Pedro Esteves Aranha

Bachelor's and master's degree in Chemistry from the Federal University of São Carlos (UFSCar) and PhD in Mining Engineering from the Polytechnic School of the University of São Paulo (USP), with a thesis focused on the development of data-based methodologies for anomaly prediction and ensuring well integrity in offshore oil production using machine learning. Also holds a specialization in Business Intelligence from PUC-Rio.Joined Petrobras in 2007 and worked until 2015 at the Research Center (CENPES) on projects in the area of Well Technology and Engineering. Since 2015, has been working as a technical consultant in the corporate area of Well Construction, focusing on digital systems and well automation. Has over 15 years of experience in the development of scientific software, well design systems, and solutions for real-time data monitoring and analysis (streaming analytics). Stands out in the development of digital twins and artificial intelligence and machine learning (AI/ML) models for monitoring the integrity of subsea wells during production. Author of approximately 20 technical publications for the industry, focusing on software development and engineering analysis. (Source: Lattes Curriculum)