Abdulaziz Qasim

Saudi Aramco (United States), Saudi Aramco (Saudi Arabia)

Papers

Total Citations

H-Index

About

Abdulaziz Qasim is a forward-thinking researcher at the intersection of artificial intelligence, carbon management, and sustainable energy systems. His work centers on leveraging deep learning and real-time sensor intelligence to optimize subsurface CO₂ injection and storage—critical for both enhanced oil recovery and carbon capture utilization. Qasim’s most cited paper, “A Deep Learning Wag Injection Method for CO2 Recovery Optimization” (2021, 4 citations), introduces a novel AI-driven approach to water-alternating-gas (WAG) injection, exploiting CO₂’s solubility in crude oil to boost sweep efficiency and reduce viscosity. He further advances intelligent monitoring in “Real-Time Intelligent Sensor Selection for Subsurface CO2 Flow and Fracture Monitoring” (2022, 2 citations), enabling adaptive, data-driven reservoir management. His work “Minimizing Carbon Footprint by Smart Sustainable Reservoir Management” (2021, 2 citations) directly addresses the oil and gas industry’s role in the 4th Industrial Revolution, proposing strategies to reduce carbon footprints while maximizing recovery. Though early in his career, Qasim’s focused contributions to AI-enabled CO₂ optimization and sustainable reservoir practices position him as an emerging voice in the global push toward net-zero energy systems.