Hybrid machine learning algorithms to predict condensate viscosity in the near wellbore regions of gas condensate reservoirs

被引：0
|
作者：
Behesht Abad, Abouzar Rajabi [1 ]
Mousavi, Seyedmohammadvahid [2 ]
Mohamadian, Nima [3 ]
Wood, David A. [4 ]
Ghorbani, Hamzeh [5 ]
Davoodi, Shadfar [6 ]
Alvar, Mehdi Ahmadi [7 ]
Shahbazi, Khalil [8 ]
机构：
[1] Department of Petroleum Engineering, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran
[2] Department of Petroleum Engineering, Islamic Azad University, Nour Branch, Nour, Iran
[3] Young Researchers and Elite Club, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran
[4] DWA Energy Limited, Lincoln,LN5 9JP, United Kingdom
[5] Young Researchers and Elite Club, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
[6] School of Earth Sciences & Engineering, Tomsk Polytechnic University, Lenin Avenue, Tomsk, Russia
[7] Faculty of Engineering, Department of Computer Engineering, Shahid, Chamran University, Ahwaz, Iran
[8] Department of Petroleum Engineering, Petroleum University of Technology (PUT), Ahwaz, Iran
来源：
Journal of Natural Gas Science and Engineering | 2021年 / 95卷
关键词：
117;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [21] Effect of surfactants on wettability of near-wellbore regions of gas reservoirs
    Adibhatla, B.
    Mohanty, K. K.
    Berger, P.
    Lee, C.
    JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2006, 52 (1-4) : 227 - 236
  • [22] Effect of a synthesized anionic fluorinated surfactant on wettability alteration for chemical treatment of near-wellbore zone in carbonate gas condensate reservoirs
    Iman Nowrouzi
    Amir HMohammadi
    Abbas Khaksar Manshad
    Petroleum Science, 2020, 17 (06) : 1655 - 1668
  • [23] Effect of a synthesized anionic fluorinated surfactant on wettability alteration for chemical treatment of near-wellbore zone in carbonate gas condensate reservoirs
    Iman Nowrouzi
    Amir H.Mohammadi
    Abbas Khaksar Manshad
    Petroleum Science, 2020, (06) : 1655 - 1668
  • [24] Effect of a synthesized anionic fluorinated surfactant on wettability alteration for chemical treatment of near-wellbore zone in carbonate gas condensate reservoirs
    Nowrouzi, Iman
    Mohammadi, Amir H.
    Manshad, Abbas Khaksar
    PETROLEUM SCIENCE, 2020, 17 (06) : 1655 - 1668
  • [25] Application of Machine Learning to Accelerate Gas Condensate Reservoir Simulation
    Samnioti, Anna
    Anastasiadou, Vassiliki
    Gaganis, Vassilis
    CLEAN TECHNOLOGIES, 2022, 4 (01): : 153 - 173
  • [26] The impact of near-wellbore wettability on the production of gas and condensate: Insights from experiments and simulations
    Ali, Nour El Cheikh
    Zoghbi, Bilal
    Fahes, Mashhad
    Nasrabadi, Hadi
    Retnanto, Albertus
    JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2019, 175 : 215 - 223
  • [27] A Comparative Analysis of the Prediction of Gas Condensate Dew Point Pressure Using Advanced Machine Learning Algorithms
    Lertliangchai, Thitaree
    Dindoruk, Birol
    Lu, Ligang
    Yang, Xi
    Sinha, Utkarsh
    FUELS, 2024, 5 (03): : 548 - 563
  • [28] Variations of gas/condensate relative permeability with production rate at near-wellbore conditions: A general correlation
    Jamiolahmady, M.
    Danesh, A.
    Tehrani, D. H.
    Sohrabi, M.
    SPE RESERVOIR EVALUATION & ENGINEERING, 2006, 9 (06) : 688 - 697
  • [29] Machine learning modelling of dew point pressure in gas condensate reservoirs: application of decision tree-based models
    Esmaeili-Jaghdan, Zohre
    Tatar, Afshin
    Shokrollahi, Amin
    Bon, Jan
    Zeinijahromi, Abbas
    NEURAL COMPUTING & APPLICATIONS, 2024, 36 (04): : 1997 - 2014
  • [30] Machine learning modelling of dew point pressure in gas condensate reservoirs: application of decision tree-based models
    Zohre Esmaeili-Jaghdan
    Afshin Tatar
    Amin Shokrollahi
    Jan Bon
    Abbas Zeinijahromi
    Neural Computing and Applications, 2024, 36 : 1973 - 1995
12345