화학공학소재연구정보센터
Energy & Fuels, Vol.33, No.6, 5011-5023, 2019
Modeling of Asphaltene Deposition in a Packed Bed Column
Asphaltene deposit buildup in production pipelines and subsea flowlines greatly affects the production rate of oil and, hence, is a major concern for the upstream oil and gas industry. To better understand the behavior of asphaltenes under different production scenarios and operating conditions, the physics of asphaltene deposition and effectively develop mitigation strategies to overcome this problem, experimental techniques, and modeling methods are extremely important. Recently, deposition tests using a packed bed column have been performed to measure and quantify asphaltene deposition in the laboratory. This work focuses on the development of a modeling technique to simulate the process of asphaltene deposition occurring in the packed bed column. A computational fluid dynamics model has been developed to analyze the multi-step process of asphaltene phase separation, aggregation, diffusion, and deposition. Three-dimensional transient flow simulations have been performed using an indigenous in-house finite element solver developed on MATLAB platform. A surface deposition mechanism has been employed to capture asphaltenes deposited on the packed bed spheres. The effects of precipitant, precipitant concentration, and experimental run time on the extent of deposition have been studied in detail. It has been found that the magnitude of asphaltene deposition, the deposition rate, and consequently, the deposition risk increase with an increase in the concentration of phase-separated asphaltene primary particles and the driving force for precipitation and deposition. The model has also been modified to comprehend the effect of chemical dosage on asphaltene deposition. The developed methodology can be applied to analyze the effectiveness of industrially available asphaltene deposition dispersants and solvents and, hence, help us in developing strategies for asphaltene deposition problem mitigation and remediation. This study provides a computationally efficient modeling technique that helps in simulating asphaltene deposition studied in an experimental setup, recognizing the competing phenomena of asphaltene aggregation and deposition that are simultaneously taking place in the system and, hence, providing a better understanding of the asphaltene deposition process.