Abstract
Artificial intelligence (AI) and machine learning (ML) are increasingly being applied to petroleum engineering. Petroleum operations generate large amounts of geological, operational, and production data. AI can help engineers analyze this data, identify patterns, forecast production, support reservoir studies, improve drilling and maintenance decisions, and optimize operations. This student literature review examines selected applications of AI in petroleum engineering and considers its potential contribution to efficiency and sustainability. It also discusses important limitations, including data quality, model interpretability, validation, and the need for engineering judgment. The review suggests that future petroleum engineers will benefit from combining traditional engineering knowledge with data science and artificial intelligence skills.
Cite
MLA
Oduwoga, Kehinde Michael, and Taiwo Sarah Oduwoga. “Artificial Intelligence in Petroleum Engineering: Opportunities for Smarter and More Sustainable Energy Production.” Journal of Secondary and Undergraduate Research, vol. 4, no. 2, 2026
APA
Oduwoga, K. M., & Oduwoga, T. S. (2026). Artificial Intelligence in Petroleum Engineering: Opportunities for Smarter and More Sustainable Energy Production. Journal of Secondary and Undergraduate Research, 4(2)
Chicago
Oduwoga, Kehinde M. and Taiwo S. Oduwoga “Artificial Intelligence in Petroleum Engineering: Opportunities for Smarter and More Sustainable Energy Production.” Journal of Secondary and Undergraduate Research 4, no. 2 (2026).