Fatai Anifowose

Independent Researcher

Fatai Anifowose, SPE, is an independent researcher in the field of machine learning. His research focuses on automating geological and petroleum engineering workflows and application of machine learning to increase accuracy, improve efficiency, and enhance productivity. He has an accomplished researcher with over 90 papers, an innovator with over 10 granted patents and several filed, and received a number of R&D awards, including the 2021 SPE Middle East and North Africa Regional Service Award, 2021 SPE Middle East and North Africa Regional Data Science and Engineering Analytics, and 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, and Dhahran Geoscience Society.

Data & Analytics

Deep Learning and Its Applications in the Energy Industry

This article explains what deep learning is and how it works and presents an example use case from the energy industry.

September 13, 2023 • Fatai Anifowose • Data Science and Digital Engineering
Data & Analytics

Mud Gas Data Could Reveal a Wealth of Reservoir Information

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…

October 29, 2021 • Fatai Anifowose • Data Science and Digital Engineering
Data & Analytics

Hybrid Machine Learning Explained in Nontechnical Terms

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.

February 6, 2020 • Fatai Anifowose • Data Science and Digital Engineering