modeling and approved developed accuracy for oil refinery

International Journal of Chemistry; 2014[01] ISSN 2306-6415

31 www.engineerspress.com

Modeling and approved developed accuracy for oil refinery hydrogen

treatment unit by Petro-SIM software and set decision – making parameters

for decrease error of model

Mahbobeh Afkhami 1, Amir Samimi

2

1 Isfahan Oil Refinery Company, Research and Development Office, Isfahan, Iran

Email: [email protected]

2 Isfahan Oil Refinery Company, THN tinU , Isfahan, Iran

Email: [email protected]

Abstract: Modeling refinery unit has possibility for investigating every change in operation situation

and extra costs of improper changes. Also process stimulation provide possibility for recognize problems

in unit control system design and we should solve this problem. Other advantages of refinery units

modeling in use of them in increase units capacity in addition if we considered provide one optimization

system for every units of refinery, We should precious inspected them. In this projects complex of

industrial data gather for simulation and unit model by petro-SIM software.

Keywords: Refinery units modeling, Refinery units, Feed, Petro-SIM software

Introduction

Process of project implement

Modeling refinery units has possibility we can investigate incomes and their effects on production quality

before changes in operational situation and feed. Also process stimulation recognized failure in design of

unit control system and we should immediately remove this problem.

One of other advantages is increase unit capacities In addition if we considered provide optimization

system of units we should carefully inspected information for simulation.

We should give operational data as test-run as input to software for developed model, set calibration

parameter and simulate oil filter units, and oil refinery in this project after carefully investigating every

process units, begin test-runs gather process. In this phase, entrepreneur record data for every units and

unit’s calibration and simulation with certain internal time. We should consider recorded data set for

every process in 2 groups.



First section in needed reaction part and use for calibration program implement. And second group

include data for process simulation .In this project 4 run-test set provide for oil treatment units. And are

related to data timely output of Esfand 1389. Measurement tools error and not being tool by operator lead

to error in data.

On other hand test-run data set should determine system situation. So we should meet all and record

trustable data. And time difference of data record is of factors that threat data set accuracy. Since in some

cases it is not possible to measure process parameters and we considered parameter for estimation.

Detail of data in units stimulation and assumption present in stimulation section. In stimulation phase use

data set and investigated calibration and simulation. But there is doubt about confusion in test-runs. And

remove with refinery engineering exerts. And plan administered experts. It is worth nothing they meet

units control unit for evaluating data record way.

After recorded data analyse for this unit, proper parameters selected for processes stimulation. In this

report, calibration and oil hydrogen treatment unit gathered by 4 test-run. In this section we present

calibration after introduce HTR-SIM. Finally they present report about data gather related to unit and unit

stimulation.

Calibration and oil hydrogen treatment unit

HTR-SIM Majols produce by KBC Company for stimulating hydrogen treatment process. NHTR-SIM

model design for oil feed while DHTR-SIM for dizel and crozin feeds.

We can use this model in 2 modes of common desulfurization and process with low sulfur. VGOHTR-

SIM model is designed for units with gasoline input feed such as vacuum tower, Coker heavy gas, FCC

unit heavy oil and other similar flows. HTR-SIM model show composite of sintiki stimulation of reactor

and separating productions we can access to this model by stand-alone or petro-SIM stimulation.

HTR-SIM models has below important specifications

Stimulation of hydrogen treatment reactor that include cooler flows, reactor low sudden vapor container.

And return hydrogen flow ring. Present sintik for all important reactions that include HDS, HDN, HAD,

Alfins and Cracking saturation.

Energy balance for compute catalysor bed temperature increase and cooler flows Catalisor inactive

modeling base on catalisor temperature hydrogen partial pressure and input feed quality. Considering

different sulfur compound and separate reaction trends proper and efficient tools for develop LP factors.

REF-SIM internal optimization by receive feed and products price catalyst price and process operation

boundary. We can obtain below result by HTR-SIM tool.

We should consider what temperature for decrease product sulfur decrease and after what time this

catalisor is inactive?



How we investigate correctly catalisor inactivation and determine process shut down time?

How we can produce set of output factors for feed and different operation situation?

Utility and shut down for feed certain prices in what situation obtain?

Hydrogen treatment unit calibration by HTR-SIM Majol

We should at first gathered data for process calibration in test-run forms for modeling hydrogen

treatment, 4 set of test-run show oil hydrogen treatment unit performance. Since model parameter set is in

calibration phase, model accuracy depends on input data precious. At first we should investigate data

present in every test-run. But main input data in Majol NHTR-SIM is catalysor life, inactive speed and

light hydrocarbons produce output.

In calculate light hydrocarbons produce output like Metan to botzu we should pay attention to input

compensate gas and it should minus mass Debi. And software calculate light hydrocarbons output and

input by mass balance program (MBP).

Evaluate recorded data according for hydrogen treatment unit

This model accuracy is significantly depend on oil hydrogen treatment unit and stimulation data. Experts

that are plan administer meet control room for evaluate gathered data accuracy. In this case sample of

recorded data relate to operation variables gathered and studied change trend with pass time. In this

section we review sample of recorded operation data for hydrogen treatment unit.

1- Input feed Debi to this unit is fixed and recorded value shows there is no change in feed Debi by

passing time.

2- Output gas Debi of high-stress separator is 1-4 test-run are 291-569-436-262. Figure 1-2 show

Debi record paper of this trend that drawing line shows Debi value. And place of this recorded

value is that its accuracy is low during data reading and recording.

3- Recorded data sample for return gas of reactor show this flow is relatively fixed. Value in test-

runs is very close together and confirms this issue.

4- Also compensate hydrogen gas Debi has fixed value and data record paper has small oscillation

for Debi. And we can say this reported value accuracy is acceptable for this data.

5- Return flow Debi of striper tower top is in figure 2-2 top curve in related to this flow.

Less recorded value in this paper is 24/5 mm/h and more value is 33/8 mm. This value is 28/8, 29, 30/6

and 30 mm.

According to this paper, output gas Debi of striper tower top is 635/9, 777/2. Change trend is such its

value has oscillation in one little output but there are some peaks that are out of scope.



Result of hydrogen treatment unit stimulation

Calibration program implement for every test-runs after completing data in calibration input and result

transmit to petro-SIM space. And they can use model for reactor in oil treatment process stimulation. In

figure 1-2 and 2-2 shows plan of calibration input papers and calibration result for oil treatment unit.

We can transmit calibration coefficient to stimulation file by menu in NHTR-SIM Majol. And oil

treatment process stimulate by determining signtic parameters and other model parameters figure 3-2

shows trend of this process in stimulation file.

Base on recorded information, Etanol, propan and Botan is Positive base on recorded data and show

hydrogen treatment process consumed in this material. But major reactions don’t accrue in alpines in

desulfurization, denitronization and saturation.

So we except produce light hydrocarbons components and we obtain production output that in positive. In

this case gas and liquid flow Debi measured carelessly and is error origin in calculated process stability

and sustainability is increase units capacity since. Increase units capacity oscillate change trend in some

process sustainability. So this phenomenon affect on recorded data. On the other hand we should carefully

investigate data with respect to reaction synthesis modeling and catalyst activity.

In oil treatment unit of Esfahan refinery recycled catalyst activity by periodic replacing some of

consumed catalysts. And we have not significant change in input feed temperature to reactor. So

quantities like begin temperature and cycle end or inactivation speed is not proper scale for calculate

inactivation and synthetic calculations. We expert NHTR-SIM Majol prediction of catalyst behavior and

hydrogen treatment process is different relative to experiment results.

Stimulation by this test-run shows result of desulfurization. Processes have not high reliability. So it

seems NHTR-SIM Majol of petro-SIM software for operation situation stimulation and prediction is not

proper and obtains to precession data depend on use of other tools consistent to present situation.

Calibration and stimulation result

We provide 4 test-run set provided during shanhavior to Esfahan in this project and for every oil

hydrogen treatment unit. We should gathered data for showing system situation in one certain time. This

data use in data set stimulation and every unit calibrated and stimulated. We hold meeting by experts and

plan administer and they remove confusion related to data so project supervisor request to hold meeting

for petro-SIM software training. They use for calibration NHTR-SIM Majol oil hydrogen unit. Analyzing

data shows some quantity like output gas and liquid flows Debi carelessly measured and lead to error in

light hydrocarbons output stimulation hydrogen treatment unit show data has not high reliability for

modeling sulfurization process.

In addition catalyst activity recycles method in present unit and data in NHTR-SIM affect result of

NHTR-SIM Majol.



Table 1: Ran tests for modules prepared NHTR –SIM

1- NHTR Test

Run

2- Unit 3- 1 4- 2 5- 3 6- 4 7- Fresh Feed 8- Rate 9- bbl / day 22500 22500 22500 22500 10- Density 11- API 0.7451 0.7445 0.7439 0.745 12- Sulfur 13- ppm 14- 170-

200

15- 170-

200

16- 100 17- 100 18- Total

Nitrogen

19- ppm 20- 2 21- 2 22- 2 23- 2 24- Bromine

Number

25- 26- 27- 28- 29- 30- Feed Distillation (D-86) 31- Vol % 32- Temp. 33- 0% 34- °C 22500 22500 22500 22500 35- 10% 36- °C 0.7451 0.7445 0.7439 0.745 37- 30% 38- °C 109 113 108 110 39- 50% 40- °C 117 121 117 116 41- 70% 42- °C 127 131 127 125 43- 90% 44- °C 141 144 140 137 45- 99% 46- °C 161 160 164 157 47- Base

Temperature

48- °C 38 289.5 290 289 49- Combined

Fresh Feed

50- °C 62 335.1 336 335.5 51- HDS Reactor 52- Inlet T 53- °C 335 335.1 336 335.5 54- Outlet T 55- °C 335.3 335.7 336 335.7 56- V-201 P 57- bar 28 29.1 29.1 29.4 58- Catalyst

Weight

59- kg 8945 8945 8945 8945 60- Catalyst

Density

61- g/cm3 0.71 0.71 0.71 0.71

62- Age 63- m3/kg 2856 2964.2 2975.5 3001.8

64- Average

Deactivation

Rate

65- °C/(m3/k

g)

66- 0 67- 0 68- 0 69- 0 70- Gas System 71- H2 Make Up

Flow Rate

72- kNm3/d 25.54 68.4 34.08 26.6

73- H2 Make Up Analysis 74- H2 75- mol % 73.9 71 72.9 73.3 76- H2S 77- mol % 0 0 0 0 78- CH4 79- mol % 11.5 12.6 11.9 11.6 80- C2H6 81- mol % 7.4 9 8.2 8 82- C3H8 83- mol % 4.8 4.6 4.6 4.7 84- I-Butane 85- mol % 1.2 1.2 1.2 1.2 86- N-Butane 87- mol % 0.7 1 0.8 0.7 88- C5+ 89- mol % 0.5 0.6 0.4 0.5 90- High Pressure Separator 91- HPS T 92- °C 39 39 39 40 93- HPS P 94- bar 23 22 22 22.1 95- HPS Vent

Gas Flow

Rate

96- kNm3/d 6.984 6.246 6.412 6.29

97- HPS Vent Gas Analysis 98- H2 99- mol % 92.2 92.3 90.9 92.9 100- H2

S

101- mol % 0.04 0.04 0.04 0.04 102- C

H4

103- mol % 6.7 6.9 7.9 5.9 104- C2

H6

105- mol % 0.9 0.7 1 0.7 106- C3

H8

107- mol % 0.1 0.1 0.2 0.5 108- I-

Butane

109- mol % 0.1 0 0 0 110- N-

Butane

111- mol % 0 0 0 0 112- C5

+

113- mol % 0 0 0 0 114- Yield 115- Ch

emical H2

Consumpt

ion

116- nm3/m

3 117- 118- 119- 120-

121- M

ethane

122- Wt %

of Fresh feed

0.0331 -0.0355 0.0291 0.0077 123- Et

hane

124- Wt %

of Fresh feed

0.0108 -0.1158 -0.0410 0.0130



125- Pr

opane

126- Wt %

of Fresh feed

-0.0089 -0.0809 -0.0256 0.0158 127- I-

Butane

128- Wt %

of Fresh feed

0.0035 -0.0126 0.0076 0.0073 129- N-

Butane

130- Wt %

of Fresh feed

0.0029 -0.0093 0.0214 0.0240 131- Na

phtha

132- Wt %

of Fresh feed

133- 134- 135- 136- 137- Product Properties 138- De

nsity

139- g/cm3 0.784 0.7446 0.7447 0.7445

140- Su

lfur

141- Wt % 0.3 0.2 0.18 0.2 142- To

tal

Nitrogen

143- Wt % Nil Nil Nil Nil 144- Br

omine

Number

145- 146- Product Distillation (D-86) 147- Vo

l %

148- Temp. 149- 150- 151- 152- 153- IB

P

154- °C 88 89 90 90 155- 10

%

156- °C 102 101 101 103 157- 30

%

158- °C 108 110 109 109 159- 50

%

160- °C 116 118 117 117 161- 70

%

162- °C 125 127 129 126 163- 90

%

164- °C 139 141 139 138 165- FB

P

166- °C 160 159 163 161 167- Reactor 168- S

OR

WABT

169- °C 335.1 335 335 335 170- E

OR

WABT

171- °C 335.1 335 335 335 172- H2

Treat gas

to bed 1

173- kNm3/d

Figure 1 - record outflow of high pressure separator



Figure 2 - A view of the module calibration sheet input

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modeling and approved developed accuracy for oil refinery

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