A Linear Extrapolation of Normalized Cohesive Energy (LENCE) for fast and accurate prediction of the asphaltene onset pressure

Abstract

Knowledge of the conditions at which asphaltenes precipitate from petroleum fluids is useful in the development of enhanced oil recovery scenarios and field development plans. In this work we present a semi-empirical linear model for approximating onset pressure by means of a Linear Extrapolation of Normalized Cohesive Energy (LENCE). A normalized cohesive energy function is found to correlate linearly with temperature along the asphaltene onset curve for several crude oils from different regions. The linear trend is observed from simulation results using the perturbed-chain version of the Statistical Associating Fluid Theory Equation of State (PC-SAFT EoS). LENCE can be used to approximate the asphaltene onset pressure (AOP) for petroleum fluids at different temperatures from knowledge of two experimental onset pressures. Several case studies are presented to demonstrate the capability of LENCE to accurately predict asphaltene onset pressure as well as detecting experimental uncertainties in reported measurements from near infrared (NIR) and high pressure microscopy (HPM) experiments. LENCE model can reproduce AOP modeling results from PC-SAFT with an average absolute percent deviation of 2.38%, with 5 times faster computational speed. It is found that PC-SAFT predicts a minimum temperature at which an upper asphaltene onset exists. Below this temperature, asphaltenes are inherently unstable in solution as predicted by PC-SAFT. This behavior seems to be a characteristic of SAFT-based models and is not yet supported by experimental evidence. Compared to PC-SAFT, the LENCE model exhibits improved characteristics for the liquid-liquid phase boundary in the low temperature region.