Survival analysis: The statistically rigorous method for analyzing electrical submersible pump system performance

被引：0
作者：
Schlumberger-Doll Research, Ridgefield, CT, United States [1 ]
不详 [2 ]
不详 [3 ]
不详 [4 ]
不详 [5 ]
机构：
[1] Schlumberger-Doll Research, Ridgefield, CT
[2] U. of the West of England, Bristol
[3] Uncertainty Risk and Optimization Program, Schlumberger-Doll Research, Ridgefield, CT
[4] Mathematics and Modeling Dept., Ridgefield, CT
来源：
SPE Prod. Oper. | 2006年 / 4卷 / 492-504期
关键词：
Submersible pumps;
D O I：
10.2118/96722-pa
中图分类号：
学科分类号：
摘要：
A rigorous statistical methodology using survival analysis (SA) was developed and applied to electrical submersible pump (ESP) system performance data. The approach extracts unbiased information from performance data and permits lifetime modeling, with parameter combinations employing all available data. The analysis explicitly accounts for ESPs that are still operational at the time of the study, thus removing a historical source of statistical bias. The analysis uses Kaplan-Meier (KM) (Kaplan and Meier 1958) and Cox proportional hazards (CPHs) (Cox 1972) modeling to determine statistical significance of explanatory variables (EVs). Methods developed to facilitate EV factor collapsing are also discussed (the partitioning of levels of each factor into nonempty subsets of statistically similar response), so that an acceptable degree of parsimony is achieved. Essential definitions necessary for preliminary data structure are also covered. We demonstrate the practical utility of this methodology on a comprehensive data set to enable unbiased and conclusive appraisal of ESP performance, thereby resolving a common concern about comparative-system reckoning. The paper concludes that SA, suitably applied to properly censored data, is essentially the only reliable method of evaluating ESP system performance (and other types of time-to-event data). Copyright © 2006 Society of Petroleum Engineers.
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页码：492 / 504
页数：12
相关论文
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