Amir Nematollahi Sarvestani









Amir Nematollahi Sarvestani – AI & Petroleum Engineering Innovator



Amir Nematollahi Sarvestani

Amir Nematollahi Sarvestani

PhD Candidate in Petroleum Engineering | Pioneering AI in Digital Rock Physics & Unconventional Reservoir Innovation

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Professional Profile

Data Scientist and Petroleum Engineer with a research focus on leveraging advanced computational methods for geoscientific innovation. My work integrates 3D geological modeling, digital rock physics, and deep learning for image processing (SEM/micro-CT) to enhance shale reservoir characterization, petrophysical analysis, and reservoir simulation. Proficient in Python, Azure, Abaqus, and Power BI for developing data-driven insights that optimize resource development and de-risk subsurface projects. My research bridges the gap between geoscience and computational analytics. I am driven to create innovative, data-centric solutions that address challenges in petrophysics, sustainable resource development, and production optimization.

Education Timeline

B.Sc. in Petroleum Engineering

Shiraz University, Shiraz, Iran • 2012–2017

M.Sc. in Mining Engineering (100/110)

Politecnico di Torino, Turin, Italy • 2018–2021
Alta Scuola Politecnica – Double degree Politecnico di Milano and di Torino • 2018–2019

Ph.D. in Petroleum Engineering

China University of Geosciences, Wuhan, China • 2025–2029
Research Focus: Image processing, deep learning, geometric modeling, and petrophysical analysis applied to unconventional reservoirs.

Test Scores

GRE Scores: Total 308 | Quantitative Reasoning 164 | Verbal Reasoning 142 | Analytical Writing 3.5 • Dec 2023

IELTS Academic: 7.5 band | Speaking 7.0 | Writing 7.0 | Reading 8.0 | Listening 8.0 • March 2025

Research Interests

3D geological modeling, digital rock physics, image processing and analysis, deep learning, SEM and micro-CT imaging, shale reservoir characterization, computational geomechanics, and reservoir simulation.

Technical Skills

Programming

Python (proficient), MATLAB, Fortran

Image Analysis & AI

ImageJ, TensorFlow, PyTorch, OpenCV

Geoscience Software

ArcGIS, Abaqus, Eclipse100, SolidWorks, Ventsim, WinProp, Pipesim

Data Visualization & Cloud

Power BI, Azure, SQL

Other

Microsoft Office, WordPress

Research Experience

  • Develop and implement deep learning models to reconstruct 3D pore-scale models from 2D SEM images of shale samples.
  • Apply image segmentation and stereological methods to quantify pore morphology, connectivity, and mineral distribution.
  • Integrate petrophysical data to improve permeability and porosity predictions in heterogeneous reservoirs.
  • Designed and simulated ventilation circuits for underground mines using Ventsim and numerical modeling.
  • Published multiple peer-reviewed articles on fire safety, ventilation, and environmental modeling.

Publications

  • Nematollahi Sarvestani, Amir, and Pierpaolo Oreste. 2023. “Effects of the Ventilation System by Using Jet Fans during a Fire in Road Tunnels” Applied Sciences 13, no. 9: 5618. DOI
  • Nematollahi Sarvestani, A.; Oreste, P.; Gennaro, S. “Fire Scenarios Inside a Room-and-Pillar Underground Quarry Using Numerical Modeling to Define Emergency Plans.” Appl. Sci. 2023, 13, 4607. DOI
  • Nematollahi Sarvestani, A.; Oreste, P.; Gennaro, S. “Improving environmental conditions of a Room and Pillar underground quarry using the numerical modeling of the ventilation system”, 2021, Mining Technology.
  • Carola Botto, Alberto Cannavo, Daniele Cappuccio, Giada Morat, Amir Nematollahi Sarvestani, Paolo Ricci, Valentina Demarchi, Alessandra Saturnino, “Augmented Reality for the Manufacturing Industry: The Case of an Assembly Assistant”, 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Atlanta, GA, USA. DOI
  • E. Bakyani, A. Taghizade, A. Nematollahi Sarvestani, F. Esmaeilzadeh and D. Mowla (2018), “Three-dimensional and two-phase numerical simulation of fractured dry gas reservoirs”, J. Petrol. Explor. Prod. Technology. DOI
  • Bakyani, A., Namdarpoor, A., Nematollahi Sarvestani, A., Daili, A., Ganji, S. and Esmaeilzadeh, F. (2018) “A Simulation Approach for Screening of EOR Scenarios in Naturally Fractured Reservoirs”. International Journal of Geosciences, 9, 19-43. DOI

Teaching Experience

Teaching Assistant

Shiraz University • 2012–2017
Assisted in courses including Reservoir Simulation, Drilling Engineering, and Rock Mechanics. Graded assignments, held office hours, and supported lab sessions.

Instructor – Power BI and Azure

Faradars.org • 2022
Developed and delivered curriculum on data visualization and cloud computing for industry professionals.

Professional Experience

Data and Trading Analyst

Aminsazeh Gostaran Company (Bakren), Iran • 2022–2025
Performed market analysis, risk assessment, and financial planning using Python, SQL, and Power BI. Contributed to business growth through data-driven trading strategies.

Current Project Highlights

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