摘要
Cubic equation-of-state solid models are one of the most widely used models to predict asphaltene precipitation behavior.Thermodynamic parameters are needed to model precipitation under different pressures and temperatures and are usually obtained through tuning with multi asphaltene onset experiments.For the purpose of enhancing the cubic Peng–Robinson solid model and reducing its dependency on asphaltene experiments,this paper tests the use of aromatics and waxes correlations to obtain these thermodynamic parameters.In addition,weighted averages between both correlations are introduced.The averaging is based on reported saturates,aromatics,resins,asphaltene(SARA)fractions,and wax content.All the methods are tested on four oil samples,with previously published data,covering precipitation and onset experiments.The proposed wax-asphaltene average showed the best match with experimental data,followed by a SARA-weighted average.This new addition enhances the model predictability and agrees with the general molecular structure of asphaltene molecules.
Cubic equation-of-state solid models are one of the most widely used models to predict asphaltene precipitation behavior.Thermodynamic parameters are needed to model precipitation under different pressures and temperatures and are usually obtained through tuning with multi asphaltene onset experiments. For the purpose of enhancing the cubic Peng–Robinson solid model and reducing its dependency on asphaltene experiments, this paper tests the use of aromatics and waxes correlations to obtain these thermodynamic parameters. In addition, weighted averages between both correlations are introduced. The averaging is based on reported saturates, aromatics, resins, asphaltene(SARA) fractions, and wax content. All the methods are tested on four oil samples, with previously published data, covering precipitation and onset experiments. The proposed wax-asphaltene average showed the best match with experimental data, followed by a SARA-weighted average. This new addition enhances the model predictability and agrees with the general molecular structure of asphaltene molecules.
