Applications of Cloud Computing and Artificial Intelligence in the Oil and Gas Industry: A Review Alfitouri Ibrahim Jellah, Mohamed. M, Moaad. I 6th IEEE International Conference on Image Processing Applications and Systems Ipas 2025 Proceedings, 2025 This paper reviews the latest machine learning and artificial intelligence technology, showcasing its potential to revolutionize the oil and gas industry. Despite the current limitations, the industry is on the brink of a digital transformation that promises to enhance operations and increase overall production. With the help of AI and cloud computing, the oil and gas industry's future is one of optimism and potential. The review showed a significant increase in production when applying AI technology, particularly with EOR. The paper summarized the limitations and future challenges of this technology.
EXPLORING THE POTENTIAL OF CATALYTIC CRACKING OIL SLURRY AS HIGH AROMATIC RUBBER FILLING OIL Suleiman A Wali, Abdulhalim Musa Abubakar, Abubakar Mohammed, Alfitouri Ibrahim Jellah, Anna Sobczak, Noureddine Elboughdiri, Vivek Kumar Pandey, Marwea AlHedrewy Engineering Review, 2025 The utilization of catalytic oil slurry furfural extract as a high aromatic filling oil holds immense potential for enhancing rubber performance and properties. This study focuses on the properties and composition analysis of oil slurries extracted from the Maoming Petrochemical No. 2 and No. 4 catalytic cracking units, revealing a high content of aromatic hydrocarbons up to 70%. Through systematic experimentation, it has been determined that the 2# slurry oil is optimal for butadiene rubber (BR), while the 4# slurry oil is well-suited for styrene-butadiene rubber (SBR). Furthermore, a market feasibility comparison evaluates the performance of synthetic rubber infused with high aromatic oil, providing insights into the potential market acceptance of the 2# and 4# slurry oil extractions. This comprehensive study not only highlights the technical advancements in rubber manufacturing but also emphasizes the competitive edge and economic viability offered by catalytic oil slurry furfural extract as a high aromatic filling oil.
Addressing Reservoir Uncertainty: Sensitivity Study on a Virgin Oil Field Alfitouri Ibrahim Jellah Proceedings of IEEE International Conference on Advent Trends in Multidisciplinary Research and Innovation Icatmri 2020, 2020 This field is virtualized to be located offshore. Its management was informed in 2016 about a commercial recovery. The first exploration well was drilled in the top of a closed dome structure as indicated from seismic data. The well, W1, found 80 ft of net sand in the Paleocene sandstone along with thousands of feet of salt beneath. The first appraisal well 2, encountered 150 ft of net sand in the Paleocene as well as hydrocarbon in the Jurassic and established an oil-water contact at 8560 ft. The second appraisal well 3, was drilled to locate the areal extent of the field but did not encounter significant hydrocarbon. The features of this simulation include: water injection after natural depletion, wells orientation, heterogeneity, the model of wells number and placement, as well as fault modelling. The uncertainty inherited in the model is also stated. A description of a 16320-cell-model is provided along with sensitivity simulations and the results. Conclusion drawn from this study include: (1) the poor performance given by natural depletion without pressure support , (2) the success shown by water injection as pressure maintenance way which proved to yield the best recovery , and (3) the well arrangement of 11*5 producers and injectors was the best development plan for this field.