A new correlation for predicting hydrate formation conditions for ...

( )A.A. Elgibaly, A.M. ElkamelrFluid Phase Equilibria 152 1998 23–42 35Fig. 9. Cross plot of ANN model-D.models were considered to facilitate comparisons with models available in the literature and also tocheck whether or not more specialized models might lead to better accuracies than a generalizedmodel. Table 3 compares the statistical parameters for these models. The results show that thecomprehensive ANN model-D deliver a competitive correlation coefficient. For a total number of dataentries of 2387, this model gives an average absolute error of 19.4% and sum-squares error of 0.9794.The cross plot of this model Ž Fig. 9.confirms this fact.To further check the accuracy of the generalized model-D compared to models-C and -D, a smallsubset of the data was considered. In Table 4 the experimental hydrate-forming pressure is tabulatedagainst the pressure predicted by different compositional models for this data subset. The resultsreveal that the ANN model-D fit is good and compares well with the other models. Therefore, it canbe concluded that the comprehensive ANN model-D can be generally used to predict the hydrateformation pressure for all system compositions. The predictions of the statistical thermodynamicmodel Ž STM.are also included in Table 4 for comparison purposes.The new model can predict the hydrate formation conditions for gas systems existing in one ormore of the following phase regions: I–H–V, L w–H–L hc, L w–H–L hc–V, and L w–H–L hc on thegeneral equilibrium pressure–temperature plot. Contrary to the statistical thermodynamic model, thedeveloped model does not necessarily require a priori knowledge of the number and type of phasesbefore prediction.3.4. Validation of the deÕeloped modelsThe validation of the new models was examined by using data that have not been considered intheir developments. Random samples of extra measured data points, which represent different phases