Enhancing digital twin reliability using FAIR principles and data quality assessment

Miguel Burg Demay, Luiz Eduardo de Farias, Gustavo Donatelli, Andre Luiz Meira de Oliveira

Abstract

The use of digital tools such as digital twins is spreading throughout the O&G sector. For integrity management, digital models of relevant asset degradation phenomena have been used to estimate and predict its health, aiming to improve maintenance planning and to provide information about the risk of failure and its evolution over time. The input data of models for O&G integrity monitoring are commonly found in different databases and present very different characteristics, such as sampling rate, temporal stability and variability, influencing the data quality in different ways. This work addresses the use of FAIR principles and data quality assessment for O&G asset integrity management. A brief review of established concepts is discussed, and a practical case study is presented, which illustrates the very important role that data quality assessment and the use of FAIR principles play in digital models’ reliability.

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IMEKO-TC6-2025-068.pdf

DOI

10.21014/tc6-2025.068

IMEKO TC

TC6 - Digitalization

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