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Predicting Formation Pore-Pressure from Well-Log Data with Hybrid Machine-Learning Optimization Algorithms |
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| Authors: | Farsi Mohammad Mohamadian Nima Ghorbani Hamzeh Wood David A Davoodi Shadfar Moghadasi Jamshid Ahmadi Alvar Mehdi |
| Institution: | 1.Department of Petroleum Engineering, Faculty of Petroleum and Chemical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran ;2.Young Researchers and Elite Club, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran ;3.Young Researchers and Elite Club, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran ;4.DWA Energy Limited, Lincoln, LN5 9JP, UK ;5.School of Earth Sciences and Engineering, Tomsk Polytechnic University, Lenin Avenue, Tomsk, Russia ;6.Petroleum Engineering Department, Petroleum Industry University, Ahvaz, Iran ;7.Faculty of Engineering, Department of Computer Engineering, Shahid Chamran University, Ahwaz, Iran ; |
| Abstract: | Natural Resources Research - Accurate prediction of pore-pressures in the subsurface is paramount for successful planning and drilling of oil and gas wellbores. It saves cost and time and helps to... |
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