusions coincide with already proven theories, unlike physics-based models, we did not need to acquire any domain knowledge to reach to those outputs. Moreover, in addition to exploring the significance of subcategories with respect to imposed risk, we managed to quantify those impacts which would be of great value when calibrating malpractices later using the proposed "correction-prediction" procedure.

Publisher

OTC

Reference22 articles.

1. Dusseault, M.B., Maury, V., San??lippo, F. et al. 2004. Drilling around salt: risks, stresses, and uncertainties. Presented at the 6th North America Rock Mechanics Symposium (NARMS), Houston, Texas, 5–9 June. ARMA-04-647.

2. Data Wrangling: Making Data Useful Again;Endel;IFAC-PapersOnLine,2015

3. Failure Rate Modelling for Reliability and Risk;Finkelstein,2008

4. Furche, T., Gottlob, G., Libkin, L., 2016. Data Wrangling for Big Data: Challenges and Opportunities. Proc. 19th International Conference on Extending Database Technology, Bordeaux, France, 15-18 March. http://doi.org/10.5441/002/edbt.2016.44.

5. Estimating the Dimension of a Model;Gideon;The annals of statistics,1978

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3