New Strategic Method to Tune Equation-of-State for Compositional Simulation

Abstract

Abstract Since the plus fraction of reservoir fluids has some uncertainty in itsmolecular weight and critical properties, equation-of-state, EOS, are generallynot predictive without tuning its parameters to match experimental data. Tuningof the EOS is found to be the best method for improving the predictions ofcompositional reservoir simulators. The proposed strategy for tuning EOS consists of seven steps:split thelaboratory plus fraction to single carbon number groups, SCN, usually up to SCN44; the last component will be C45+,use set ofcorrelations to calculate the critical properties and acentric factor for eachSCN group,match the saturation pressure at reservoir temperature byaltering the measured value of the molecular weight of the plus fraction usingthe extended composition,group SCN groups to multiple carbon numbergroups, MCN,assign critical properties and acentric factor for each MCNgroup,rematch the saturation pressure at reservoir temperature using thegrouped composition, andmatch the volumetric data by regressing on volumeshift parameters of all components in grouped composition. This paper shows an accurate method to split the plus fraction to SCNgroups. The most accurate set of correlations to calculate the criticalproperties and acentric factor for each SCN group that will result in a smalladjustment for the molecular weight of the plus fraction when saturationpressure is matched using the extended composition. The proposed strategygroups the extended composition to eight pseudocomponents. The binaryinteraction coefficients between hydrocarbons and between hydrocarbons andnon-hydrocarbons are set to zero which dramatically reduces the simulationtime. The strategy proposed in this paper for tuning EOS to match experimentaldata has been tested for a wide range of C7+ mole% (4 -25) which covers gas condensate and volatile oil samples. The scope of thispaper is to come up with an accurate and systematic technique for tuning an EOSfor use in compositional simulation. Introduction In order to describe the phase behavior of a reservoir fluid and calculateits volumetric properties, an EOS requires the values of critical pressure, critical temperature, and acentric factor for each component. There are severalcorrelations in the literature for calculating critical properties and acentricfactor for each SCN group. Together with the molecular weight, these properties aresufficient for simpler property prediction models. The liquid densityinformation represented by specific gravity can also be considered a physicalconstant for many models.