Research Papers: Petroleum Engineering

Introduction of Novel Process for Sweetening of Sour Crude Oil: Optimization of Process

[+] Author and Article Information
Farshad Farahbod

Department of Chemical Engineering,
Firoozabad branch,
Islamic Azad University,
Firoozabad, Iran
e-mail: mf_fche@iauf.ac.ir

Sara Farahmand

School of Chemical and Petroleum Engineering,
Molasadra Avenue Engineering Building,
Shiraz, Iran
e-mail: sfarahmand2005@gmail.com

1Corresponding author.

Manuscript received December 4, 2015; final manuscript received September 27, 2016; published online November 10, 2016. Assoc. Editor: Daoyong (Tony) Yang.

J. Energy Resour. Technol 139(2), 022907 (Nov 10, 2016) (9 pages) Paper No: JERT-15-1458; doi: 10.1115/1.4034905 History: Received December 04, 2015; Revised September 27, 2016

The subject of this experimental report is the application of nanoparticles in petroleum refining. Sulfur removal from petroleum using carbon nanotubes is considered in this study. The properties related to the process characterization are measured experimentally and reported. The effect of low range temperature and pressure, initial concentration, interfacial velocity, the ratio of height to diameter of the bed and particle diameter on the outlet sulfur is investigated. Design of experiment is performed to show which of the controllable parameters affects the sulfur removal process and a predictive model is developed. Optimization of the model is performed with the aim that the outlet sulfur content less than 0.6 ppm is achievable. Also, the increase in the amount of pollutant higher than 50 ppm sulfur and increase in the amount of superficial velocity higher than 0.4 m/s lead the adsorption process to the improper results. Finally, cost estimation due to pressure and temperature is presented and the optimum conditions of 1.7 atm pressure and 35 °C temperature with the height to diameter ratio of three and nano carbon tubes of 50 nm for packed bed are proposed.

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Fig. 4

Externally studentized residuals versus run number

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Fig. 3

Predicted values versus actual amounts of logit (C/C0)

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Fig. 2

Normal plot of residuals

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Fig. 1

(a) Schematic of experimental equipments and (b) a schematic of layered packed bed

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Fig. 11

The amount of pressure drop versus H/D

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Fig. 12

Perturbation plot in numerical optimization

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Fig. 13

Contour plot in numerical optimization

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Fig. 9

The effect of input concentration on C/C0 values

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Fig. 5

The effect of temperature and pressure on C/C0

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Fig. 10

The effect of superficial velocity on the amount of C/C0

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Fig. 6

The effect of particle diameter on the value of C/C0

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Fig. 7

The effect of cross-section area on the amount of C/C0

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Fig. 8

The effect of ratio of H/D on values of C/C0

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Fig. 14

Amount of design cost versus pressure

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Fig. 15

Energy cost versus temperature




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