Prediction of failure probability of oil wells
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...
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| Principais autores: | , , |
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| Formato: | article |
| Idioma: | pt_BR |
| Publicado em: |
Brazilian Statistical Association
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| Assuntos: | |
| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/27094 |
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| Resumo: | 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. |
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