Enhanced recovery

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.
This paper explains that the discovery of specific pressure trends, combined with an unconventional approach for analyzing gas compositional data, enables the detection and prediction of paraffin deposition at pad level and in the gathering system.

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