Team

Shell has been present in Brazil since 1913. With the main objective to meet the energy needs of society today and in the future, acting responsibly in the economic, environmental and social spheres.
Shell is one of the largest companies in the world in the area of Exploration and Production, Shell in Brazil has one of its biggest technological challenges in the Upstream segment.
Shell was the first private company to produce oil in the Campos Basin after the market was opened. Our deepwater projects include Parque das Conchas, Bijupirá and Salema, Libra and participation in 5 discoveries in the Santos Basin (Lula, Iracema, Sapinhoá, Lapa, and the former large area of Iara, currently Berbigão, Sururu, and Atapú West).

The Computational Methods Laboratory in Engineering (LAMCE) of COPPE/UFRJ is represented in the second stage of the Project Azul by its Nucleus of Environmental Modeling with 12 years researching Environmental Computational Modeling. The main objectives of the group are Academic and Professional Training and the idealization and Execution of R&D Projects.
At this stage of Project Azul, the laboratory will be responsible for the development of a high resolution spatial oceanographic and meteorological forecasting system for the Libra field, which includes the implementation of atmospheric, oceanic and operational assimilation models and propagation of wind-generated surface gravity waves.

PROOCEANO is an oceanographic technology company founded in 2004 in Rio de Janeiro and currently provides numerical modeling services, data collection and environmental analysis in various parts of the world. In the Project Azul, PROOCEANO is responsible for the collection and analysis of data and its operational supply for assimilation in the forecast models. In addition, PROOCEANO has developed and maintains the storage and visualization system of the collected data and results of the numerical forecast in a web page.
At this stage of the project, ocean gliders, mooring lines, and autonomous surface vehicles will be used collecting data aimed for its assimilation in numerical models, aiming to increase the reliability of the predictions and safety of offshore operations.