Open Access
May 2014 Prediction of failure probability of oil wells
João B. Carvalho, Dione M. Valença, Julio M. Singer
Braz. J. Probab. Stat. 28(2): 275-287 (May 2014). DOI: 10.1214/12-BJPS206


We consider parametric accelerated failure time models with random effects to predict the probability of possibly correlated failures occurring in oil wells. In this context, we first consider empirical Bayes predictors (EBP) based on a Weibull distribution for the failure times and on a Gaussian distribution for the random effects. We also obtain empirical best linear unbiased predictors (EBLUP) using a linear mixed model for which the form of the distribution of the random effects is not specified. We compare both approaches using data obtained from an oil-drilling company and suggest how the results may be employed in designing a preventive maintenance program.


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João B. Carvalho. Dione M. Valença. Julio M. Singer. "Prediction of failure probability of oil wells." Braz. J. Probab. Stat. 28 (2) 275 - 287, May 2014.


Published: May 2014
First available in Project Euclid: 4 April 2014

zbMATH: 1319.62228
MathSciNet: MR3189498
Digital Object Identifier: 10.1214/12-BJPS206

Keywords: accelerated failure time models , correlated data , empirical Bayes predictors , empirical best linear unbiased predictors , random effects models

Rights: Copyright © 2014 Brazilian Statistical Association

Vol.28 • No. 2 • May 2014
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