Faculty
The faculty leading this IAP are uniquely capable to address these challenges, given our strong knowledge concerning geology, geophysics, gomechanics, drilling and completions, reservoir engineering, formation evaluation, geostatistics, reservoir modeling, data analytics and machine learning.
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Michael Pyrcz, Ph.D., P.Eng.
Professor
Ph.D. Student Researchers
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Muhammad Muneeb Akmal
Physics-informed machine learning for subsurface forecast proxy models.
Supervisors: Drs. Pyrcz and Sephernoori
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Aun Al Ghaithi
Novel uncertainty modeling workflows to support optimum subsurface resource development.
Supervisor: Dr. Pyrcz
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Nataly Chacon-Buitrago
Improved subsurface heterogeneity modeling with rule-based and generative AI-based modeling.
Supervisor: Dr. Pyrcz
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Ryan McGuigan
Uncertainty modeling robustness for optimum subsurface resource development.
Supervisors: Drs. Foster & Pyrcz
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Ahmed Merzoug
A critical evaluation of performance of generative AI for subsurface modeling.
Supervisor: Dr. Pyrcz
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Misael Morales
Deep learning for the integration of 4D seismic and fibre for enhanced subsurface resource modeling.
Supervisors: Drs. Pyrcz & Torres-Verdin
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Elnara Rustamzade
Deep learning for enhanced subsurface mdoeling to support optimum decision making.
Supervisors: Drs. Foster & Pyrcz
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Eldar Sharafutdinov
Spatiotemporal, multiscale modeling of methane emmissions to support green house gas reductions.
Supervisors: Drs. Pyrcz & Ravikumar
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Dinghan Wang
Supervisors: Drs. Pyrcz & Lu
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Qianqian Zhou
Supervisors: Drs. Pyrcz & Prodanovic
Masters Student Researchers
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Laaiba Akmal
Discrepancy machine learning models for the integration and discovery of physics for subsurface modeling.
Supervisor: Dr. Pyrcz
Former Student Researchers
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Jose Hernandez Mejia
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Honggeun Jo
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Wendi Liu
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Lei Liu
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Ademide Mabadeje
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Eduardo Maldonado Cruz
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Wen Pan
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Akhil Potla
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Jose Julian Salazar Neira
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Javier Santos
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Mahmood Shakiba
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Ruoyu Wang