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Prediction of Asphaltene Precipitation from Empirical Models

Abstract Asphaltene precipitation in the reservoir has proved to be a difficult problem to define and study. Field conditions conducive to precipitation include normal depletion, acid stimulation, gas-lift operations, and miscible flooding. Asphaltene precipitation is generally believed to be an irreversible process, which is the main reason it can have a profound impact on production operations. Investigations into asphaltene precipitation have been impeded by a shortage of experimental data and information on precipitation mechanisms. The aim of this work is to generate empirical models with other thermodynamic models to describe and predict precipitate formation models with a variety of reservoir fluids. Experimental asphaltene precipitation data on several live-oil at reservoir conditions were measured to study the effects of temperature, pressure, and composition on precipitate formation and the relationships between critical properties. Data generated by the model can be used to identify operating amount of asphaltene deposited under different conditions.