Developing of Scaling Equation with Function of Pressure to Determine Onset of Asphaltene Precipitation

Abstract

In this study a simple and applicable scaling equation as a function of pressure, molecular weight, dilution ratio (solvent) and weight percent of precipitated asphaltene has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of different precipitants (solvents) and the amount of solvent at onset point. Since increasing the pressure of crude oil decreases the amount of asphaltene precipitation, the effect of reservoir pressure has been taken into account in developing this equation. By considering the effect of reservoir pressure in developing the scaling equation and application of a genetic algorithm, the unknown parameters of the scaling equation are simultaneously and without any reservation obtained. The most important application of this unique equation is in the determination of critical point of asphaltene precipitation, known as onset point, and asphaltene precipitation in gas injection operations for enhanced oil recovery. The results predicted using the scaling equations are compared with literature precipitation data and it is shown that they are in good agreement with experimental data. The scaling equation can be used in the design of gas-injected reservoir to prevent precipitation of the asphaltene aggregates in the reservoir.

Modeling Asphaltene Precipitation by n-Alkanes from Heavy Oils and Bitumens Using Cubic-Plus-Association Equation of State

“…Besides the solubility model and equation of state, other approaches have been employed to study asphaltene precipitation from petroleum fluids such as the scaling equation, − micellization model, − aggregation model, , and integral equation theory . These methods may qualitatively or even quantitatively describe the asphaltene phase behavior.…”

Prediction of Asphaltene Precipitation: Learning from Data at Different Conditions

“…To test capabilities of the BBN model, the predictions by the model have been compared to those obtained using the new scaling model 27 and experimental data of other studies. 20 Considering the importance of the pressure effect on the asphaltene precipitation in the reservoirs, the variation of the asphaltene weight percent with pressure was obtained from the BBN model.…”

“…Menshad et al included the effect of the pressure on the nucleation onset and the amount of asphaltene precipitation in the scaling model. In the new scaling model, the relation between the dilution ratio and the molecular weight of diluents and the amount of asphaltene precipitation has been presented in two variables x and y as follows: x = R M w Z and y = wt % R Z ′ …”

“…Thermodynamically, asphaltene precipitation is not independent of the reservoir pressure. However, the effect of the pressure is not included in the scaling model developed by Rassamdana et al 18,20 Menshad et al 27 included the effect of the pressure on the nucleation onset and the amount of asphaltene precipitation in the scaling model. In the new scaling model, the relation between the dilution ratio and the molecular weight of diluents and the amount of asphaltene precipitation has been presented in two variables x and y as follows:…”

Monodisperse Thermodynamic Model Based on Chemical + Flory–Hüggins Polymer Solution Theories for Predicting Asphaltene Precipitation

“…Predictive tools based on scaling equation, corresponding states, and correlations have also been reported in the literature. ,,− These tools may, however, be limited to specific systems. Recently, application of mathematical correlations has been investigated for predictions of the amount of asphaltene precipitation. ,, Ashoori et al have used the artificial neural network (ANN) in comparison with the scaling laws and found out that the prediction results of the latter network are more accurate than the modified scaling equations proposed by Rassamdana et al and Hu et al , However, ANN based models should be used very carefully because they may face over-fitting or under-fitting problems.…”