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This map has gone through several changes each one being worse than the last With a tit-for-tat to whom ever wants to slug it out for a possible single kill, quick death and little other reward. Spg's are locked into the corners, there is little to no cover for West advance as spotting is lost almost immediately and Island affords poor cover and advancement.Įast buildings are just Blah.locking tanks into a head to head.Ĭenter of the map is locked up and just promotes both a death rush and a campfest for TD's in the rear Have you not figure out that it is WAY TOO SMALL for anything above tier 5 Once again another wasted opportunity to increase this terrible map Here's to hoping they play as good as they look. Thank you for the well overdue addition of 2 new maps Update 1.1 New maps and changes to existing Finally, the presented model was evaluated against a comprehensive theoretical model of slim tube compositional simulation on a trusted literature dataset. This comparison presents an acceptable accuracy relative to this estimation model. The SVR model was compared to popular data-driven MMP estimation models as well. In addition, the SVR results demonstrate the proposed model to be a fast tool and a robust approach to map input space to output features. The model results illustrate a correlation coefficient ( R 2) of 0.999. The proposed data-driven model was verified by statistical validation data.
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Genetic algorithm was implemented to optimize the SVR model parameters. The database contains 135 datasets, from which 125 datasets were used for model development, and the rest were used for model evaluation. Experimental MMP is regarded as the model output. Each data point input includes methane and intermediate components mole percent, plus fraction properties and reservoir temperature related to reservoir fluid and CO 2, H 2S, N 2 and intermediate mole fractions, and intermediate properties of the injected gas. Experimental MMP data taken from the reliable literature were used as input. In this work, a support vector regression (SVR) model is developed using experimental data to estimate the minimum miscibility pressure (MMP) for various reservoir fluids and injection gases.
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Determination of gas–oil minimum miscibility conditions is one of the important design parameters to improve the displacement efficiency of the hydrocarbon reservoir during enhanced oil recovery with gas injection.
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