Type | Value | Early-bird (November 22th 2024) |
---|---|---|
Associate SBGf | R$ 2,642.00 USD 500 |
R$ 2,113.00 USD 400 |
Non-Member SBGf | R$ 3,170.00 USD 600 |
R$ 2,642.00 USD 500 |
Undergraduate Student (Associate) | R$ 660.00 USD 125 |
R$ 660.00 USD 125 |
Undergraduate Student (Non-Member) | R$ 660.00 USD 125 |
R$ 660.00 USD 125 |
Machine Learning (ML) is a field of Artificial Intelligence that has experienced rapid growth in the last ten years across diverse industries, including communications, financial services, security, transportation, and others. Applications of ML have produced dramatic results, enabling new opportunities and business models. Driving the adoption of ML are the volume and velocity of information, the application of deep learning techniques, and economic computing power. Applied to geoscience, these data-driven approaches are complementary tools for physical-based modeling, simulation, and inversion. ML facilitates an understanding of complex relationships among a large and diverse set of variables, valuable for generating and validating models and answering scientific questions. ML can enable fast high-quality decisions in the oil & gas industry, an essential component for viability given the industrys long-term outlook. Geoscience datasets are among the largest volumes of data in the industry. The data has a wide spectrum of properties with scales varying over many orders of magnitude. The workshop will allow the attendees to evaluate and compare the best developments of ML technology that have occurred in industry over the last five years.
Opening of Call for Abstracts: 19/07/2024
Abstracts Submission Deadline: 16/10/2024
Notification to authors: 30/10/2024
Presenter confirmation: 15/11/2024
Final Technical Program: 22/11/2024
Registration Early Open: 07/10/2024
Registration Early ends: 14/11/2024
Geocientista sênior com mais de 20 anos de experiência em exploração de hidrocarbonetos, atuando em projetos convencionais e não convencionais, tanto em ambientes onshore quanto offshore. Possui um histórico sólido em empresas de pequeno, médio e grande porte, como Devon, HRT/PRIO, Murphy e Total. Com PhD em Geologia pela Universidade de Houston, mestrado em Geofísica pelo Observatório Nacional e graduação em Oceanografia pela UERJ, detém um conhecimento abrangente das geociências. Sua experiência inclui projetos em diversas bacias sedimentares, como Parnaíba, Solimões, Barnett, Barreirinhas, Campos, Nigéria, Angola, Namíbia e Golfo do México. Global Technical Advisor na CMG/Bluware, nos últimos seis anos, tem se dedicado à aplicação de técnicas de inteligência artificial e big data para a análise de dados geológicos, buscando soluções inovadoras para desafios complexos na indústria de petróleo e gás.
Claudio Guerra has major in Geology from the Federal University of Rio de Janeiro, Masters in Petroleum Sciences from the University of Campinas and PhD in Geophysics from Stanford University. He's been at Petrobras since 1990 and his currently position is senior advisor in geophysics.
I am a Geophysicist with experience in seismic data processing, reservoir characterization, and cloud geophysical data ingestion. My expertise includes knowledge of time processing for standard marine streamer data from Santos and Campos basins; seismic interpretation and reservoir characterization of the Búzios Field through the application of seismic attributes and performance of seismic facies classification; and management of geophysical data in the AWS cloud using the OSDU® Data Platform. Both seismic processing and interpretation experiences aimed Brazilian presalt carbonate reservoir targets.
Geologist with specialization in Geophysics, with more than 25 years of experience in the area of geophysics applied to Petroleum, having worked in the areas of seismic acquisition, seismic processing and E&P technology and data management. I currently work as leader of the OSDU project in the Petrobras Exploration area
Rodrigo Portugal is a geophysicist with extensive experience in the E&P industry, specializing in seismic data analysis, processing, and reservoir characterization. He holds a Ph.D. in Applied Mathematics from UNICAMP, where his research focused on advanced mathematical modeling for geophysical applications. With over two decades of experience, Rodrigo has contributed to numerous exploration and reservoir geophysics projects. He currently serves as a Geosciences Advisor at Halliburton.
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