Efficient AI-Physics hybrid model with productive capabilities to reduce the time of history matching and scenario assessment; a case study: Minagish oil field
Ali Qubian, Mohammed Ahmad Zekraoui, Sina Mohajeri, Emad Mortezazadeh, Reza Eslahi, Maryam Bakhtiari, Abrar Al Dabbous, Asma Al Sagheer, Ali Alizadeh, Mostafa Zeinali
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引用次数: 0
Abstract
This paper proposes a novel approach that combines physics-based numerical simulation with deep-learning neural networks to create an AI-Physics hybrid model for reservoir simulation. Our primary o...
期刊介绍:
The international journal of Petroleum Science and Technology publishes original, high-quality peer-reviewed research and review articles that explore:
-The fundamental science of fluid-fluid and rock-fluids interactions and multi-phase interfacial and transport phenomena through porous media related to advanced petroleum recovery processes,
-The application of novel concepts and processes for enhancing recovery of subsurface energy resources in a carbon-sensitive manner,
-Case studies of scaling up the laboratory research findings to field pilots and field-wide applications.
-Other salient technological challenges facing the petroleum industry.