An Approach for Characterization and Lumping of Plus Fractions of Heavy Oil
- Ivan Rodriguez (University of Stavanger) | Aly A. Hamouda (University of Stavanger)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- April 2010
- Document Type
- Journal Paper
- 283 - 295
- 2010. Society of Petroleum Engineers
- 5.2.2 Fluid Modeling, Equations of State, 5.5 Reservoir Simulation, 5.3.9 Steam Assisted Gravity Drainage, 4.1.5 Processing Equipment, 5.2.1 Phase Behavior and PVT Measurements, 1.8 Formation Damage, 5.2 Reservoir Fluid Dynamics, 4.3.3 Aspaltenes
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Heavy-oil fluids contain large concentrations of high-molecular-weight components, including a large content of the plus fractions, such as C7+.
Different approaches have been developed to characterize the petroleum plus fractions to improve prediction of the pseudocomponents properties by equations of state (EOSs).
A method is developed in this work to split the plus fraction into single carbon numbers (SCN), generating the mole fraction and the respective molecular weight. The developed method is based on the relationships between three-parameter gamma (TPG) distribution, experimental mole fraction, molecular weight, and SCN data obtained from the literature and industrial contacts. TPG is used to fit the trend of the compositional analysis. The characterized mole distribution as a function of SCNs is generated by integrating the TPG between the limiting molecular weights (LMw). The limiting molecular weights are determined simultaneously during the integration process by fitting the characterized and experimental mole fractions.
The developed method is easy to use. In addition, the approach is not dependent on the assumption that only normal carbon numbers exist in the composition resulting on fixed molecular weights for each single carbon number.
There are several correlations generated to predict physicochemical properties as a function of SCNs. Those correlations have been originally developed to work with light oil. Our approach is combined with some of the correlations and is tested for heavy-oil samples to identify the ranges in which they can be applied. Two lumping schemes are used to group the SCNs into pseudocomponents. The properties for each pseudo-component in this work are used to predict pressure/volume/temperature (PVT) data, constant volume depletion, using the Peng-Robinson EOS (PR-EOS), and the PVTP™ commercial simulator.
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