Dr. Omid Shahrokhi
Research Fellow
School of Engineering & Physical Sciences, Institute of Mechanical, Process & Energy Engineering, Heriot-Watt University, Riccarton, UK
Biography
Dr. Omid Shahrokhi is a Research Fellow at Heriot-Watt University, specialising in subsurface energy storage, CO₂ sequestration, and integrated energy systems. His research supports the global energy transition by bridging advanced modelling with real-world industrial applications, focusing on scalable low-carbon solutions for industrial decarbonisation.
Dr. Shahrokhi holds a BSc and MSc in Petroleum Engineering from Sharif University of Technology, Iran, and a PhD in Petroleum Engineering from Heriot-Watt University, UK. His expertise includes subsurface hydrogen and CO₂ storage, multiphase flow in porous media, and multi-vector energy-system optimisation.
He has contributed to numerous joint-industry projects (JIPs) and EPSRC programmes aimed at decarbonising industrial clusters, power and heat. His work integrates computational modelling, techno-economic assessment, and full-system integration from campus to national scale.
Technical skills: advanced reservoir simulators CMG and Eclipse; programming in Python (NumPy, pandas, SciPy, scikit-learn, matplotlib), MATLAB, and C#; and energy-data API integration (ENTSO-E, Elexon BMRS, National Grid ESO, National Gas Transmission) that feeds live market and grid data into optimisation dashboards.
Professional affiliations include SPE, EAGE, InterPore, UKCCSRC, and the Society of Core Analysts (Lifetime Member). Recognitions include the James-Watt Scholarship and SPE Student Bursary.
He welcomes collaboration and consultancy partnerships advancing low-carbon and energy-transition technologies.
Roles & Responsibilities
Research, MSc and PhD Supervision
Research interests
From pore-scale physics to system-scale decarbonisation
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Multiphase flow imaging & modelling – X-ray/micro-CT visualisation and numerical simulation of two- and three-phase flow in reservoir rocks. These pore-scale insights underpin all downstream storage and system studies.
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Subsurface energy storage – applying flow-physics learnings to design and operate hydrogen and CO₂ storage in porous media, with integrity and risk assessment.
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Geological CO₂ sequestration – evaluating trapping mechanisms, long-term plume evolution and monitoring strategies using coupled flow models derived from (1) and (2).
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Integrated energy-system optimisation – linking underground storage with renewables, CCS, hydrogen networks and district heating in multi-vector models spanning campus, industrial-cluster and national scales.
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Techno-economic evaluation & policy support – translating technical results into cost, emissions and investment metrics to guide industrial decarbonisation decisions.
Complementary interests
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Digital twins and data analytics for energy assets.
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Automation of laboratory & simulation workflows using Python (NumPy, pandas, SciPy, scikit-learn, matplotlib, energy APIs) and MATLAB; bespoke tools in C#.
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Machine-learning applications in reservoir engineering and energy-system planning.