Mohammad Parvazdavani headshot

Dr. Mohammad Parvazdavani

PhD

Affiliations

Postdoctoral Associate

Faculty of Science, Department of Earth, Energy, and Environment

Contact information

Email

mohammad.parvazdavan@ucalgary.ca

Web presence

Google Scholar

Phone number

cell: 825-747-1543

Location

Office: Department of Earth, Energy and EnviromentES-130

Background

Credentials

Machine Learning and Visualization, University of Calgary, 2024

Educational Background

Ph.D. Reservoir Engineering, Amirkabir University of Technology, 2022

M.Sc Reservoir Engineering, Sharif University of Technology, 2012

Research

Areas of Research

Simulation of Unconventional Reservoirs

My interests include history matching and optimization under uncertainty; laboratory- and field-scale simulation of enhanced oil recovery (EOR) processes; and experimental research focused on the characterization of petrophysical properties, such as relative permeability. I have a strong background in reactive flow simulation, particularly in water-based EOR methods like low-salinity water injection, using commercial software such as CMG. I am a member of EAGE and SPE, and currently serve as a reviewer for Elsevier journals, including JPSE and JNGSE.

Participation in university strategic initiatives

Energy Innovations for Today and Tomorrow (2013-2021)

Projects

Evaluation of Continuous Fluid Injection and WAG Techniques for Enhanced Oil Recovery in a Tight Oil Reservoir in Alberta, Canada

This study provides practical insights into the impact of model uncertainty and completion methods on the design and performance of various continuous injection and WAG EOR schemes in tight oil reservoirs. Wherever possible, customized laboratory data, such as relative permeability collected for low-permeability rock samples, have been utilized.

Evaluation of Simultaneous Hydrogen Gas Stream Purification and CO2 Storage in Deep Mannville Coal

This study provides practical guidelines for achieving simultaneous hydrogen gas stream purification and CO2 storage in the deep Mannville coal in Alberta by applying HNP and flooding schemes using horizontal wells. Realistic constraints on the simulation model used to evaluate these schemes are provided through the application of existing field pilot data and laboratory results. The findings of this study will be important to operators considering this novel approach for purifying SMR gases using subsurface coal resources.

Application of the DFIT-FBA method for fault identification and assessment of induced seismicity in Multi-Fractured Horizontal Wells (MFHWs)

My research focuses on fault identification and seismic risk assessment using DFIT-FBA, with an emphasis on estimating the magnitude of induced seismicity in faulted reservoirs.

Publications