Asphaltene Precipitation Envelope Prediction by Using Python

Abstract

Changes in temperature, pressure, and/or oil composition resulting from mixing with other crude oils or gas injection often affect the solubility of asphaltenes in crude oils. This might lead to the precipitation and deposition of asphaltene, permeability reduction, the obstructing of wells and other surface infrastructure, and eventually a reduction or stoppage of production, which has a considerable economic impact. Therefore, it is essential for both upstream and downstream processing to be able to understand and anticipate asphaltene phase behaviour in order to implement the correct preventative and remedial solutions. To forecast and simulate the precipitation of asphaltene, one of two theories is used: the solubility theory or the colloidal theory. In this study, the former one was applied by using cubic-plus-association equation of state (CPA EOS) to predict the asphaltene phase envelope and determine the precipitation zones for different concentrations of asphaltene of an Iraqi live oil using Multiflash software and Python depending on real field data. The results showed that the zone of precipitation becomes smaller with increasing asphaltene concentration, at which the largest area was at the lowest concentration of 0.04 (as a weight ratio of asphaltene/oil), and then it decreased little by little until it reached the smallest area at the bubble point pressure curve (at the highest concentration of 0.32). This confirms the effect and force of the large asphaltene precipitation in light oils, i.e., the low concentration of asphaltene. Also, the highest concentration of asphaltene precipitation occurs at the bubble pressure point.