Reservoir

Entrepreneurial mindsets with the motivation to explore new materials, not limited to focusing on traditional hydrocarbon gas, CO2, and chemicals such as polymer and surfactant, are becoming more important for broadening prospects beyond the conventional EOR scene.
This paper discusses a comprehensive hybrid approach that combines machine learning with a physics-based risk-prediction model to detect and prevent the formation of hydrates in flowlines and separators.
The objective of this microfluidic investigation is to identify and test two novel applications for magnetic fluids in porous media for subsurface oilfield applications.

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