Study of CCRU first reformer reactor ∆P behaviour using multiple linear regression

Determinants and explanatory variables affecting the behaviour of the first reformer reactor ∆P are identified, with the aim of controlling it and avoiding a shutdown.

Ali Al Shehhi

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Article Summary

In this article, the significant increase in pressure drop across the first reactor in the catalytic reforming unit is studied using linear regression modelling. Initially, 10 variables were identified: the total lift gas flow, secondary lift gas, lift “A” partial ∆P, first heater inlet temperature, reactor inlet temperature, research octane number (RON)control temperature, unit feed, recycle gas flow, hydrogen to hydrocarbon ratio, and hydrogen flow to first reactor for elutriation. These variables were considered as explanatory variables for the response variable, which is the first reactor ∆P in this case. The variables were accepted or rejected based on the P-value with a significance screening indicator of α=0.05. Finally, six variables were shortlisted for further study, one of which is the RON control temperature. This was identified as the main explanatory variable behind the repaid increase in the first reactor ∆P as the unit severity increased during the period from July to October 2020 in addition to catalyst attrition. Both Microsoft Excel and Minitab Statistical software were used in the study.
Study background
A continuous catalytic reforming unit (CCRU) processes heavy naphtha to convert the naphthenes and normal paraffins into principally aromatic and iso-paraffins with higher octane number. The CCRU also produces hydrogen and light hydrocarbons. The main purpose is to obtain high octane number reformate for the motor gasoline pool. This study was initiated because the first reactor in the CCRU was facing a rapid increase in ∆P, up to ~1 kg/cm2 against normally <0.2 kg/cm2, during the period of August to November 2020 when there was change in operating conditions, especially in terms of RON. A summary of average RON during the last 10 years is illustrated in Table 1.

The study’s objective is to identify the determinants and explanatory variables affecting the behaviour of the first reformer reactor ∆P to control it and avoid any emergency shutdown and its reoccurrence.

Determining factors affecting ∆P in first reactor
There were several variables affecting the behaviour of the ∆P in the first reactor. A total of 10 variables were identified then each variable was tested for its significance
The basic method is to establish the linear relationship between the output (first reformer reactor ∆P) and the influencing or explanatory variable. The identified variables for the regression analysis are:

    Total lift gas flow
    Secondary lift gas
    Lift “A” partial ∆P
    Heater inlet temperature
    Reactor inlet temperature
    RON control temperature
    Unit feed
    Recycle gas flow
    Hydrogen to hydrocarbon ratio
    Hydrogen flow to first reactor for elutriation

From the basic multiple linear regression (MLR) equation, y = xβ, the basic form MLR can be expressed as:

y=β0 + β1x1 + β2x2 + β3x3 + β4x4 + β5x5 + β6x6 + β7x7 + β8x8 + β9x9 + β10x10

Initially, 10 variables were identified for the MLR. A list of data for these variables from 01/01/2020 to 22/10/2020 was used to conduct the analysis and calculations utilising Microsoft Excel and statistical software based on MLR modelling where:

y = First reformer reactor ∆P (response variable)
x1 = Total lift gas flow
x2 = Secondary lift gas
x3 = Lift “A” partial ∆P
x4 = Heater inlet temperature
x5 = Reactor inlet temperature
x6 = RON control temperature
x7 = Unit feed
x8 = Recycle gas flow
x9 = Hydrogen to hydrocarbon ratio
x10 = Hydrogen flow to first upper hopper for elutriation

The linear regression method was used to calculate the regression coefficients with 10 independent variables. The regression coefficients from β0 to β10 are respectively given as:

β0 = -0.933
β1 = -0.003578
β2 = -30.3
β3 = 29.5
β4 = 0.00343
β5 = 0.02986
β6 = -0.03099
β7 = -0.004933
β8 = 0.01719
β9 = -0.1847
β10 = 0.001375

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