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Prediction of Dew Point Pressure in Gas Condensate Reservoirs Based On a Combination of Gene Expression Programming (GEP) and Multiple Regression Analysis

Journal: Petroleum & Petrochemical Engineering Journal (Vol.2, No. 5)

Publication Date:

Authors : ; ;

Page : 1-15

Keywords : Retrograde gas reservoirs; Dewpoint pressure; Gene expression p rogramming (GEP); Genetic Algorithm (GA); Regression analysis; Empirical correlation;

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Gas condensate reservoirs represent unique and clean hydrocarbon source of energy, so prediction of their thermodynamic criteria especially dewpoint pressure (P d ) is crucial for reservoir characterization and management, since declining of initial reservoir pressure below dewpoint pressure result in liquid built up near wellbore and reduce gas productivity index. In this study, a mathematical modeling developed to estimate dewpoint pressure at reservoir temperature using reliable, precise, well - organized gene expression programming (GEP) approach in combination with multiple non - linear regression analysis. The dataset comprises 453 published data points, and the mo del developed as a function of compositional analysis of hydrocarbons components (Z C1 - Z C7+ ), physical properties of heptane plus fractions (C 7 + ) including molecular weight and specific gravity, the mole fraction of nonhydrocarbons (Z CO2 & Z N2 ) and reservoir temperature. Experimental Pressure - Volume - Temperature (PVT) analysis including constant composition expansion (CCE) at reservoir conditions and compositional analysis are carried out through 27 gas condensate samples not used in model devel opment, and covering a great range of PVT properties to evaluate the new predictive model accuracy. Assessment and validation of the developed and published correlations carried out by a statistical and graphical error analyses. The obtained relative error s indicate that the developed model employed as an alternative approach monitoring the dewpoint pressure of gas condensate reservoirs when the required real data are not accessible.

Last modified: 2018-09-01 20:03:09