Brazilian Journal of Probability and Statistics

Prediction of failure probability of oil wells

João B. Carvalho, Dione M. Valença, and Julio M. Singer

Full-text: Open access

Abstract

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.

Article information

Source
Braz. J. Probab. Stat., Volume 28, Number 2 (2014), 275-287.

Dates
First available in Project Euclid: 4 April 2014

Permanent link to this document
https://projecteuclid.org/euclid.bjps/1396615441

Digital Object Identifier
doi:10.1214/12-BJPS206

Mathematical Reviews number (MathSciNet)
MR3189498

Zentralblatt MATH identifier
1319.62228

Keywords
Accelerated failure time models correlated data empirical Bayes predictors empirical best linear unbiased predictors random effects models

Citation

Carvalho, João B.; Valença, Dione M.; Singer, Julio M. Prediction of failure probability of oil wells. Braz. J. Probab. Stat. 28 (2014), no. 2, 275--287. doi:10.1214/12-BJPS206. https://projecteuclid.org/euclid.bjps/1396615441


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