Prediction of failure probability of oil wells

• Autor(a) principal: Carvalho, João B.
• Data de Publicação: 2014
• Outros Autores: Valença, Dione M., Singer, Julio M.
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/27094
• topic: Accelerated failure time models; Correlated data; Empirical Bayes predictors; Empirical best linear unbiased predictors; Random effects models

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.