IEEE Access (Jan 2020)

Incorporation of Frailties Into a Non-Proportional Hazard Regression Model and Its Diagnostics for Reliability Modeling of Downhole Safety Valves

  • Francisco Louzada,
  • Jose Alberto Cuminato,
  • Oscar Mauricio Hernandez Rodriguez,
  • Vera L. D. Tomazella,
  • Eder Angelo Milani,
  • Paulo Henrique Ferreira,
  • Pedro Luiz Ramos,
  • Gustavo Bochio,
  • Ivan Carlos Perissini,
  • Oilson Alberto Gonzatto Junior,
  • Alex Leal Mota,
  • Luis Felipe Acuna Alegria,
  • Danilo Colombo,
  • Paulo Guilherme Oliveira De Oliveira,
  • Hugo Francisco Lisboa Santos,
  • Marcus Vinicius De Campos De Magalhaes

DOI
https://doi.org/10.1109/ACCESS.2020.3040525
Journal volume & issue
Vol. 8
pp. 219757 – 219774

Abstract

Read online

In this paper, our proposal consists of incorporating frailty into a statistical methodology for modeling time-to-event data, based on non-proportional hazards regression model. Specifically, we use the generalized time-dependent logistic (GTDL) model with a frailty term introduced in the hazard function to control for unobservable heterogeneity among the sampling units. We also add a regression in the parameter that measures the effect of time, since it can directly reflect the influence of covariates on the effect of time-to-failure. The practical relevance of the proposed model is illustrated in a real problem based on a data set for downhole safety valves (DHSVs) used in offshore oil and gas production wells. The reliability estimation of DHSVs can be used, among others, to predict the blowout occurrence, assess the workover demand and aid decision-making actions.

Keywords