Robust correlation to predict dew point pressure of gas condensate reservoirs

When the bottom-hole flowing pressure in a gas condensate reservoir drops below the dew point pressure,liquid starts to build up around the well bore resulting in gas productivity decline.For this reason it is important to be able to accurately either measure or estimate the dew point pressure.The condensate formed in the reservoir will not flow until its saturation reaches the critical saturation and in many cases it might not be entirely recovered.It order to maximize gas production and condensate recovery,the reservoir pressure must be maintained close to the dew point pressure.Several attempts have been made to predict the dew point pressure in case the gas sample becomes unavailable or measured value is unreliable.Unfortunately,most of these attempts have minor success rates and are based on limited data.In this paper we present a robust,cheap,and easy model for predicting the dew point pressure for gas condensate reservoirs.The new model is an intelligent based model called“Gene Expression Programming”that is carried out to generate a precise and accurate correlation to estimate the dew point pressure in condensate gas reservoirs.The new model has been trained and tested using a large data bank collected for the literature.Precision of the suggested correlation has been compared to published correlations.The validity of this model has also been compared to experimental data and other published correlations.

Developing a K-value equation for predict dew point pressure of gas condensate reservoirs at high pressure

This paper proposed a new empirical K-value equation is developed to calculate dew pressure for gas condensate reservoirs.This equation is applicable in the wide ranges of composition,temperature,and pressure by considering the effect of composition via two equations for normal boiling point and critical temperature of the mixture.The range of dew pressure,temperature,heptane plus mole fraction,methane mole fraction,N2 mole fraction,CO2 mole fraction,and H2S mole fraction are fallen into 2666.7e9655 Psia,40e350.87
F,0.0021e0.213,0.3344e0.9668,0e0.4322,0e0.0864,and 0e0.942 respectively.As an important point,the proposed equation has any adjustable parameters,in addition,this equation indicates that in order to predict of dew pressure of gas condensate reservoirs,trial and error was not needed and therefore,computational speed increases beyond the accuracy.Moreover,the accuracy is validated by comparing against the experimental data of 81 gas condensate reservoirs samples from published literature and the results of Wilson,Whitson,and Ghafoori equations.Compared to the experimental data,the absolute average deviations of dew pressure calculations for the proposed equation,Wilson,Whitson,and Ghafoori were 7.6%,97.6%,99.4%,and 94.9%respectively.

Adsorption,selectivity,and phase behavior in organic nanopores for shale gas and oil development

In a shale gas and oil reservoir,hydrocarbon fluids are stored in organic nanopores with sizes on the order of~1-100 nm.The adsorption,selectivity,and phase behavior of hydrocarbons in the nanopores are crucial for estimating the gas-in-place and predicting the productivity.In this study,to understand the characteristics of the phase behavior of multicomponent hydrocarbon systems in shale reservoirs,the phase behavior of a CH_(4)/n-C_(4)H_(10)binary mixture in graphite nanopores was investigated by Grand Ca-nonical Monte Carlo(GCMC)molecular simulation.The method for determining the dew-point pressure and bubble-point pressure in the nanopores was explored.The condensation phenomenon was observed owing to the difference in the adsorption selectivities of the hydrocarbon molecules on the nanopore surfaces,and hence the dew-point pressure(and bubble-point pressure)of hydrocarbon mixtures in the nanopores significantly shifted.The GCMC simulations reproduced both the higher and lower bubble-point pressures in nanopores in previous studies.This work highlights the crucial role of the selec-tivity in the phase behavior of hydrocarbons in nanopores.