Simplifying the Task of Grouping Fluid Components in Compositional Reservoir Simulation

Abstract

Summary We present and test a new method for selection of pseudocomponents and averaging equation of state (EOS) parameters with excellent results. The new method is especially useful for compositional reservoir simulation with or without extended downstream process modeling. Introduction The main results from a compositional reservoir simulation are the production rates. Normally, these are stable oil and dry gas streams, but other streams may also be reported. The detailed description of the fluid compositions can therefore be reduced to some extent if the overall description of the fluid properties is acceptable. This is achieved by lumping the components into component groups called pseudocomponents. This reduces the computation time and the needed memory. The traditional way to prepare a fluid model with pseudocomponents is to group them based on personal experience and parameter regression. This requires a lot of experience and continuous practice, and probably represents one of the greatest obstacles for a reservoir engineer confronted with compositional reservoir simulation for the first time. This paper presents an automatic method of selecting pseudocomponents. We will compare the new method with other existing methods that automatically group components into pseudocomponents. The existing methods used in the comparison follow.The method of mole-weighted average with components grouped to have approximately equal mole fraction.The method of mass-weighted average with components grouped to have approximately equal mass fraction.The method of Newly et al. The method of Danesh et al. is not included in the comparison because it does not use the common basic EOS parameters, and it is difficult to port the method of Danesh et al. to other computer programs.

A novel three pseudo-component approach (ThPCA) for thermodynamic description of hydrocarbon-water systems

“…Other authors have chosen to form pseudocomponents which are approximately equal in size (Kay 1936;Pedersen et al 1982). In some more theoretically based models, components with similar properties are grouped together (Lee et al 1981;Montel and Gouel 1984;Danesh et al 1990;Schlijper and van Bergen 1991;Lomeland and Harstad 1995). In the last category of grouping methods, component groups are defined on the basis of EOS calculations performed on the original unlumped fluid descriptions (Mehra and Heidmann 1982;Li et al 1985;Newley and Merill 1991).…”

“…In the most primitive form, pseudo-component properties are calculated on the basis of pure component properties employing different averaging techniques (Hong 1982;Kay 1936;Pedersen et al 1982). In some more recent methods, the mixing rules of the EOS are utilized to calculate pseudo-component properties (Danesh et al 1990;Lomeland and Harstad 1995;Mehra and Heidmann 1982;Li et al 1985;Newley and Merill 1991;Leibovici 1993). Finally, a number of authors have used EOS calculations to adjust some parameters used in the property calculation methods (Wu and Batycky 1988;Li et al 1985;Newley and Merill1991).…”

Universal Fluid Characterization Using an EOS Based on Perturbation from n-Alkanes

“…One of the main reasons for the lack of theory is likely the unknown, implicit, non-linear relationship between phase behavior predictions and adjustment parameters such as T C , P C , V C , ω, volume-shift parameters, and BIPs. Different characterization methods have been proposed for different reservoir fluids (Whitson 1984;Stamataki and Magoulas 2001;Montel and Gouel 1984;Leibovici 1993;Lomeland and Harstad 1995); for example, gas condensates (Yarborough 1979;Lawal et al 1985;Pedersen et al 1988;Guo and Du 1989), volatile oils (Peneloux et al 1979;Whitson and Torp 1983), near-critical fluids (Zuo and Zhang 2000;Al-Meshari and McCain 2006;Hosein and Dawe 2011;Hosein et al 2013), and heavy oils (Krejbjerg and Pedersen 2006;Ghasemi et al 2011). However, P-T-x space that phase behavior spans is continuous.…”