Real-Time Investigations of Aggregation of Sulfur Rich Asphaltene and their Implications for Groundwater/Soil Remediation

Abstract:

Asphaltenes generally aggregate, then precipitate and deposit on the surfaces, with ensuing implications crucial for remediation of crude oil contaminated groundwater/soil. Extensive research based on asphaltene with low sulfur content as a model system has concluded that colloidal asphaltene aggregates display universal characteristics. However, it is unclear whether existing aggregation theories can be used to predict aggregation kinetics and morphology of sulfur rich asphaltene. We investigated the particle-by-particle growth of aggregates formed from sulfur rich asphaltene, commonly found in heavy oil. The aggregation kinetics, evolution of colloidal structure, and aggregate morphology were examined by analyzing aggregate growth curve, particle size distribution, and fractal structure, respectively. We based our analysis on advanced image processing algorithms, which enabled the examination of sulfur rich asphaltene aggregation in greater detail. Our measurements showed that aggregates assembled from sulfur rich asphaltene are time-dependent self-similar structures with morphology and growth rates aligned with a crossover behavior from reaction limited aggregation to diffusion limited aggregation. We observed cluster coalescence to have an effect on the corresponding cluster size distribution when compared to the classical Smoluchowski size distribution. These results highlight the need to quantify and correlate non-classical and classical growth mechanisms in future studies to help tune the aggregation properties of sulfur rich asphaltenes. We also investigated the effect of precipitant concentration on aggregate structure. Our results showed that higher precipitant concentration leads to a more compacted aggregate structure while precipitant near to onset point results in a less compact structure. It is suggested that aggregates with high fractal dimensions are likely to have high density of nanoscale roughness which could enhance the hydrophobicity of interfaces when they deposit on the sand surface. Findings obtained from this study advance our current understandings on the fate and transport of heavy oil contaminants in the subsurface environment, which will have huge implications for designing more efficient remediation technologies for contaminated sites.