design of a crude distillation unit and its preheat...
TRANSCRIPT
Design of a crude distillation unit and
its preheat train
By Božidar Aničid and Tibor Kuna
Contents 1 Introduction ..................................................................................................................................... 1
2 Process description.......................................................................................................................... 2
2.1 Product and feedstock prices .................................................................................................. 4
3 Model results ................................................................................................................................... 6
3.1 Economic performance ........................................................................................................... 7
3.2 Sensitivity analysis ................................................................................................................... 9
3.2.1 Summer – winter scenarios ........................................................................................... 11
4 Future work ................................................................................................................................... 12
5 Conclusion ..................................................................................................................................... 13
6 Acknoledgements .......................................................................................................................... 13
7 Bibliography ................................................................................................................................... 14
8 APPENDIX A ................................................................................................................................. 15
1
Abstract
Our simulated model of a crude distilation unit, its preheat train and natural gas burning furnace
gives clear insight into what kind of profits can be made if the heat integration is done correctly and
feed composition selected wisely. Three different feed stocks namely Iraq heavy crude (Basrah), Iran
heavy crude (Iranhy) and North sea Brent Blend (BrentBL) are used. A feed composition such that
every feed stock represented one third in weight percent, was selected to be the base case in the
preheat train optimization. In second part of this work a feed composition optimization is also
performed. The preheat train consists of heat exchangers that incrementally heat up the crude feed
using hot streams from the atmospheric distillation unit pumparounds and natural gas combustion
flue gases.
The internal rate of return for this similated unit capable of distiling 20 000 ton/day of crude without
integration was calculated to be 59%, and for an integrated process 76%. The optimal feed
composition in the year 2009 was - BrentBL : Iranhy : Basrah = 0 : 0,4 : 0,6.
1 Introduction
The advancement of computer power and dedicated software packages has given us the ability to
integrate and optimize industrial processes like never before and thus bringing water and energy
usage to a minimal, because water and energy are no longer seen as commodities, but as valuable
assets. Companies must plan and execute their processes so that they are within ecological standards
and provide reasonable profit not only today but also in the near future. Most of the times this is
easier said than done. They can be challenging to optimize, but provide great rewards if they are
brought up to date correctly.
A lot of refineries running today were built in the 80's or late 70's when energy was cheap, and when
the investors did not devote much attention to the costs of energy. Because of that leading oil
companies carried out rationalization and suggested energy-saving programs. These programs
consist of the following actions: (1) (2).
Continuous monitoring of energy costs,
identifying the places of irrational energy consumption and preparing the energy saving
project
modernization of equipment and introduction of computer management,
reconstruction of equipment and intensification of the maintenance process.
The prices of products in the petrochemical world are quite volatile because of the constantly shifting
crude oil market, rising global demand, and the geopolitical situation. Therefore it is desirable that
refineries are capable of operating with different crude oil compositions.
2
2 Process description
The described process is for the base case where the crude mix at the begining consists one thrid of
the Iranian heavy crude (IRANHY), one third North sea Brent blend (BrentBL), and one third Iraqi
heavy crude (BASRAH) by weight percent. All of these assays can be found in the Aspen Plus library.
Their specific properties are described with the use of a wast array pseudo components. In order to
simulate effect of different feed composition on annual profit, different feedstock combinations have
been used. The API gravity for the different feedstock combinations can be seen in table 1.
Table 1-API gravity for different feedstock combinations.
Basrah 0 0,8 0,6 0,4 0,2 1 0,8 0,6 0,4 0,2 0 0,6 0,4 0,2 0 0,4 0,2 0 0,2 0 0
Iranhy 1 0,2 0,4 0,6 0,8 0 0 0,2 0,4 0,6 0,8 0 0,2 0,4 0,6 0 0,2 0,4 0 0,2 0
BrentBL 0 0 0 0 0 0 0,2 0,2 0,2 0,2 0,2 0,4 0,4 0,4 0,4 0,6 0,6 0,6 0,8 0,8 1
API Gravity 33,6 32,6 32,1 31,5 33,7 34,5 33,9 33,4 32,8 32,3 35,2 34,7 34,1 33,6 36,0 35,4 34,9 36,7 36,2 36,2 37,4
Preflash tower
The crude oil that is entering the preflash tower (FEED) is at 20°C and is firstly preheated up to 154°C
after passing through the preheat train which consists of two heat exchangers (B12, B11) which
recover heat from the flue gases that come from the natural gas combustion. The Preflash tower (PF)
has 10 equilibrium stages, and in this simulation the preheated crude enters in the bottom (stage 10)
at a rate of 20 000 ton/day.
The crude is then directed towards the PF furnace which was replaced with a heat exchanger (B16)
for the purpose of the simulation. This heat exchanger (B16) recovers heat from the reactor (B14).
The crude then reaches its desired temperature of 232°C at 4 bar. Steam (STEAM-1) is also
introduced at the bottom of the column. The base case furnace heat duty is 52 MW, while the
condenser duty is 26 MW.
The top stream (LIGHT) which consists of the lightest components, is drawn at the top of the column
and purged. Although in real life this wouldn't be economical since you could use it as a feedstock for
the furnaces or sell it as liquefied petroleum gas (LPG), but for this simulation none of the previously
mentioned uses could be employed since the stream is too complicated to be used as a feedstock
(because of pseudo components), and it has an API of 89 which is not high enough to be classified as
LPG (3). In order to obtain necessary heat in the furnaces natural gas is used. It's composition is much
simpler and currently it's price is lower compared to LPG price (4).
For the main distillate light naphta (LNAPHTA) in the PF tower a design specification was set in Aspen
Plus so that it always has an API of 75 (3). The PF is represented by the blue color in figure 1.
Atmospheric distillation unit
The heavier components of the crude oil that leave at the bottom of the preflash tower (ADU-1),
then go through the second preheat train which consist of two heat exchangers (B2, B10) that
increase its temperature from 215°C to 273°C. These two heat exchangers recover heat from the
ADU pumparounds and flue gas from natural gas combustion in the reactor (B14). Finally the
3
preheated crude enters the furnace which gives the crude its final temperature of 380°C. Just as in
the preflash unit, the furnace in the ADU is replaced with a heat exchanger (B3) for the simulation
purposes. The furnace vaporizes a major portion of the crude and feeds this vapor-liquid mixture into
the atmospheric distillation tower. The overflash in Aspen Plus is set to 3%.
The ADU has two pumparounds, three sidestrippers and just like in the PF, its own steam supply (S5)
at the bottom. The steam serves to strip any residue and prevent excessive thermal cracking of crude
due to high temperatures (2). The pumparounds are used to reduce the vapor flow in the column
and allow for heat recovery. The first pumparound is located from stage 8 to 6 and the second from
stage 14 to 13. They recover 15,7 and 22,2 MW respectively.
The three sidestrippers are present in order to draw various side streams at different locations, in
our case from stage 18, 13 and 6. The draw locations represent the temperature range of the liquid
products that we can collect from the given draw location. The side products that are drawn from the
three sidestrippers are kerosene, diesel and atmospheric gas oil. The sidestripper are defined with a
design specification so that they always draw a mixture with a specified API no matter what the feed
composition. The first sidestripper draws a fraction with API of 57 (KEROSENE), the second is set to
API of 40 (DIESEL) and the last with an API of 27 (AGO) (3).
The base case furnace duty for the ADU is 121 MW, while the condenser duty is 96 MW. The ADU is
represented by the yellow color in figure 1.
Stoichiometric reactor and steam generation
The natural gas flow rate (NG) towards the reactor (B14) is such, that both furnace duties were
covered, so for the base case 173 MW. The reason why reactor is used for simulation of natural gas
combustion is easier simulation of mentioned process. As stated before, both furnaces were replaced
by two heat exchangers (for easier process simulation), which transfer the required heat duty from
the natural gas combustion reaction to the crude. Air, which is also needed in the combustion, is
supplied through the stream (AIR). The reactor is represented by the green color in fig. 1.
The steam needed for the sidestrippers (STM-1, STM-2, STM-3) is generated by heating the water
stream (WTR) with the recovered heat from the flue gases. The heat recovery is organized so that
water coming in (WTR) is brought up to the specified pressure of 4 bar by the pump (B9), then it
reaches boiling temperature in the heat exchanger (B8). The vaporization occurs in heat exchanger
(B4). The steam then flows towards the last heat exchanger (B7) which gives its final temperature of
220°C. This generated steam (S9) is then combined with an auxiliary steam (CU-STEAM) in the mixer
(B5).
Finally the steam is sent towards a splitter (B6) which splits it into six streams (S13, STM-1, STM-2,
STM-3, S5, STEAM-1), and then distributes them to all the units, except for (S13) which is purged.
Reason why S13 is present is easier convergence.
4
Figure 1 - The process flow diagram is broken down into four main sections. The Blue section represents the preflash section, yellow color represents the atmospheric distillation section, the red is for the preheat trains, and green for the natural gas combustion and steam generation/distribution section.
2.1 Product and feedstock prices
ADU process unit is one of the first units in the overall refinery process, meaning that the outputs of
the ADU unit undergo further processing and blending, before they take their final form. For
example, kerosene product stream, from the ADU, undergoes several more processes before final
product, kerosene, is obtained. Prices of semi products (outputs of ADU unit) are hardly available,
that is why the prices of final products, together with some assumption, must be taken into
consideration for estimation of mentioned semi product’s prices. Prices of some final products
(kerosene, diesel, gasoline) are available on the EIA (5). Furthermore, very useful information is
5
obtained from the mentioned web page; the refinery process contributes from 10 to 15 % of the final
product price (depending on the product) (5). That means that the price of a semi product is
approximately 10 to 15 % smaller than the price of the final product. For example, it is assumed that
the price of the diesel product stream (from the ADU) is 15 % smaller than the price of the final diesel
product, and the kerosene product stream is 10 % smaller than the price of the final kerosene
product (5). Prices of Ago semi product and ADU residue were unavailable. Therefore, in order to
calculate needed prices, the price ratio between after mentioned prices of semi products and before
calculated semi products prices (kerosene, diesel, gasoline) is taken into account (6). Finally,
estimated prices of all semi products are represented at the Figure 2. Data used for obtaining graphs
on figure 2, is given in the appendix A1.
At the other hand the prices of feedstock, including prices of crude oils and natural gas, are
represented at the figure 3. The same price variation trends can be observed for both, products and
feedstock. It is assumed that the prices of raw material, including steam and cooling water, are
constant. The price of steam is 0,055 $/kg, and the price of cooling water is 0,006 $/MJ. Since, for
obtaining necessary temperature, natural gas is combusted, also the emission of CO2 must be taken
into consideration. It is assumed that the value of carbon tax is constant, and equals to 20 $/t of CO2
emitted (7).
Figure 2: Prices of ADU products during the investigated time period.
Figure 3: Prices of the feedstock during the investigated time period.
100
300
500
700
900
1100
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Pri
ce (
$/C
UM
)
Year
dieselkerosenegasolineAGOADU-residue
0
200
400
600
800
1000
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Pri
ce (
$/C
UM
)
Year
OPEC
EU Brent
Natural gas*1000
6
3 Model results
The results of the proposed crude distillation unit and its preheat train is presented in the following
subsections. Mass flows of the main products and feedstock’s for the base case are presented in
table 2. The consumption of natural gas is presented for the first year of operating. Since the fouling
has been taken into account, the amount of natural gas is increased by 5 % per year. This increase on
gas consumption is taken from reference (8). Simulation results for the part where feed composition
is varied are presented in table 3. These results are used for further calculation of economic
performance.
Table 2: Simulation results for base case
Crude feed combination Volumetric flow (m3/hr) Basrah
Iranhy
BrentBL
Feed
Heavy naphta
Light naphta
Kerosene
Diesel
Ago
ADU residue
Natural gas
0,333 0,333 0,333 979,0 200,5 79,8 259,7 275,6 109,9 247,7 27874,3
Table 3: Simulation results for different feed composition
Crude feed combinations Mass flow (kg/hr) Basrah
Iranhy
BrentBL
Feed
Heavy naphta
Light naphta
Kerosene
Diesel
Ago
ADU residue
Natural gas
0 1 0 833333 126937 58610 170355 206974 74200 179777 18870
0,8 0,2 0 833333 107325 93650 172115 162797 74200 223628 17300
0,6 0,4 0 833333 121642 76927 157313 157512 74200 238137 17210
0,4 0,6 0 833333 124477 76340 145820 150182 74200 253719 16900 0,2 0,8 0 833333 127680 57287 169853 210130 74200 176977 19050
1 0 0 833333 141650 37926 167291 227370 74200 155156 19860
0,8 0 0,2 833333 138582 41687 169710 200103 74200 180451 17700
0,6 0,2 0,2 833333 128854 58703 175005 171366 74200 206688 18030
0,4 0,4 0,2 833333 127946 62931 169382 154743 74200 227457 17470 0,2 0,6 0,2 833333 131932 59533 158192 145550 74200 244570 17700
0 0,8 0,2 833333 120714 55429 200540 208144 74200 150457 19444
0,6 0 0,4 833333 112398 68782 206493 176201 74199 178394 18450
0,4 0,2 0,4 833333 109229 75571 204536 152836 74200 203012 17666
0,2 0,4 0,4 833333 121763 63095 189858 143604 74200 220997 17420 0 0,6 0,4 833333 113638 57702 220172 204693 74200 137283 19650
0,4 0 0,6 833333 124297 48104 209679 187553 74199 159190 19099
0,2 0,2 0,6 833333 135256 39642 195714 186075 74199 168245 19444
0 0,4 0,6 833333 104298 62351 241342 199630 74199 125187 19744
0,2 0 0,8 833333 116899 49557 229578 183513 74199 146806 19200 0 0,2 0,8 833333 116085 50833 229786 181981 74200 148469 19165
0 0 1 833333 116271 41527 241178 183630 64200 146445 18900
7
The overall energy balance is represented using Sankey diagram, and can be seen at figure 4.
Presented diagram is for integrated process. It can be seen that flue gas heat is used for preheating
of feedstock (B11, B12) and for steam production (green part on figure 1). The difference between
integrated and non-integrated process is in fact usage of flue gases. In contrary to integrated process,
in non-integrated process, flue gases are used only for preheat of feedstock.
Figure 4- Sankey diagram of proposed CDU.
3.1 Economic performance
The method of net present values (NPV) is used in order to determine the economic efficiency and
validity of the overall process. The NPV is a commonly-used method for the calculation of economic
feasibility. The value of the capital cost is one of the variables that must be calculated in order to
determine NPV. Several parameters and indexes are used for the calculation of capital cost (9). The
main equation used for estimating capital (investment) costs is 0 0/ ( )feC n C S n S ,where C is the
cost of a process unit, n is the number of equally-sized units, C0 is the cost of a reference unit, S is the
capacity of a process unit, S0 is the capacity of a reference process unit, e is the cost scaling exponent
for different numbers of equally-sized units, and f is the cost- scaling factor (10). Costs of reference
units are taken from 2003, meaning that no further adjusting, using CEPCI indexes is necessary. Prices
of the atmospheric distillation unit and complete site utilities (tanks, sewage treatments, etc.) are
represented in the table 4.
In order to calculate annual profit, the prices of raw material and feedstock are necessary. Those
prices are mentioned in the previous chapter. Annual profit is calculated using following equation:
Ap = Pp - Pc - Png – Ot –Mt , where, Pp is the price of the total amount products, Pc is the price of the
total amount of crude oil used, Png is the price of the total amount of natural gas used, Ot are total
operating costs, and Mt is the maintenance cost. Operating costs are associated with usage of steam,
cooling water, etc. The value of the maintenance costs varies between five and six percent of the
8
capital costs (11) . In our work it was estimated that the maintenance cost would amount to 5.5% of
capital costs, resulting in 36,2 M$ per year.
Table 4: Calculation of capital costs.
Unit Scaling
parameter S S0 C0 (M$) n f e C (M$)
Atmospheric distillation unit
Bbl/day 197436 6000 6,48 33 0,67 0,9 150,5
Site facilities Bbl/day 197436 6000 21,8 33 0,67 0,9 506,7
Total cost 657,2
Finally, the last parameter needed for the calculation of NPV is the annual discount rate. The value of
annual discount rate that is taken into consideration is 10%. Furthermore, the 30% tax rate is also
taken into account. The calculated annual profits, for both processes, with and without heat
integration, are represented at the figure 5.
Figure 5: Calculated annual profits
Calculated annual profits are higher for integrated process for about 1M$ per year. That proves
efficiency of suggested heat integration. As it can be seen, annual profits are considerably smaller in
years from 2009 to 2013 (in 2011 even negative) compared to first five years. That is a result of
global economic crisis, and as it can be seen in the figures 2 and 3 the price of crude oils and products
strongly decreased when crisis had started. As mentioned before, prices of crude oil and products
are strongly connected (easily observed at figures 2 and 3), but on the other hand the price recovery
of the crude oil was faster, compared to the price recovery of the refinery products. That is why, in
the years after main impact of crisis, the annual profit strongly decreased (in 2011 even negative) in
-700,00
-500,00
-300,00
-100,00
100,00
300,00
500,00
700,00
900,00
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013Pro
fit
(M$
)
Year
with heat integration
without heat integration
9
comparison to the profit obtained in the years before global crisis (2004- 2008). It is also very
important that with decrease of profits, the heat integration becomes more obvious, because it
contributes higher percentage of profit. Calculated annual profits are used for calculation of NPV.
Results are represented at the figure 6.
Figure 6: Net present value
The NPV of integrated process is higher for about 4 M$ after the 10 years long period (2013). It is
obvious that NPV achieved approximately constant value after year 2008. That is because the annual
profit strongly decreased in 2009, resulting in negligible change in NPV value. Calculated internal rate
of return for integrated process is 76%, and 59% for non-integrated process. Even though calculated
NPV difference is only 4M$, this value has a strong influence on IRR, since IRR for integrated process
is 17% higher. This fact, once again, proves efficiency of performed heat integration.
3.2 Sensitivity analysis
In order to determine the effect of different values of independent variables, such are capital costs,
price of products and reactants, on net present value, the sensitivity analysis is performed. The value
of capital cost is varied ± 20% and ± 10 %. The variation influence is measured using calculation of
internal rate of return. Furthermore, the prices of refinery products and crude oil are varied in the
same manner. Results of the sensitivity analysis are represented on Figures 7, 8 and 9.
When the product price change was 10%, obtained NPV was negative, meaning that calculation of
IRR was not possible (it is smaller than proposed annual discount rate). Same occurs as the crude oil
price increased by 10%. That is why further change (up to 20%) is omitted. It can be seen that the
change in crude oil price and refinery product’s prices has a strong impact on IRR, meaning that
refinery process is very sensitive to products and feedstock price change.
The feed composition is another variable that has been changed in order to determine its influence
on economic performance.
-700
-500
-300
-100
100
300
500
700
900
1100
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
NP
V (
M$
)
YEAR
With heat integration
Without heat integration
10
Figure 7: Effect of crude oil price change on IRR Figure 8: Effect of change in products price on IRR
Figure 9: Effect of capital cost change on IRR
The feed composition is another variable that has been changed in order to determine its influence
on economic performance. Mass flows (of all products and feed stream) needed for calculations of
annual profits are already represented in Table 3. Calculated annual profits, for different feed
composition, are represented at the ternary diagram (Figure 10). Spots with highest annual profits
are represented with red color, while dark blue represents lowest annual profit. Highest annual profit
is obtained for feed composition – BrentBL:Iranhy:Basrah = 0:0,4:0,6. The lowest annual profit (even
negative) is obtained when pure BrentBL crude oil is used. Nonetheless, there are also some other
spots with negative revenues. That is why optimal feed composition is crucial for positive economic
performance of refinery process. This was reasonable to expect, due to the fact that composition of
crude oils varies strongly, and crudes from which more expensive products are produces, are more
economically favorable. In our case that are Iranhy and Basrah. Calculations of after mentioned
annual profits are given in the appendix A2.
It is well known that majority of crude oil fields are placed in countries with unstable political and
social situation. Because of that, the crude oil supply from these countries is unsustainable, meaning
that refineries from the other countries, which use crudes from mentioned areas, have to consider
20
40
60
80
100
120
140
160
-5% 0% 5% 10% 15% 20%
IRR
(%
)
Change in products price
with heat integration
without heat integration
30
50
70
90
110
130
150
-20% -15% -10% -5% 0% 5%
IRR
(%
)
Crude oil price change
with heat integration
without heat integration
40
50
60
70
80
90
100
-20% -10% 0% 10% 20%
IRR
(%
)
Capital (investment) cost change
with heat integration
without heat integration
11
alternative oil, when political or social situation break crude oil distribution. Alternative choice should
be considered very carefully, because, as it can be seen from figure 10, same feed compositions can
lead to the negative revenues.
Figure 10: Variation of annual profits (2009) due to the change in feed composition.
3.2.1 Summer – winter scenarios
Crude oil distillation would be also evaluated through two summer-winter scenarios. In first such
scenario, variation of diesel price was taken into consideration. It is well known that the price of
diesel increases during winters, because the usage of heating oil strongly increases in winter mounts
(12). Heating oil and diesel are produced is similar way, from same crude oil fraction. That is why the
increase of heating oil consumption is connected with increase in diesel price. It is reasonable to
expect that refinery should operate with feed composition that would give as much as possible diesel
in the winter. Two extreme prices (winter and summer one) for the year 2010 are taken into
consideration. The summer price of diesel is 812,8 $/m3 and winter price is 981,6 $/m3. It is assumed
that one half of annual production is sold for summer price, and another half for winter price. The
half year revenues are than compared, for different feed compositions. Results are graphically
represented on Figure 11, while detailed calculations can be found in the appendix. Winter half year
revenues are represented on the left hand side, while summer half year revenues are represented on
the right.
Same as in figure 10, red spots represents highest annual profits, while blue spots represent lowest
annual profit. It is easily observed that there are huge differences between mentioned half year
revenues, for all feed compositions. That once again shows how sensitive profit is on price change of
one or more products. It can be also seen that majority of summer annual profits are negative,
meaning that optimal feed composition is crucial for obtaining positive revenues. Highest winter
revenue is obtained when pure Basrah is used, while highest summer profit is obtained for following
feed composition : BrentBL : Iranhy : Basrah = 0 : 0,4 : 0,6. It is obvious that optimal feed composition
changes when the price of product changes. That means that flexibility of refinery process, in a way
that feed composition can be varied, is essential for obtaining highest annual profit.
12
Figure 11 - Variation of half year revenues due to the change in feed composition.
Second summer – winter scenario is associated with yearly temperature variation, and it is
considered for base case (base feed composition). It is well known that in continental climate areas,
air temperature varies by more than 40 °C during the year. For example, winter temperature is most
the time negative, while summer temperature is approximately 30 °C. Different ambient
temperature contribute to different feed temperature and heat losses, meaning that greater amount
of natural gas is needed during winters, for satisfying heat needs. It is calculated that consumption of
natural gas is 1000 kg/h greater, when feed temperature is -10 °C compared to the 20 °C feed
temperature. The difference can have strong effect on annual revenue, since it can increase process
annual cost by 1 to 1,5 M$.
4 Future work
The overall refinery process is very complex, and CDU only a first part of mentioned process. In order
to obtain better heat integration, the overall refinery process must be simulated more thoroughly.
For example, also VDU, cracking units, hydrogenation process unit, etc. have to be incorporated for
integration of mentioned units with CDU. Furthermore, the integration of some other process, in
which energy is released, with CDU can be considered. Since CDU is energy consuming, such
integration can have a very strong positive influence on economic efficiency. One of such process is
methanol production, and instead of using the released heat for electricity production, it can be used
within refinery process. Methanol process can be useful also from other point of view, since
methanol is used as additive in gasoline.
A mass integration of some streams (LIGHT) has not been looked at with great detail in this work,
since it would increase the complexity of the simulation by great degree. In the future work the
mentioned stream should be integrated, thus providing a feedstock for furnace or a new product
(LPG). During our work in ASPENPlus we had difficulties using optimization function. That is why
presented results are heuristically obtained. In order to increase overall efficiency, optimization of
overall process must be performed (using ASPEN or some other program).
13
5 Conclusion
The economical performance of the simulated refinery in this work was looked at from different
points of view. The investigation can be placed into three main topics:
a) The impact of the feedstock composition on the economical performance for the years 2009
and 2010 was studied. For this part we have chosen that the plant was integrated. The
results are shown graphically with the help of ternary contour diagrams.
b) The sensitivity analysis for the capital costs, product prices and feedstock price was also
carried out. The variation influence was measured using calculation of internal rate of return.
c) The impact of different variables (fouling, seasonal fluctuation in feed stream temperature,
seasonal fluctuation in product prices, heat integration) was examined for a base case.
This study concludes that the feedstock composition is of great importance, because on one hand we
can achieve a great profit if the composition is right (Basrah:Iranhy:BrentBL=0,6:0,4:0), on the other
hand (Basrah:Iranhy:BrentBL=0:0:1) we can also achieve big loss if we aren't careful when selecting
the crude oil.
The sensitivity analysis shows that, annual profit is very sensitive on feedstock or predicts price
change. For example, the 10% increase in crude oil price, would contribute to negative NPV after the
10 years long period.
As it was expected lower feedstock temperature contribute to a grater consumption of natural gas,
thus lowering the revenue. The same could be said for fouling which also raised the consumption of
NG.
To sum up, it is shown that crude oil distillation can be very profitable process when the right feed
composition is chosen. Furthermore, in order to increase economic performance an additional work
(overall process simulation, optimization, etc.) should be done.
6 Acknoledgements
We would like to thank Miloš Bogataj from the laboratory for process systems engineering and
sustainable development at the faculty for chemistry and chemical technology Maribor, Slovenia for
his mentorship and helpful insights in the preparation of this work.
7 Bibliography 1. Ocic, Ozren. Oil Refineries in the 21st Century. 2005.
2. Ai-Fu Chang, Kiran Pashikanti, Y. A. Liu. Refinery engineering - Integrated Process Modeling and
Optimization. s.l. : Wiley-Vch, 2012.
3. Exxonmobil. [Online] http://www.exxonmobil.com/crudeoil/about_crudes_kearl.aspx.
4. Indexmundi. [Online] [Cited: 03 22, 2014.] http://www.indexmundi.com/.
5. EIA. [Online] http://www.eia.gov/petroleum/supply/weekly/.
6. Optimization of crude distillation system using aspen plus: Effect of binary feed selection on grass-
root design. R.K. More, V.K. Bulasara, R. Uppaluri, V. R. Banjara. 2010, Chem. Eng. Res. Des., pp.
121-134.
7. Slovenije, Carinska uprava Republike. Emisija CO2. [Online] [Cited: 9 1, 2013.]
http://www.carina.gov.si/si/ostale_dajatve/okoljske_dajatve.
8. Ernst Worrell, Christina Galitsky. Energy Efficiency Improvement and Cost Saving Opportunities For
Petoleum Refineries. s.l. : Berkley National Laboratory, 2005.
9. John D. Jones, P. E. Feasibility Study for a Petroleum Refinery for The Jicarilla Apache Tribe.
Pheonix : s.n., 2004.
10. Comparison of coal IGCC with and withour CO2 capture and storage. Martelli E., Kreutz T. 14, s.l. :
Energy Procedia, 2009, Vol. 1.
11. Pintarič, Zorka Novak. Razvoj produktov in procesov. Maribor : FKKT MB, 2014.
12. Wikipedia. [Online] [Cited: 04 10, 2014.] http://en.wikipedia.org/wiki/Diesel_fuel.
13. Lasse R. Clausena, Niels Houbak b. Technoeconomic analysis of a methanol plant based on
gasification of biomass and electrolysis of water. 2010.
8 APPENDIX A Table A 1: Prices of various commodities.
Year Opec
($/m3)
BrentBL ($/m
3
Diesel ($/m
3)
Kerosene ($/m
3)
Gasoline ($/m
3)
AGO ($/m
3)
ADU residue ($/m
3)
Natural gas
($/m3)
2004 302,10 320,62 406,43 297,96 425,44 325,29 190,30 0,21
2005 424,36 457,30 539,36 426,98 582,99 445,75 260,77 0,32
2006 511,85 546,04 607,39 488,32 660,89 505,31 295,62 0,24
2007 578,89 607,05 647,81 537,14 714,38 546,21 319,54 0,25
2008 791,49 812,36 853,94 747,40 964,62 737,55 431,48 0,32
2009 511,68 517,38 553,95 427,78 592,49 453,02 265,02 0,14
2010 649,03 667,13 671,84 533,28 727,01 555,87 325,19 0,16
2011 900,51 932,36 862,25 734,96 962,52 735,94 430,54 0,14
2012 917,19 935,46 890,99 747,48 987,62 755,13 441,76 0,10
2013 887,19 909,73 880,66 727,70 969,70 741,43 433,75 0,13
Table A 2: Profit as a function of crude feed composition for the years 2009 and 2010, and for the winter/summer extreme. The numbers in the red color are for the biggest loss, and the green for the biggest profit.
Weight fraction Profit(M$/a)
Basrah
Iranhy
BrentBL
2009
Winter half revenue (2010)
Summer half revenue (2010)
0 1 0 205,2 87,0 -67,5
0,8 0,2 0 439,3 283,4 63,2
0,6 0,4 0 460,7 271,9 99,1
0,4 0,6 0 319,4 173,0 6,3
0,2 0,8 0 262,1 128,9 -29,8
1 0 0 443,0 287,6 64,1
0,8 0 0,2 346,0 226,1 -15,4
0,6 0,2 0,2 245,4 143,5 -68,9
0,4 0,4 0,2 239,2 124,0 -57,7
0,2 0,6 0,2 180,6 74,5 -89,1
0 0,8 0,2 92,1 9,0 -144,5
0,6 0 0,4 323,1 198,3 -23,2
0,4 0,2 0,4 285,5 155,6 -31,7
0,2 0,4 0,4 214,7 94,6 -67,4
0 0,6 0,4 87,9 3,0 -148,7
0,4 0 0,6 276,2 161,4 -56,6
0,2 0,2 0,6 154,8 69,2 -130,0
0 0,4 0,6 97,6 28,5 -168,5
0,2 0 0,8 229,2 123,7 -89,2
0 0,2 0,8 98,3 24,7 -168,6
0 0 1 -79,5 -98,5 -293,5