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The artificial intelligence (AI) revolution has arrived and is here to stay. For the first time in history, machine learning, an application of AI, is not only available to big companies in specialized applications, but it is now part of our daily routines. We are on the edge of a breakthrough that will profoundly change how we live and how we work.

The E&P industry has been using machine learning for a specific set of problems for decades and the new challenge is how to leverage those techniques in today’s challenges. The broad industry challenges that can be addressed : from seismic interpretation to production, improving operational efficiency and reducing costs. This webcast outlines and explains machine learning foundations, industry related machine learning initiatives, and its impacts for the E&P industry.

Speaker | Welton Souza

Regional Technical Sales Consultant for Information Management, Platform Technologies and Cloud solutions for Europe & Sub-Saharan Africa. He holds a BSc in Computer Engineer and has 12 years experience in the E&P industry.

Speaker | Marcelo Gomes

Regional Advisor for Digital E&P in Latin America. Marcelo has a MSc in Machine Learning, completing his PhD in the same area, as well as 20 years of experience of development of Scientific Computing Algorithms. He has spent the last 10 years in E&P industry.

Speaker | Henrique Araujo

Regional Advisor for Drilling and Completions and Digital E&P in Latin America. Henrique has more than 30 years experience in the E&P industry, specifically in Data Management.


  • Understand how machine learning technology and advancements can improve overall efficiency across all E&P domains
  • Find out the foundations and challenges to successfully use machine learning to achieve goals
  • Practical application of machine learning techniques and technology tailored to the industry


  • Exploration geoscientists
  • E&P Managers and Vice Presidents
  • Geo-modelers
  • Reservoir Engineers
  • Drilling and Completion Engineers
  • E&P Information Management
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