Artificial Intelligence for Oil and Gas Without the Hype

Sunday, 28 September Monday, 29 September 2025, 9:00 a.m.–5:00 p.m.  |  Brazil

short course image

Course Content

This short course is a broad and principled, no frills, exploration of the main kinds of tasks which fall under the umbrella of Artificial Intelligence and Machine Learning. Upon completion, attendees will understand not only what AI/ML algorithms can do, but also their underlying assumptions and limitations. They will recognize the important role of the domain expert in its applications, especially considering the kinds of incomplete, biased and interpreted data so common in the geosciences in general and the Oil & Gas industry in particular.

Topics

  • Supervised vs unsupervised learning
  • Clustering, Classification and Regression
  • Under/Overfitting
  • Train, test and validation dataset segmentation
  • Model training and selection

Who Should Attend: Geologists, Geophysicists, Petroleum Engineers, and other professionals and students in the geosciences intrigued by AI/ML—but maybe a bit wary of its overhyped promises.

Prerequisites:

  • Basic Python programming skills — if you can write a for loop, you’re good to go!
  • Basic knowledge of petroleum systems concepts
  • No fear of the word “logarithm”, though there’s no need for any math beyond a basic grasp of introductory differential calculus

Instructor(s)

icon
Pedro Barros Cotta Pesce

Pedro is a senior geophysicist, internal Consultant, at Petrobras. Holds a bachelor’s (2009) and a master’s degree (2012) in physics from Universidade Federal de Minas Gerais. Since 2010, has been working in corporate education through Universidade Petrobras, focusing on quantitative methods applied to the geosciences.

icon
Thiago de Miranda Leão Toribio

Thiago is a geophysicist at Petrobras. Holds a bachelor’s degree in physics from Universidade de São Paulo (1997), bachelor’s degree in philosophy from Universidade Federal do Estado do Rio de Janeiro (2022) and a master's degree in theoretical physics from Universidade de Brasília (2000). Has professional experience in education and geophysics, particularly in teaching geophysics and mathematics.

icon
Cesar José Calderon Filho

Cesar is a senior geophysicist at Petrobras. Holds a bachelor's (2008), master's (2011) and a doctoral degree (2014) in physics from Universidade Estadual de Campinas. Since joining Petrobras in 2013, has worked with all stages of the seismic processing workflow and currently works in the Geophysical Technologies team, specializing in reverse time migration, near-field hydrophones and the application of machine learning techniques to seismic processing. Additionally, has teaching experience in geophysics and mathematics at Universidade Petrobras.

icon
Luiz Eduardo Silva Queiroz

Luiz is a senior geophysicist at Petrobras, specializing in rock physics, seismic inversion and geophysical reservoir characterization. Holds a bachelor's degree in physics (2011) and master’s degree in mechanical engineering from Universidade Federal de Pernambuco (2014), as well as a doctoral degree in materials science and engineering from Universidade Federal de Santa Catarina (2025).

icon
Antônio de Pádua Cunha Pires Filho

Antonio is a senior geophysicist at Petrobras. Holds a bachelor's (1988) and a master's degree (1991) in physics from Universidade Federal do Ceará, a master's degree (DEA) in physical meteorology from Université Blaise Pascal Clermont Ferrand II (1992), and a Ph.D. in atmospheric physics from Université Toulouse III Paul Sabatier (1996). Since joining Petrobras in 2011, has been developing mathematical, statistical, and artificial intelligence models to describe geological processes, as well as teaching mathematics, programming, and machine learning to geoscientists and data scientists within the company.


Fee:
$550 USD
Attendee Limit:
20

Venue

Artificial Intelligence for Oil and Gas Without the Hype
Windsor Barra
Rio de Janeiro
Brazil

Accommodation information is not yet available for this event. Please check back often.

Instructor