Michael Pyrcz

Michael Pyrcz is a Professor in the Hildebrand Department of Petroleum and Geosystems Engineering and holds the rank of Associate Professor in the Jackson School of Geosciences at the University of Texas at Austin. He is the recipient of the B. J. Lancaster Professorship in Petroleum Engineering and the George H. Fancher Centennial Teaching Fellowship in Petroleum Engineering. His research focuses on subsurface data analytics, geostatistics, and machine learning applications in energy systems and CO2 sequestration. Pyrcz teaches widely, including through online lectures and GitHub workflows, and has authored over 50 peer-reviewed publications and a textbook on spatial data analytics.

His work integrates machine learning with geoscience challenges, such as uncertainty quantification in reservoir modeling and CO2 storage site evaluation. He leads initiatives in energy data analytics through the Freshman Research Initiative and collaborates with industry on workflow development. Key research areas include generative AI for subsurface models, stochastic methods for fracture networks, and anomaly detection in geologic monitoring.

• Education: Background in petroleum engineering and geosciences (details not explicitly provided).
• Grants/Advising: Extensive industry collaboration and mentorship roles at Chevron prior to UT Austin.

Labs/Teams: Maintains active GitHub repositories (GeostatsGuy), YouTube lecture series (GeostatsGuyLectures), and social media outreach (X/GeostatsGuy).