TY - GEN
T1 - Fouling Modelling in Crude Oil Preheat Systems
AU - Loyola Fuentes, Jose
AU - Smith, Robin
AU - Jobson, Megan
PY - 2017
Y1 - 2017
N2 - Fouling in the pre-heat system for crude oil distillation has become one of the most challenging issues within the refinery industry. For a single crude oil distillation unit, the cost due to fouling can reach magnitudes of millions of dollars per year. Given a fouling model, deposition can be mitigated through the manipulation of heat exchanger tube wall temperatures, wall shear stress and cleaning of heat exchangers. However, the implementation of such strategies requires a mathematical model. Fouling models can be developed from laboratory tests, but such experimental work involves a significant amount of time and the controlled conditions during a test cannot be extrapolated to field processes with confidence. Fouling threshold modelling also presents drawbacks; since each fouling rate model is developed for a specific mechanism, and each parameter within these models can change significantly when the type of crude oil is changed. To overcome these problems, a new methodology for determining fouling models is proposed from on-line data, eliminating the need for laboratory experiments. Heat transfer coefficients coupled with different fouling mechanism models for individual heat exchangers are used to predict thermal and fouling behavior within a heat exchanger network, using reconciled measured data and parametric fitting. The model is able to split the fouling contributions of both shell and tube-side. Also, the reconciled data present no systematic and random errors. Each fitted model can be used for prediction of fouling conditions for operating decisions or optimization of cleaning schedules or retrofit.
AB - Fouling in the pre-heat system for crude oil distillation has become one of the most challenging issues within the refinery industry. For a single crude oil distillation unit, the cost due to fouling can reach magnitudes of millions of dollars per year. Given a fouling model, deposition can be mitigated through the manipulation of heat exchanger tube wall temperatures, wall shear stress and cleaning of heat exchangers. However, the implementation of such strategies requires a mathematical model. Fouling models can be developed from laboratory tests, but such experimental work involves a significant amount of time and the controlled conditions during a test cannot be extrapolated to field processes with confidence. Fouling threshold modelling also presents drawbacks; since each fouling rate model is developed for a specific mechanism, and each parameter within these models can change significantly when the type of crude oil is changed. To overcome these problems, a new methodology for determining fouling models is proposed from on-line data, eliminating the need for laboratory experiments. Heat transfer coefficients coupled with different fouling mechanism models for individual heat exchangers are used to predict thermal and fouling behavior within a heat exchanger network, using reconciled measured data and parametric fitting. The model is able to split the fouling contributions of both shell and tube-side. Also, the reconciled data present no systematic and random errors. Each fitted model can be used for prediction of fouling conditions for operating decisions or optimization of cleaning schedules or retrofit.
KW - Fouling
KW - Crude oil pre-heat train
KW - Data reconciliation
U2 - 10.1016/B978-0-444-63965-3.50070-2
DO - 10.1016/B978-0-444-63965-3.50070-2
M3 - Conference contribution
T3 - Computer Aided Chemical Engineering
BT - Proceedings of the 27th European Symposium on Computer Aided Process Engineering – ESCAPE 27
ER -