Hussain Alqahtani

Research Interests

My research focuses on CO₂ storage reservoir characterization and modelling, integrating petrophysical data and digital core analysis to enhance storage efficiency. I also explore machine learning techniques to improve data analysis and predictive modelling, contributing to more accurate subsurface storage assessments and the advancement of carbon capture and storage (CCS) technologies

Selected Publications

Segmentation of X-ray images of rocks using supervoxels over-segmentation Hussain Alqahtani; Naif Alqahtani; Ryan T. Armstrong; Peyman Mostaghimi Paper presented at the International Petroleum Technology Conference, Riyadh, Saudi Arabia, February 2022. Paper Number: IPTC-22131-MS

Education

M.Sc., Petroleum Engineering, University of New South Wales (UNSW), Sydney, Australia, 2021

B.Sc., Petroleum Engineering, Louisiana State University, Baton Rouge, Louisiana, USA, 2014

Professional Profile

· 2021-2023: Petrophysicist, Saudi Aramco, Dhahran, Saudi Arabia

· 2017-2019: Petrophysicist, Saudi Aramco, Dhahran, Saudi Arabia

· 2016-2017: Reservoir engineer, Saudi Aramco, Dhahran, Saudi Arabia

· 2015-2016: Drilling engineer, Saudi Aramco, Udhailiyah, Saudi Arabia

· 2014-2015: Petrophysicist, Saudi Aramco, Dhahran, Saudi Arabia

Scientific and Professional Membership

· Society of Petroleum Engineers (SPE) – Kingdom of Saudi Arabia Section

· Society of Petrophysicists and Well Log Analysts – Saudi Arabia Chapter

Awards

· Century Club status from the Society of Petroleum Engineers – Life membership

· Petroleum Engineering Certification from the Society of Petroleum Engineers (SPE)

Research Interests Keywords

C02 storage reservoirs Reservoir Characterization Reservoir modeling petrophysical data Digital core analysis Machine Learning predictive modeling subsurface storage assessment Carbon capture and Storage computational techniques