Asphaltenes, akin to the "cholesterol" of crude oils, can lead to significant flow issues in oil and gas processes, impacting the economy of oil recovery, transportation, and processing by raising operational costs. They elevate oil viscosity, diminish market value, and when they precipitate, pose flow challenges. Understanding asphaltene precipitation and phase behavior is crucial to address these flow issues. Conducting experimental investigations is time-consuming and limited by operational conditions. Therefore, accurate asphaltene modeling is vital to predict and manage precipitation. Despite research efforts, asphaltene behavior and improved thermodynamic models remain inadequately understood. This study focuses on modeling crude oil asphaltene precipitation under various operating conditions using different approaches, such as equations of state. Altering conditions like temperature and composition can trigger asphaltene phase separation. However, predicting precipitation and its effects are uncertain and require detailed thermodynamic investigations. Various studies have employed equations of state, including advanced one’s accounting for hydrogen bonding. However, uncertainties exist, necessitating systematic studies to adjust parameters for accurate predictions. The research objectives encompass comprehensive literature review, investigating asphaltene thermodynamic modeling gaps, and addressing these gaps. To overcome limitations of gradient-based optimization, a global optimization approach is used to correlate hydrogen bonding with binary interaction parameters of the Cubic Plus Association equation of state. This improves correlation and prediction capabilities, significantly enhancing modeling accuracy. Additionally, the influence of heteroatoms on asphaltene behavior is studied using a Cubic Plus Polar equation of state, effectively incorporating polarity effects. The developed approaches, global optimization, and heteroatom effects consideration can enhance asphaltene thermodynamic modeling efficiency, serving as valuable tools for future research in the field.
Click here to learn more: https://research.library.mun.ca/16015/