Digital Twin Applied to Oil and Gas Production: A Path to Performance Improvement

Iara Tammela (), Rodolfo Cardoso (), Dalton Garcia Borges de Souza (), Luiz Antonio de Oliveira Chaves (), Ana Carolina Ribeiro Duarte Hashimoto (), Andre Luis Severino Abrego () and Carlos Alexandre Peixoto Costa ()
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Iara Tammela: Fluminense Federal University (UFF)
Rodolfo Cardoso: Fluminense Federal University (UFF)
Dalton Garcia Borges de Souza: Fluminense Federal University (UFF)
Luiz Antonio de Oliveira Chaves: Fluminense Federal University (UFF)
Ana Carolina Ribeiro Duarte Hashimoto: Fluminense Federal University (UFF)
Andre Luis Severino Abrego: CENPES/Petrobras, Av. Horácio Macedo, 950 - Cidade Universitária
Carlos Alexandre Peixoto Costa: CENPES/Petrobras, Av. Horácio Macedo, 950 - Cidade Universitária

A chapter in Proceedings of the International Conference on Industrial Logistics (ICIL) 2025, 2026, pp 3-10 from Springer

Abstract: Abstract Simulation models are widely employed to evaluate complex systems and test new operational strategies with lower capital investment. Among emerging technologies, Digital Twins (DTs) stand out by integrating simulation with real-time data to support dynamic decision-making. In oil and gas production, particularly within Intelligent Completion Systems (ICS), DTs enable advanced monitoring, predictive analysis, and proactive maintenance. The objective of this article is to present the initial results of a larger research project aimed at developing a Digital Twin model for the ICS to analyze well control operations for simulated scenarios. The first findings show the potential of DTs as a strategic tool for increasing efficiency, reducing costs, and supporting supply chain resilience in high-risk industrial sectors.

Keywords: Digital Twin; Intelligent Completion Systems; Oil and Gas; Supply Chain Management (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-14489-8_1

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