Predicting CO2 Minimum Miscibility Pressure (MMP) Using Alternating Conditional Expectation (ACE) Algorithm

• Published in: Oil & gas science and technology 2015-11, Vol.70 (6), p.967-982
• Main Authors: Alomair, O., Malallah, A., Elsharkawy, A., Iqbal, M.
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Carbon dioxide; Correlation coefficient; Correlation coefficients; Data; Data points; Enhanced oil recovery; Gas injection; Hydrogen sulfide; Injection; Mathematical models; Measurement methods; Miscibility; Natural gas; Oil recovery; Physics; Pressure; Recovery; Statistical analysis; Statistical methods; Transformations
• ISSN: 1294-4475; 1953-8189; 2804-7699
• DOI: 10.2516/ogst/2012097

Miscible gas injection is one of the most important enhanced oil recovery (EOR) approaches for increasing oil recovery. Due to the massive cost associated with this approach a high degree of accuracy is required for predicting the outcome of the process. Such accuracy includes, the preliminary screening parameters for gas miscible displacement; the “Minimum Miscibility Pressure” (MMP) and the availability of the gas. All conventional and stat-of-art MMP measurement methods are either time consuming or decidedly cost demanding processes. Therefore, in order to address the immediate industry demands a nonparametric approach, Alternating Conditional Expectation (ACE), is used in this study to estimate MMP. This algorithm Breiman and Friedman [Brieman L., Friedman J.H. (1985) J. Am. Stat. Assoc. 80, 391, 580-619]estimates the transformations of a set of predictors (here C1, C2, C3, C4, C5, C6, C7+, CO2, H2S, N2, Mw5+, Mw7+ and T) and a response (here MMP) that produce the maximum linear effect between these transformed variables. One hundred thirteen MMP data points are considered both from the relevant published literature and the experimental work. Five MMP measurements for Kuwaiti Oil are included as part of the testing data. The proposed model is validated using detailed statistical analysis; a reasonably good value of correlation coefficient 0.956 is obtained as compare to the existing correlations. Similarly, standard deviation and average absolute error values are at the lowest as 139 psia (8.55 bar) and 4.68% respectively. Hence, it reveals that the results are more reliable than the existing correlations for pure CO2 injection to enhance oil recovery. In addition to its accuracy, the ACE approach is more powerful, quick and can handle a huge data. L’injection de gaz miscibles est une des méthodes les plus utilisées pour améliorer la récupération d’hydrocarbures (Enhanced Oil Recovery, EOR). En raison du coût important de cette technique, un haut degré de précision est requis pour prédire le processus. Une telle précision comprend les paramètres de dépistage préliminaires pour le déplacement de gaz miscible, la pression minimale de miscibilité (Minimum Miscibility Pressure, MMP) et de la disponibilité du gaz. Toutes les méthodes de mesure du MMP conventionnelles sont des processus consommateurs de temps requérant de ce fait des coûts importants. Par conséquent, afin de répondre aux demandes de réponses rapides du secteur, une approche non paramétrique