INVESTIGADORES
CISMONDI DUARTE Martin
congresos y reuniones científicas
Título:
A predictive model for hydrocarbon synthetic fluids based on the RKPR EOS
Autor/es:
CISMONDI DUARTE, M.; GOMEZ, M.J.; JARA, D.E.; MONTOYA, F.; TASSIN, N.G.; ZUÑIGA, S.
Lugar:
Eindhoven
Reunión:
Simposio; 27th European Symposium on Applied Thermodynamics (ESAT 2014); 2014
Resumen:
Inthe use of simulators for PVT and thermodynamic properties of reservoir fluidsfrom Equations of State (EOS) it is common practice to adjust or fit theconstants for the pseudo components representing the heavy fractions, in orderto match important measured properties like saturation pressure at thereservoir temperature. These fitting strategies do not necessarily lead to thebest characterization of the heavy fractions of the fluid but sometimes playthe role of correcting for more basic modeling limitations and may producedangerous extrapolations. Such limitations can be detected and analyzed throughthe modeling of synthetic fluids with trustable data available, where theconstants of defined components are well established and should not be modified.Inorder to have a consistent model with higher chances of good predictions andsafe extrapolations, it is important to reproduce reasonably the behavior ofthe different series of binary systems involved. In particular the mostasymmetric pairs which present immiscibility up to more than 1000 bar attypical reservoir temperatures, as it is the case of methane with heavyalkanes. These systems are also very sensitive to interaction parameters andplay an important role in many real fluids. If the modeling of those systems isappropriate, then the characterization of the heavy fractions will play therole it is supposed to play and will not have to account for deficiencies inthe modeling of defined components. In a recent work [1] it was shown that thethree-parameter RKPR cubic EOS [2] can successfully represent the phasebehavior of the most asymmetric mixtures of alkanes up to hyperbaricconditions, with clear superiority to the PR EOS. In this work, a newpredictive model for synthetic fluids is presented. It is based on the RKPR EOSwith a new correlation for the third parameter of alkanes and interactionparameters that were in turn correlated with the third parameter of the alkanealong each series of binary systems. Predictions for different natural gas andgas condensate synthetic fluids with data available in the literature arepresented and analyzed.