thermodynamic considerations. Here, a base case feed yield data (in this case a
straight run waxy distillate) at a conversion of 75 % using zeolite catalyst was used.
Yields from all other feedstocks (including those which had been hydrotreated)
were related by first principle kinetic and thermodynamic considerations to the base
case. A short and simple computer program was used for this purpose, and it was
also possible to simulate the effect of changing the quantity of zeolite catalyst by
this means. The results of these computerized calculations were checked against
existing plant data before being incorporated into the study.
In other processes such as hydrocracking, hydrotreating, visbreaking, etc., care
was taken that only proven yield data or correlations were used.
Catalytic reforming yield data was obtained from a correlation which related yield
to severity for a basic naphthene and aromatic content of the feedstock. A whole range
of severity operations from 95 to 105 O.N. (Research) clear was encompassed in the
study. Spot checks of the predicted yield by this method against actual yield from an
operating unit showed that the method was viable and acceptably accurate.
Basic Economic Data
Having developed the physical yield structure of the “model,” the next step was to
complete the basic data by providing investment and maintenance costs.
There is, of course, a considerable wealth of plant cost data available to a
contractor from the projects he has completed over the years. However, there is
always the need to analyze these costs and to review them in terms of up-to-date
material and labor cost changes.
For this study, a large amount of cost data was statistically analyzed for each type
of plant. From this analysis, a base cost and an empirical exponential factor was
developed in order to relate a total investment cost to capacity in as realistic way as
possible. This relationship can be expressed mathematically in a nonlinear form.
C ¼ C o T=T o
ð
Þ
k
(38)
where
C = Investment cost
C o = Base cost at a base throughput To
T = New throughput
K = An empirical constant
The inclusion of a nonlinear form for investment costs in a linear program
required special consideration, and we shall see later how this was utilized.
In the models, many of the units considered were licensed processes, for which a
royalty would be paid. A value in terms of a paid-up royalty in dollars per barrel of
throughput was included in the investment. Where chemicals and catalysts were
used, the first inventory of these was also included as part of investment.
776
D.S.J. Jones and P.R. Pujado ´
straight run waxy distillate) at a conversion of 75 % using zeolite catalyst was used.
Yields from all other feedstocks (including those which had been hydrotreated)
were related by first principle kinetic and thermodynamic considerations to the base
case. A short and simple computer program was used for this purpose, and it was
also possible to simulate the effect of changing the quantity of zeolite catalyst by
this means. The results of these computerized calculations were checked against
existing plant data before being incorporated into the study.
In other processes such as hydrocracking, hydrotreating, visbreaking, etc., care
was taken that only proven yield data or correlations were used.
Catalytic reforming yield data was obtained from a correlation which related yield
to severity for a basic naphthene and aromatic content of the feedstock. A whole range
of severity operations from 95 to 105 O.N. (Research) clear was encompassed in the
study. Spot checks of the predicted yield by this method against actual yield from an
operating unit showed that the method was viable and acceptably accurate.
Basic Economic Data
Having developed the physical yield structure of the “model,” the next step was to
complete the basic data by providing investment and maintenance costs.
There is, of course, a considerable wealth of plant cost data available to a
contractor from the projects he has completed over the years. However, there is
always the need to analyze these costs and to review them in terms of up-to-date
material and labor cost changes.
For this study, a large amount of cost data was statistically analyzed for each type
of plant. From this analysis, a base cost and an empirical exponential factor was
developed in order to relate a total investment cost to capacity in as realistic way as
possible. This relationship can be expressed mathematically in a nonlinear form.
C ¼ C o T=T o
ð
Þ
k
(38)
where
C = Investment cost
C o = Base cost at a base throughput To
T = New throughput
K = An empirical constant
The inclusion of a nonlinear form for investment costs in a linear program
required special consideration, and we shall see later how this was utilized.
In the models, many of the units considered were licensed processes, for which a
royalty would be paid. A value in terms of a paid-up royalty in dollars per barrel of
throughput was included in the investment. Where chemicals and catalysts were
used, the first inventory of these was also included as part of investment.
776
D.S.J. Jones and P.R. Pujado ´