Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

PetroBayes' Modules for Reliability Assessment for Oil and Gas Industry

Paulo Gabriel Siqueira1,a, Thais Lucas1,b, Beatriz Cunha1,c, João Mateus Santana1,d, Rafael Azevedo1,e, Marcio Moura1,g, Isis Lins1,g, Caio Souto Maior1,h and Everton Lima2

1Center for Risk Analysis, Reliability Engineering and Environmental Modeling (CEERMA), Industrial Engineering Department, Universidade Federal de Pernambuco, Brazil.

2Petrobras S.A., Brazil.


PetroBayes is user-friendly software that performs Bayesian reliability estimation. The software comprises three main modules that can provide the reliability measures. The first, the Bayesian module, enables the user to assess the variability distribution of non-homogenous failure data. In this module, one can obtain a prior distribution for the reliability measure of interest based on generic data; the posterior distribution is a result of the update procedure with specific information of the system of interest. The Statistical module can fit data into distributions (e.g., the duration of maintenance actions) and perform statistical tests (e.g., goodness of fit). The Availability module can be fed with data from the previous models to build a continuous time homogenous semi Markov process (CTHSMP) and estimate the system's availability. The failure rate can be derived from the Bayesian module, while the repair rate, from the Statistical module in a straightforward workflow. Note that these rates need not to be constant (i.e., exponentially distributed), thus allowing a more robust assessment. All the results can be displayed to the user, be given in written reports and images. The software can be hosted on a remote server, minimizing the usage of the user's own computation resources. We illustrated the use of the Availability module considering generic databases.

Keywords: Bayesian analysis, Weibull distribution, Availability assessment, Web-based app, Oil & Gas industry.

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