The fouling of oil quench tower internals is a recurrent problem for ethylene plants and it is important to monitor the rate of fouling so that mitigating steps can be taken and cleaning of the tower can be planned. The most useful instruments for monitoring the fouling of the OQT are differential pressure measurements across some or all of the sections of packed beds or trays. When the measured pressure drop across a section of internals is higher than design and growing, this is usually due to fouling of that section. Unfortunately, normal variations in plant operation, including feed rates and feed slates, reflux flows, temperatures and pressures cause enough variation in the measured differential pressure(s) that it can be very difficult to see an increase due to fouling until it is very large; this reduces the time available to plan a response to the fouling.
A useful tool for improved monitoring of fouling progression is a prediction for the differential pressure which accounts for variation due to process variables. An accurate prediction can be compared to the measured pressure drop across a section of internals to determine if there is a growing deviation between the measured and predicted values. By eliminating the normal process variation, fouling can be detected when it is less advanced and appropriate action taken.
This paper will describe the development of a regression equation for prediction of the differential pressure across a section of trays in an oil quench tower. Topics included will be the approach to selecting variables for the regression, a demonstration of its accuracy and a description of some success using the prediction and finally, some weaknesses of the equation.
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