The main objective of this study was to present a novel approach for predication of gas hydrate formation rate based on the Intelligent Systems. Using a data set obtained from flow tests in a mini-loop apparatus, different predictive models were developed. From the results predicted by these models, it can be pointed out that the developed models can be used as powerful tools for prediction of gas hydrate formation rate with total error of less than 4%.
In this study, separating water from oil is studied numerically. In this simulation, the Reynolds Stress Model and the mixture multiphase model are used for coupling the velocity and pressure equations using the SIMPLE algorithm. The simulated geometry is taken from an experimental setup. It results that, in the case of the crude oil as the discrete phase, by increasing the diameter of the discrete phase (crude oil) droplets, the separation efficiency increases. If the diameter of the oil droplets is greater than 100 microns, the percentage of oil output from the spillway reaches 99.5%. In the case of the water phase as the discrete phase, if the water droplets size is considered equal to 200 microns, the water separation efficiency in the spillway reaches 69%.
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