A new experimental and modeling strategy to determine asphaltene precipitation in crude oil

Abstract

Asphaltene precipitation phenomenon which exhibits considerable influence on enhanced oil recovery (EOR) processes is taken into account as an important matter in the petroleum and chemical engineering processes/operational units. Available mathematical methods to investigate crucial aspects of this production problem (e.g., precipitation conditions and determination of amount of precipitated asphaltene) seem difficult to be implemented at a variety of process conditions and oil properties. Thus, it is important to evaluate the influences of different controlling variables on the asphaltene precipitation for practical purposes through introduction of proper mathematical/empirical correlations. In this research work, an experimental approach and response surface methodology (RSM) are employed to study the impacts of main factors, including pressure, molecular weight (Mw) of n-alkanes (n-pentane, n-hexane, and n-heptane) and dilution ratio on the asphaltene precipitation in a dead oil sample through a systematic parametric sensitivity analysis. The extent of precipitated asphaltene is mathematically modeled as a function of independent variables such as dilution ratio and molecular weight. Analysis of variance (ANOVA) technique is also conducted to examine the efficiency of the proposed model. It was found that the simple predictive tool works fairly well to estimate the precipitation values over a wide range of thermodynamic conditions. The correlation coefficient (R2) of 0.9908 and the mean absolute error percentage of less than 3.1% show a pretty good agreement between the modeling and experimental results. The RSM model appears to be a strong tool for calculation of asphaltene precipitation at statistic and dynamic conditions in oil industry.