Please use this identifier to cite or link to this item: https://repositorio.ufrn.br/jspui/handle/123456789/27094
Title: Prediction of failure probability of oil wells
Authors: Carvalho, João B.
Valença, Dione M.
Singer, Julio M.
Keywords: Accelerated failure time models;Correlated data;Empirical Bayes predictors;Empirical best linear unbiased predictors;Random effects models
Issue Date: 2014
Publisher: Brazilian Statistical Association
Citation: CARVALHO, João B.; VALENÇA, Dione M.; SINGER, Julio M. Prediction of failure probability of oil wells. Brazilian Journal of Probability and Statistics , v. 28, n.2 p. 275-287, 2014. Disponível em:< https://projecteuclid.org/euclid.bjps/1396615441>. Acesso em: 06 dez. 2017.
Portuguese 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 aWeibull 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.
URI: https://repositorio.ufrn.br/jspui/handle/123456789/27094
ISSN: 0103-0752
Appears in Collections:CCET - DEST - Artigos publicados em periódicos

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