Browsing by Author "Mohyaldinn, Mysara Eissa"
Now showing items 1-5 of 5
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A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis
Alakbari, Fahd Saeed; Mohyaldinn, Mysara Eissa; Ayoub, Mohammed Abdalla; Muhsan, Ali Samer; Hussein, Ibnelwaleed A. ( Public Library of Science , 2022 , Article)The bubble point pressure (Pb) could be obtained from pressure-volume-temperature (PVT) measurements; nonetheless, these measurements have drawbacks such as time, cost, and difficulties associated with conducting experiments ... -
A robust Gaussian process regression-based model for the determination of static Young's modulus for sandstone rocks
Alakbari, Fahd Saeed; Mohyaldinn, Mysara Eissa; Ayoub, Mohammed Abdalla; Muhsan, Ali Samer; Hussein, Ibnelwaleed A. ( Springer Science and Business Media Deutschland GmbH , 2023 , Article)Static Young's modulus (Es) is one of the leading mechanical rock properties. The Es can be measured from experimental lab methods. However, these methods are costly, time-consuming, and challenging to collect samples. ... -
An Accurate Reservoir's Bubble Point Pressure Correlation
Alakbari, Fahd Saeed; Mohyaldinn, Mysara Eissa; Ayoub, Mohammed Abdalla; Muhsan, Ali Samer; Hussein, Ibnelwaleed A. ( American Chemical Society , 2022 , Article)Bubble point pressure (Pb) is essential for determining petroleum production, simulation, and reservoir characterization calculations. The Pbcan be measured from the pressure-volume-temperature (PVT) experiments. Nonetheless, ... -
Do Leadership, Organizational Communication, and Work Environment Impact Employees’ Psychosocial Hazards in the Oil and Gas Industry?
Naji, Gehad Mohammed Ahmed; Isha, Ahmad Shahrul Nizam; Alazzani, Abdulsamad; Brough, Paula; Saleem, Muhammad Shoaib; Mohyaldinn, Mysara Eissa; Alzoraiki, Mohammed... more authors ... less authors ( MDPI , 2022 , Article)Workplace hazards can have a significant influence on a worker’s physical and mental health, reducing an organization’s effectiveness in terms of safety. However, psychosocial hazards are being recognized as a crucial ... -
Prediction of critical total drawdown in sand production from gas wells: Machine learning approach
Alakbari, Fahd Saeed; Mohyaldinn, Mysara Eissa; Ayoub, Mohammed Abdalla; Muhsan, Ali Samer; Abdulkadir, Said Jadid; Hussein, Ibnelwaleed A.; Salih, Abdullah Abduljabbar... more authors ... less authors ( John Wiley and Sons Inc , 2023 , Article)Sand production is a critical issue in petroleum wells. The critical total drawdown (CTD) is an essential indicator of the onset of sand production. Although some models are available for CTD prediction, most of them are ...