Neural Networks Plus CFD Speed Up Simulation of Fluid Flow
High-fidelity 3D engineering simulations are valuable in making decisions, but they can be cost-prohibitive and require significant amounts of time to execute. The integration of deep-learning neural networks with computational fluid dynamics may help accelerate the simulation process.
Smart-Fluid-Processing System Reduces Footprint, Improves Separation Efficiency
Reducing a separation system’s footprint while increasing separation efficiency is demonstrated in an Oklahoma field trial.
Challenges in the Design of Separators
Reliable separation is becoming an enabling technology to help develop remote location resources and more difficult applications, such as heavy oil, produced water, sand disposal, and back-produced fluids in enhanced oil recovery.
Computational Fluid Dynamics-Based Study of an Oilfield Separator—Part II: An Optimum Design
This paper provides details of comprehensive computational-fluid-dynamics (CFD) -based studies performed to overcome the separation inefficiencies experienced in a large-scale three-phase separator.
Computational Fluid Dynamics-Based Study of an Oilfield Separator—Part I: A Realistic Simulation
A realistic computational fluid dynamics (CFD) simulation of a field three-phase separator has been developed. Further, a useful approach to estimating the particle size distribution in oilfield separators was developed. The predicted separation efficiencies are consistent with oilfield experience.
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