fatai-anifowose-2019.jpg

Fatai Anifowose

Lead Research Scientist Saudi Aramco

Fatai Anifowose, SPE, is a lead research scientist at Saudi Aramco. His research focuses on automating geological and petroleum engineering workflows and application of machine learning to increase accuracy, improve efficiency, and enhance productivity. He is an accomplished researcher with 90 papers, 10 granted patents and several filed, and has received a number of R&D awards, including the 2021 SPE Middle East North Africa Regional Service Award, 2021 SPE Middle East North Africa Regional Data Science and Engineering Analytics Award, and the 2024 IChemE Learning and Development Award. He is a technical reviewer for international conferences and reputable journals. He is a member of EAGE, SPE, AAPG, Dhahran Geoscience Society.

  • This article explains what deep learning is and how it works and presents an example use case from the energy industry.
  • The utility of mud gas data so far has been limited to fluid typing, formation evaluation, and interwell geological and petrophysical correlation. The ongoing digital transformation has presented the opportunity to increase the utility of, and get more value from, the abundant and rich mud gas data. This article raises the question of whether getting more from mud gas…
  • HML methods have become common in recent applications. We have probably been using some of them without realizing it. It is, however, necessary to know about them in the context of understanding the underlying concepts of their methods and how they work.