Modeling Strategies for Crude Oil-Induced Fouling in Heat Exchangers: A Review

Abstract

Semi-empirical fouling models have proven more effective in predicting the fouling behavior of crude oils in heat exchangers. These models have aided refineries in optimizing operating conditions to minimize or eliminate fouling in preheat exchangers. Despite their complexity, the models continue to improve in approximating real behavior by taking into account previously neglected aspects. This paper summarizes these findings from various studies along with highlighting different factors which were considered to enhance the predictability of the models. A critical analysis is presented to emphasize that activation energy in the deposition term varies depending on the physical processes involved and may not conform to the precise definition of activation energy. Two primary modeling approaches for crude oil fouling have emerged, i.e., deterministic and threshold models. Threshold models have gained more attention due to their fewer adjustable parameters. The stability or compatibility of crude oils has a substantial impact on asphaltene deposition, which is a major contributor to fouling. However, incorporating this factor into fouling models has received little attention. The inclusion of parameters for inorganic fraction and ageing has increased predictability by accurately estimating the fouling thickness. The use of CFD to analyze fouling mechanisms is promising, particularly for complex geometries. The dynamic and moving boundary modeling approach has potential to broaden the applicability of fouling models.

Environmental Significance of Fouling on the Crude Oil Flow. A Comprehensive Review

“…The asphaltenic components of crude oil are the biggest components that settle in refinery preheat trains, although little is understood regarding their structure and behavior [1][2][3][4][5][6][7][8][9][10][11][12][13].…”

“…As described by Myers et al, a portion of the crude oil is upgraded before it enters the pipeline. Their work aims to improve oil flow through the pipeline [10].…”

The Foundation and Validation of Sigmoid-Typed Functions for Fouling Formation Modelling of Crude Oil Flows

“…Deposit formation was observed increasing with temperature at fixed flow velocity [11], but the surface temperature of deposit usually decreases as fouling layer grows even though the wall temperature increase [12]. On the other side, removal term is highly susceptible to flow geometry and this led the need to convert a scaling factor by comparing experimental data toward different geometries [13]. The Other factors are due to filterable solids present in the opportunity crudes, velocity driven deposit, crude incompatibility, thermal degradation and solubility crude blending [14].…”

“…The practical fouling model needs to cover all aspects mechanism involved during fouling development process. Recent consideration to describe deposition term may come up with introducing temperature dependent of crude oil properties to involve physical processes factor [13]. The challenges also come from the shifting balance between thermal and hydraulic impacts of fouling caused by ageing that may cause error in estimating foulant layer due to increase of thermal conductivity [15].…”