PVT Fluid Characterization and Consistency Check for Retrograde Condensate Reservoir Modeling

Abstract

Retrograde gas condensate systems are complex systems as a result of the unique compositional changes that when the reservoir pressure is decreased. Correct selection of Equation of State (EOS) is necessary for proper fluid characterization so that the PVT behavior in the simulation model is a good representation of the reservoir fluid. High quality and accurate PVT data can reduce uncertainty in reservoir fluid properties and set the stage for reservoir engineering modeling whilst improving the technical work on which investment decisions are made. In order to obtain reliable PVT data for effective reservoir modeling, the following steps are essential: Acquisition of sufficient volumes of representative reservoir fluid samples. Proper examination and supervision of all field and laboratory experiments to ensure accuracy, consistency and validity of the resulting PVT analysis results. Results from the PVT experiments are imported into PVT software for validation in order to ascertain a good match between the simulated and experimental data. This process generates the Equation of State model required for material balance and other simulation studies for gas condensate reservoirs. The mass balance test is one of the methods that can be used to validate laboratory PVT data. It is a rigorous test for the evaluation of compositional consistency between feed composition, separator vapor and liquid compositions. Other laboratory PVT data validation means include Mass balance plot, Hoffman plot CVD/CCE comparison plots and Campbell diagrams. These plots serve as data quality assessment methods prior to their use for EOS characterization. PVT validation checks helps to confirm the true content of the fluid as either a rich or lean gas condensate and also confirm the Gas oil ratio of the system. Inaccurate PVT data can give misleading information that could cause a wrong evaluation of hydrocarbon in place. However, when these methods are properly applied it could lead to huge savings for the company as accurate results are obtained from reservoir simulation models which could aid optimization efforts and achieve incremental recovery.

A new approach for quality control of reservoir fluid composition data using live oil solubility parameter

“…For measuring the solubility parameter of live oil samples while considering the effect of pressure and temperature, internal pressure appears to be the most relevant method to be used [33]. Internal pressure (π) is defined as follows [33][34][35]: (2) where is coefficient of isobaric expansion of oil (1/K), and is coefficient of isothermal compressibility of oil (1/Pa, 1/MPa), T is temperature (K), and P is pressure (Pa, MPa). Both internal pressure and solubility parameter describe the same phenomenon, the cohesion of a liquid, but not in the same way [35].…”

“…Inaccurate fluid analysis can seriously affect all facets of chemical and petroleum engineering such as fluid properties measurement and construction of thermodynamic model for representative reservoir fluid, precise evaluation of hydrocarbon in place (i.e. amount of hydrocarbon likely to be contained in the reservoir), and reservoir development strategies [1,2].…”

An inclusive consistency check procedure for quality control methods of the black oil laboratory data

“…Buckley has shown that log (K i ) versus T c 2 yields a straight line with negative slope. Therefore, any observed deviations from the straight line in the Buckley plot illustrate existing of the composition measuring errors (Whitson and Brulé 2000;Akpabio et al 2014Akpabio et al , 2015. Modified Wilson plot is another thermodynamic method which could be applied for checking the fluid compositions reliability.…”

Investigation of gas condensate drop‐out effect on gas relative permeability by Lattice Boltzmann modelling

“…[40] This form of the interaction potential function behaviour is consistent with that of an isothermal process and can be appropriately applied for density ratios $7-8, which we deal with here. [32,44,50,51] In LB modelling, the macroscopic fluid density and velocity can be obtained using the fluid distribution functions. [40] To calculate the pressure throughout the domain, an equation of state (EOS) is required to be employed.…”

“…There are various forms of the interaction potential proposed by Raiskinmäki et al, Hyväluoma et al, Martys and Chen, and Qian et al Here, we used the function introduced by Shan and Chen as follows: where and are arbitrary constants . This form of the interaction potential function behaviour is consistent with that of an isothermal process and can be appropriately applied for density ratios ∼7–8, which we deal with here …”