Dr. Farshad Sadeghpour | Data prediction | Best Researcher Award

Farshad Sadeghpour (b. 1996) is a Petroleum Engineer and Data Scientist with expertise in reservoir engineering, petrophysics, and AI applications in the energy sector. Based in Tehran, Iran , he holds a Master’s and Bachelor’s in Petroleum Exploration. With extensive experience in EOR, SCAL/RCAL analysis, and machine learning, Farshad has contributed to both academic and industrial R&D at RIPI, NISOC, and PVP. He has published multiple research articles , won international awards , and participated in key petroleum projects. He served in the military and actively collaborates with academia and industry on AI-driven energy solutions.

Profile

• Orcid

Education

Master’s in Petroleum Engineering (Petroleum Exploration), Petroleum University of Technology, Abadan (2019–2022) | GPA: 18.82/20
Bachelor’s in Petroleum Engineering, Islamic Azad University (Science & Research Branch), Tehran (2015–2019) | GPA: 19.14/20
Courses covered include reservoir engineering, geomechanics, well-logging, and advanced data analytics.
Projects include CO₂ storage modeling, permeability prediction via AI, and LWD-based mud loss forecasting.
Developed key industry collaborations with NISOC, RIPI, and OEID through thesis, internships, and military service projects.
Honed computational and simulation skills using MATLAB, Python, COMSOL, Petrel, and ECLIPSE.
Academic mentors: Dr. Seyed Reza Shadizadeh, Dr. Bijan Biranvand, Dr. Majid Akbari.

Experience

Computer Aided Process Engineering (CAPE) – Petroleum Reservoir Engineer (Nov 2024–Present)
Petro Vision Pasargad – Reservoir Engineer & Lab Operator (Sep 2023–May 2024)
Research Institute of Petroleum Industry (RIPI) – Petroleum Engineer, Data Scientist (Mar 2023–Apr 2024)
National Iranian South Oil Company (NISOC) – Petroleum Engineer, Petrophysicist (Mar 2021–Nov 2024)
Internships: NIOC – Exploration Management, Oil & Energy Industries Development (OEID)
Key contributions include EOR analysis, SCAL/RCAL lab testing, permeability modeling, machine learning pipelines, and field data analysis.
Delivered reports, simulations, and AI models supporting production optimization and reservoir characterization.

Awards & Recognitions

3rd Prize Winner – EAGE Laurie Dake Challenge 2022 (Madrid, Spain)
Recognized for thesis excellence in AI-driven mud loss prediction with NISOC collaboration
Acknowledged during military service project with RIPI for developing ANN-based well log models
Published in high-impact journals such as Energy, Geoenergy Science and Engineering, and JRMGE
Co-author of multiple peer-reviewed papers and under-review articles across petroleum engineering disciplines
Worked alongside top researchers including Dr. Ostadhassan, Dr. Gao, and Dr. Hemmati-Sarapardeh
Actively participated in multidisciplinary teams combining AI, geomechanics, and petrophysics
Regular presenter and contributor at petroleum conferences and AI-in-energy seminars.

Research Interests