PRH22.1 - Digital Technologies for the Coastal and Oceanic Ecosystem in the Oil, Gas, and Biofuel Industry

• Grant number: 24/10523-5
• Support Opportunities: Regular Research Grants
• Start date: July 01, 2024
• End date: August 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Emanuel da Silva Diaz Estrada
• Grantee: Emanuel da Silva Diaz Estrada
• Host Institution: Centro de Ciências Computacionais. Universidade Federal do Rio Grande (FURG). Campus Carreiros. Rio Grande , SP, Brazil
• Associated researchers: Paula Spotorno de Oliveira

Abstract

FURG, a university focused on coastal and oceanic ecosystems, began its involvement with the Oil and Gas industry during the 1990s. For 17 years, it promoted the PRH-ANP 27 program, training students with a focus on challenges and applications related to the Oil, Natural Gas, and Fuel (ONGF) industry. In recent decades, scientific and technological advances in modeling, computing, automation, and data science have allowed for better exploration and understanding of coastal and oceanic phenomena. In the early 2010s, three new lines were added to the PRH: Computational Modeling, Computing, and Automation. Initially having a purely environmental emphasis, the PRH transformed into a pioneering research, technological development, and training center in Marine Technologies in Brazil. In 2019, an agreement was signed for the implementation of the "Digital Technologies for Coastal and Oceanic Ecosystems in the ONGF Industry" program, PRH-22. Emphasizing digital technologies and automation focused on the sea, this new project aimed to reedit PRH-27 as a proposal capable of pioneeringly training professionals in Brazil with outstanding experience in digital and automation technologies for the sea. This interdisciplinary training, involving the computational modeling of chemical, physical, biological, and geological oceanographic phenomena, as well as the manipulation and development of digital and automation devices for the sea, has enabled professionals with unique expertise in the country to work in various areas associated with oil exploration, natural gas transportation, renewable energies, submarine systems, new materials, among other important segments of the ONGF Industry. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DE JESUS, JUNIOR COSTA; KICH, VICTOR AUGUSTO; KOLLING, ALISSON HENRIQUE; GRANDO, RICARDO BEDIN; GUERRA, RODRIGO DA SILVA; DREWS-JR, PAULO LILLES JORGE. Image-based Mapless Navigation of a Hybrid Aerial-Underwater Vehicle using Prioritized Deep Reinforcement Learning. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, v. 111, n. 1, p. 13-pg., 2025-02-13. (24/10523-5)

SCHEIN, TATIANA TAIS; DE ALMEIRA, GUSTAVO PEREIRA; BRIAO, STEPHANIE LOI; DE BEM, RODRIGO ANDRADE; DE OLIVEIRA, FELIPE GOMES; DREWS-, PAULO L. J., JR.. UDBE: Unsupervised Diffusion-based Brightness Enhancement in Underwater Images. 2024 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, v. N/A, p. 7-pg., 2024-01-01. (24/10523-5)