J. Chem. Pet. Eng. University of Tehran Journal of Chemical and Petroleum Engineering 2423-673X University of Tehran 8 10.22059/jchpe.2014.7559 Original Paper A New Analytical Model for Developing Fractional Flow Curve Using Production Data A New Analytical Model for Developing Fractional Flow Curve Using Production Data Adesina Fadairo Department of Petroleum Engineering, Covenant University Otta, Ogun State, Nigeria Abiodun Adeyemi Department of Petroleum Engineering, Covenant University Otta, Ogun State, Nigeria Olugbenga Falode University of Ibadan, Nigeria 01 12 2014 48 2 81 90 17 09 2013 24 09 2014 Copyright © 2014, University of Tehran. 2014 https://jchpe.ut.ac.ir/article_7559.html

The immiscible displacement of oil by water through a porous and permeable reservoir rock can be described by the use of a fractional flow curves (fw versus Sw). Water flooding project parameters can be obtained from the fractional flow curve. However, developing a representative fractional flow curve for a specific reservoir can be quite challenging when fluid and special core analysis data is limited or compromised.  Hence, a mathematical model for dependence of fw on Swis developed by solving material balance algorithm using production data. The results of the model were compared with forecasts from the conventional Bucklett Leverett fractional flow equation and Corey’s correlation and were found to be favorable with less time and effort.

 Waterflooding Fractional flow curve Secondary recovery buckley leverret [1]Craig, Jr., F.F. (1993). "The reservoir engineering aspects of waterflooding."Vol. 3. 134 pp.; SPE Monograph Series ISBN:978-0-89520-202-4 Society of Petroleum Engineers. [2] Willhite, G.P. (1986). Waterflooding, Vol. 3. Richardson, Texas: Textbook Series, SPE. [3] Sitorus, J. (2006)."Developing a fractional flow curve from historic production to predict performance of new horizontal wells." Bekasap Field, Indonesia, SPE 101144. [4] Tarek Ahmed. (2010). Reservoir engineering Handbook Gulf Professional Publishing; 4th edition. [5] Eric P. Robertson (2007)."Low- salinity waterflooding to improve oil recovery- Historic oil residence." /Idaho National Laboratory SPE 109965. [6] El–Khatib, N.A. (1999). "Waterflooding performance of communicating stratified reservoirs with log-normal permeability distribution."SPEREE (Dec. 1999), Vol. 2, pp. 542-549. [7] Pande, K.K., Ramey, H. J. Jr., Brigham, W.E. and Orr, F.M. Jr. (1987). Frontal Advance Theory for Flow in Heterogeneous Porous Media, paper SPE 16344 presented at SPE California Regional Meeting. [8] El–Khatib, N.A. (1985). "The effect of crossflow on waterflooding of stratified reservoirs." Soc. Pet. Eng. J. (April, 1985), pp. 291–302. [9] Ayodele, A.O. (2011). "A new analytical model developed for designing fractional flow curve form production history."B.Sc final year project. Covenant University, (June, 2011). [10] Lake, L.: Enhanced Oil Recovery, Prentice Hall. Englewood Cliffs, NJ (1989). [11] Dake, L.P.: Fundamentals of Reservoir Engineering, Elsevier Scientific Publishing Co., Amsterdam (1978). 352. [12] Dholkawala, Z.F., Sarma, H.K. and Kam, S.I. (2006). "Application of fractional flow theory to foams in porous media."Accepted in J. of Pet. Sci. & Eng. [13] E. Terry R. and Brandon Rogers, J.( 2014).Applied Petroleum Reservoir Engineering Prentice Hall.
J. Chem. Pet. Eng. University of Tehran Journal of Chemical and Petroleum Engineering 2423-673X University of Tehran 8 10.22059/jchpe.2014.63712 Original Paper Carbon Dioxide Capture by Modified UVM-7 Adsorbent Carbon Dioxide Capture by Modified UVM-7 Adsorbent Babaie Fatemeh Faculty of Caspian, College of Engineering, University of Tehran, Guilan, Iran Mousavi Seyed Hamed Faculty of Caspian, College of Engineering, University of Tehran, Guilan, Iran Alizadeh Ali mohammad Gas Research Division, Research Institute of Petroleum Industry (RIPI), Tehran, Iran Hazrati Nastaran Faculty of chemistry, Amirkabir University of Technology, Tehran, Iran 01 12 2014 48 2 91 102 08 01 2014 22 07 2014 Copyright © 2014, University of Tehran. 2014 https://jchpe.ut.ac.ir/article_63712.html

In this study, bimodal meso-porous silica (UVM-7) synthesized and fabricated amino silane modified supports were characterized by powder X-ray diffraction (XRD), N2 adsorption/desorption, transmission electron microscope (TEM), elemental analysis and titration. Capacity of CO2 capture on modified bimodal pore structure silica at 70°C was calculated using breakthrough curves; and it was found that the modified UVM-7 captured more CO2 than unmodified UVM-7 and pore structure of UVM-7 make it suitable for loading large molecules such as tri-amino silanes. The adsorbents modified with tri-amino silane showed the largest capacity. Dynamic and kinetic of adsorption were investigated by mathematical models in order to prediction of adsorption behavior. Yoon Nelson model was successfully employed to describe the adsorption breakthrough curves of CO2 and Avrami model applied as a kinetic model and was in good agreement with experimental data in comparison with two other kinetic models including Lagergen’s pseudo-first and pseudo-second order models.

 CO2 N2 Adsorption/ Desorption Isotherm Breakthrough Carbon capture Flue gas [1] Song, C. (2006). "Global challenges and strategies for control, conversion and utilization of co2 for sustainable development involving energy, catalysis, adsorption and chemical processing." Catal. Today, Vol. 115, No. 1–4, pp. 2-32. [2] Aaron, D. and Tsouris, C. (2005). "Separation of co2 from flue gas: A review." Sep. Sci. Technol., Vol. 40, No. 1-3, pp. 321-348. [3] Choi, S., Drese, J.H. and Jones, C.W. (2009). "Adsorbent materials for carbon dioxide capture from large anthropogenic point sources." Chem Sus Chem, Vol. 2, No. 9, pp. 796-854. [4] Pachauri, R.K and Reisinger, A. (eds.) (2007).Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland. [5] Steeneveldt, R., Berger, B. and Torp, T.A. (2006). "Co2 capture and storage: Closing the knowing-doing gap." Chem. Eng. Res. Des., Vol. 84, No. 9, pp. 739-763. [6] Chu, S. (2009). "Carbon capture and sequestration." Science, Vol. 325, No. 5948, pp. 1599-1599. [7] Gough, C. (2008). "State of the art in carbon dioxide capture and storage in the UK: An experts’ review." Int. J. Greenhouse Gas Control, Vol. 2, No. 1, pp. 155-168. [8] Figueroa, J.D., Fout, T., Plasynski, S., McIlvried, H. and Srivastava, R.D. (2008). "Advances in co2 capture technology—the u.S. Department of energy's carbon sequestration program." Int. J. Greenhouse Gas Control, Vol. 2, No. 1, pp. 9-20. [9] Goeppert, A., Czaun, M., Surya Prakash, G.K. and Olah, G.A. (2012). "Air as the renewable carbon source of the future: An overview of co2 capture from the atmosphere." Energy Environ. Sci., Vol. 5, No. 7, pp. 7833-7853. [10] Pennline, H.W., Luebke, D.R., Jones, K.L., Myers, C.R., Morsi, B.I., Heintz, Y.J. and Ilconich, J.B. (2008). "Progress in carbon dioxide capture and separation research for gasification-based power generation point sources." Fuel Process. Technol., Vol. 89, No. 9, pp. 897-907. [11] Sjostrom, S. and Krutka, H. (2010). "Evaluation of solid sorbents as a retrofit technology for co2 capture." Fuel, Vol. 89, No. 6, pp. 1298-1306. [12] Ebner, A.D. and Ritter, J.A. (2009). "State-of-the-art adsorption and membrane separation processes for carbon dioxide production from carbon dioxide emitting industries." Sep. Sci. Technol., Vol. 44, No. 6, pp. 1273-1421. [13] Zhao, Y., Ding, H. and Zhong, Q. (2012). "Preparation and characterization of aminated graphite oxide for co2 capture." Appl. Surf. Sci., Vol. 258, No. 10, pp. 4301-4307. [14] Dasgupta, S., Nanoti, A., Gupta, P., Jena, D., Goswami, A.N. and Garg, M.O. (2009). "Carbon dioxide removal with mesoporous adsorbents in a single column pressure swing adsorber." Sep. Sci. Technol., Vol. 44, No. 16, pp. 3973-3983. [15] Huerta, L., Guillem, C., Latorre, J., Beltrán, A., Martínez-Máñez, R., Marcos, M. D., Beltrán, D., Amorós, P. (2006). "Bases for the synthesis of nanoparticulate silica with bimodal hierarchical porosity." Solid State Sci., Vol. 8, No.8, pp. 940–951. [16] Sayari, A., Belmabkhout, Y. and Serna-Guerrero, R. (2011). "Flue gas treatment via CO2 adsorption." Chem. Eng. J., Vol. 171, No. 3, pp. 760-774. [17] Serna-Guerrero, R. andSayari, A. (2010). "Modeling adsorption of CO2 on amine-functionalized mesoporous silica. 2: Kinetics and breakthrough curves." Chem. Eng. J., Vol. 161, No.1-2, pp.182-190. [18] Sing, K. S. W. (1985). "Reporting physisorption data for gas/solid systems with special reference to the determination of surface area and porosity (Recommendations 1984)." Pure Appl. Chem., Vol. 57, No.4, pp. 603-619. [19] Hu, Q., Li, J. J., Hao, Z. P., Li, L. D. and Qiao, S. Z. (2009). "Dynamic adsorption of volatile organic compounds on organofunctionalized SBA-15 materials." Chem. Eng. J., Vol. 149, No.1-3, pp. 281-288. 102 Journal of Chemical and Petroleum Engineering, Vol. 48, No.2, Dec. 2014. [20] Samanta, A., Zhao A., Shimizu, G. K. H., Sarkar, P., and Gupta, R. (2011). "Post-Combustion CO2 Capture Using Solid Sorbents: A Review." Ind. Eng. Chem. Res., Vol. 51, No.4, pp. 1438-1463. [21] Azizian, S. (2004). "Kinetic models of sorption: a theoretical analysis." J. Colloid InterfaceSci., Vol. 276, No.1, pp. 47–52.
J. Chem. Pet. Eng. University of Tehran Journal of Chemical and Petroleum Engineering 2423-673X University of Tehran 8 10.22059/jchpe.2014.7561 Original Paper CFD Simulation of UV Disinfection Reactor for Applesauce with a Low UV Absorption Coefficient CFD Simulation of UV Disinfection Reactor for Applesauce with a Low UV Absorption Coefficient Hashemabadi Seyed Hassan Computational Fluid Dynamics (CFD) Research Laboratory, School of Chemical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran Ghaderzadeh Farkhondeh Computational Fluid Dynamics (CFD) Research Laboratory, School of Chemical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran Taghipour Fariborz Department of Chemical and Biological Engineering, University of British Columbia, Vancouver, BC Canada 01 12 2014 48 2 103 116 16 12 2013 08 09 2014 Copyright © 2014, University of Tehran. 2014 https://jchpe.ut.ac.ir/article_7561.html

In this study, a Computational Fluid Dynamics (CFD) model was developed to evaluate ultraviolet disinfection applesauce reactor. To simulate UV reactors, three sets of equations, including hydrodynamics, radiation and species mass conservation were solved simultaneously. The Realizable k-e turbulence model and the discrete ordinate method were used to find the UV radiation profile through the reactor. Using the Chick-Watson kinetic model and the Eulerian framework, inactivation of applesauce microorganisms was simulated in the UV reactor. Simulation results for water disinfection in the UV reactor were evaluated by the reported experimental data. Simulation was extended for non-Newtonian fluid such as applesauce. Results show that the UV reactor is less effective in eliminating microorganisms from applesauce than from water because applesauce has a higher UV absorption rate. In order to achieve higher disinfection of the UV reactor for non-Newtonian fluids with high absorption, this study examined different parameters and makes suggestions for appropriate reactor design. Different designs for disinfection reactor were studied, due to higher UV absorption coefficient of applesauce, CFD simulations show that the inactivation of microorganisms in applesauce is less than water, consequently thin film or small radius reactors are appropriate design.

 Computational fluid dynamics (CFD) Disinfection Ultraviolet (UV) reactor Non-Newtonian fluid Reactor engineering [1] Unluturk, S. K., Arastoopour, H. andKoutchma, T. (2004). "Modeling of UV dose distribution in a thin-film UV reactor for processing of apple cider."J. Food Eng., Vol. 65, pp. 125–136. [2] Adhikari, C., Koutchma, T. and Beecham-Bowden, T. (2005). "Evaluation of HHEVC (4, 40, 400-tris-di-Bhydroxyethyl amino triphenyl acetonitrile) dye as a chemical actinometer in model buffers for UV treatment of apple juice and cider."LWT-Food Sci. Technol., Vol.38, No. 7, pp. 717-725. [3] Koutchma, T. and Parisi, B. (2004). "Biodosimetry of Escherichia coli UV inactivation in model juices with regard to dose distribution in annular UV reactors."J. Food Sci., Vol. 69, No. 1, FEP14-FEP22. [4] Koutchma, T., Parisi, B. andUnluturk, S.K. (2006). "Evaluation of UV dose in flow-through reactors for fresh apple juice and cider."Chem. Eng. Commun., Vol. 193, pp. 715–728. [5] Keyser, M., Műller, I.A., Cilliers, F.P., Nel, W. and Gouws, P.A. (2008). “Ultraviolet radiation as a nonthermal treatment for the inactivation of microorganisms in fruit juice."Innovative Food Sci. Emerging Technol., Vol. 9, pp. 348–354. [6] Koutchma, T., Parisi, B. andPatazca, E. (2007). "Validation of UV coiled tube reactor for fresh fruit juices."J. Environ. Eng., Vol. 6, pp. 319–328. [7] Oteiza, J.M., Giannuzzi, L. and Zaritzky, N. (2010). "Ultraviolet treatment of orange juice to inactivate E. coli O157:H7 as Affected by Native Microflora." Food Bioprocess Technol., Vol.3, No. 4, pp. 603-614. [8] Unluturk, S., Atılgan, M.R., Handan Baysal, A. and Tarı, C. (2008). “Use of UV-C radiation as a non-thermal process for liquid egg products (LEP)."J. Food Eng., Vol. 85, pp. 561-568. [9] Ducoste, J.J., Liu, D. and Linden, K. (2005). "Alternative approaches to modeling fluence distribution and microbial inactivation in Ultraviolet Reactors: Lagrangian versus Eulerian."Environ. Eng., Vol.131, No. 10, pp.1393–1403. [10] Duran, J.E., Taghipour, F. andMohseni, M. (2009). "CFD modeling of mass transfer in annular reactors."Int. J. Heat Mass Transfer, Vol. 52, pp. 5390-5401. [11] Elyasi, S. andTaghipour, F. (2006). "Simulation of UV photoreactor for water disinfection in Eulerian framework."Chem. Eng. Sci., Vol. 61, pp. 4741– 4749. [12] Wols, B.A., Shao, L., Uijttewaal, W.S.J., Hofman, J.A.M.H., Rietveld, L.C. andVan Dijk, J.C. (2010). "Evaluation of experimental techniques to validate numerical computations of the hydraulics inside a UV bench-scale reactor."Chem. Eng. Sci., Vol. 65, pp. 4491-4502. [13] Liu, D., Wu, C., Linden, K. and Ducoste, J. (2007). "Numerical simulation of UV disinfection reactors: Evaluation of alternative turbulence models." Appl. Math. Model., Vol. 31, pp. 1753-1769. [14] Sozzi, D. andTaghipour, F. (2006). "UV reactor performance modeling by Eulerian and Lagrangian methods."Environ. Sci. Technol., Vol. 40, No. 5, pp. 1609-1615. [15] Chiu, K., Lyn, D.A., Savoye, P. and Blatchley, E.R. (1999). 'Integrated UV disinfection model based on particle tracking."Environ. Eng., Vol. 125, No. 1, pp. 7-16. [16] Duran, J.E., Taghipour, F. and Mohseni, M. (2010). "Irradiance modeling in annular photoreactors using the finite-volume method."J. Photochem. Photobiol. A: Chemistry., Vol. 215, pp. 81-91. [17] Stamnes, K., Tsay, S.C., Wiscombe, W. andJayaweera, K. (1988). "Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media." Appl. Optics, 27(12), pp. 2502-2509. [18] Liou, B.T. and Wu, C.Y. (1996). "Radiative transfer in a multi-layer medium with Fresnel interfaces."Heat Mass Transfer, Vol. 32, No. (1-2), pp. 103-107. [19] Patankar, S.V. (1980). Numerical Heat Transfer and Fluid Flow, Taylor and Francis. [20] Versteeg, H. andMalalasekra, W. (2007). An Introduction to Computational Fluid Dynamics: The Finite Volume Method, 2nd Edition, Pearson Prentice Hall. [21] Steff, J.F. (1996). Rheological Methods in Food Process Engineering, 2nd ed., Freeman Press, East Lansing, USA. [22] Sozzi, A. andTaghipour, F. (2006). "Computational and experimental study of annular photo-reactor hydrodynamics."Int. J. Heat Fluid Flow, Vol. 27, pp. 1043–1053. [23] Liu, D., Ducoste, J. and Linden, K. (2004). "Evaluation of alternative fluence rate distribution models."J. Water Supply, Res. Technol., Vol. 56, pp. 391-408. [24] Bird, R.B., Armstrong, R.C. and Hassager, O. (1987). Dynamics of polymeric liquids: Vol. 1 Fluid Mechanics., 2nd ed., Wiley, New York.
J. Chem. Pet. Eng. University of Tehran Journal of Chemical and Petroleum Engineering 2423-673X University of Tehran 8 10.22059/jchpe.2014.7562 Original Paper Biodegradation Modeling of Nitrophenolic Pollutant in a Slurry Bubble Reactor Biodegradation Modeling of Nitrophenolic Pollutant in a Slurry Bubble Reactor Salehi Zeinab School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran Fatemi Shohreh School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran Vahabzadeh Farzaneh Chemical Engineering Department, Amirkabir University of Technology, Tehran, Iran 01 12 2014 48 2 117 124 04 03 2014 09 09 2014 Copyright © 2014, University of Tehran. 2014 https://jchpe.ut.ac.ir/article_7562.html

Biodegradation kinetics of 4-nitrophenol (PNP) in aqueous solution by a gram negative soil bacterium, Ralstoniaeutropha was firstly studied in a small scale batch reactor. The degradation of PNP was evaluated at initial PNP concentrations ranging from 3 mg/L to 14 mg/L. The rate of PNP consumption by the bacterium culture was modeled using Monod and Contois kinetics in batch condition. PNP degradation by adapted R. eutropha was well fitted to the Monod equation for the pollutant with initial concentration of 3-8 mg/L, whereas for PNP with initial concentration of 14 mg/L the experimental data were better fitted to the Contois kinetic model. The process of degradation of PNP was scaled up in a slurry bubble reactor with 250 ml working volume in presence of 0.75 L/min air flow rate. The derived kinetic model was validated by comparison the outlet time dependent experimental data of PNP concentration with the model in the slurry bioreactor and the results showed good agreement between experiments and the model.

 biodegradation p-nitrophenol Ralstoniaeutropha Kinetic modeling Slurry bubble reactor [1] Chaudhari, R. V. and Ramachandran, P. A. (1983). "Three-phase catalytic reactors." AlChE J., Vol. 26, pp.177-201. [2] Tomei, M.C., Annesini, M.C. and Bussoletti, S. (2004). "4-Nitrophenol biodegradation in a sequencing batch reactor: kinetic study and effect of filling time." Water Res., Vol. 38, pp.375–384. [3] Tomei, M.C. and Annesini, M.C. (2005). "4-Nitrophenol biodegradation in a sequencing batch reactor operating with aerobic–anoxic cycles." Environ Sci Technol., Vol. 39, pp. 5059–5065. [4] Yi, S., Zhuang W.Q., Wu, B., Stay, T.L. and Tay, J. H. (2006). "Biodegradation of pnitrophenol by aerobic granules in a sequencing batch reactor."Environ. Sci. Technol., 40, pp. 2396–2401. [5] Martin-Hernandez, M., Carrera, J., Perez, J. and Suarez-Ojeda, M.E. (2009). "Enrichment of a K-strategist microbial population able to biodegrade p-nitrophenol in a sequencing batch reactor." Water Res., Vol. 43, pp. 3871–3883. [6] Salehi, Z., Sohrabi, M., Vahabzadeh, F., Fatemi, S. and Kawase, Y. (2010). "Modeling of p-nitrophenol biodegradation by Ralstoniaeutropha via application of the substrate inhibition concept." J Hazard. Mater., Vol. 177, pp. 582–585. [7] She, Z., GaoJin, M., C., Chen, Y. and Yu, J. (2005). 'Toxicity and biodegradation of 2,4-dinitrophenol and 3- nitrophenol in anaerobic systems." Process Biochem., Vol. 40, pp. 3017–24. [8] Qiu, X., Zhong, Q., Li, M., Bai, W. and Li, B. (2007). "Biodegradation of p-nitrophenol by methyl parathion degrading Ochrobactrum sp. B2." Int Biodeterior. Biodegrad., Vol. 59, pp. 297–301. [9] Muller, R. H. and Babel, W. (1996). "Growth rate-dependent expression of phenol-assimilation pathways in Alcaligeneseutrophus JMP 134 – the influence of formate as an auxiliary energy source on phenol conversion characteristics."Appl. Microbiol. Biotechnol., Vol. 46, pp.156-162. [10] Salehi, Z., Yoshikawa, H., Mineta, R. and Kawase, Y. (2011). "Aerobic biodegradation of p-nitrophenol by acclimated waste activated sludge in a slurry bubble column." Process. Biochem., Vol. 46, pp. 284–289. [11] Qiu, X., Wu, P., Zhang, H., Li, M. and Yan, Z. (2009). "Isolation and characterization of Arthrobacter sp. HY2 capable of degrading a high concentration of p-nitrophenol." BioresourTechnol., Vol. 100, pp. 5243– 5248. [12] Gemini, V.L., Gallego, A., de Oliveira, V.M., Gomez, C.E., Manfio, G.P., SKorol. E.(2005)."Biodegradation and detoxification of p-nitrophenol by Rhodococcuswratislaviensis." Int Biodeterior. Biodegrad., Vol. 55, pp.103–108. [13] Rezouga, F., Hamdi, M. and Sperandio, M. (2009)."Variability of kinetic parameters due to biomass acclimation: case of para-nitrophenol biodegradation." Bioresour. Technol., Vol. 100, pp. 5021–5029. [14] Muller, S., Bley, T. and Babel, W. (1999). "Adaptive responses of Ralstoniaeutropha to feast and famine conditions analysed by flow cytometry." J. Biotechnol., Vol. 75, pp.81–97. [15] Hill, A., Milne, B. J. and Nawrocki, P. A. (1996). "Cometabolic degradation of 4-chlorophenol by Alcaligeneseutrophus." Appl. Microbiol. Biotechnol., Vol. 46, pp.163-168. [16] Craig Criddle, S. (1993). "The kinetics of cometabolism."Biotechnol. Bioeng., Vol. 41, pp. 1048–1056. [17] Schmidt, S. K., Simkins, S. and Alexander, M. (1985)."Models for the Kinetics of Biodegradation of Organic Compounds Not Supporting Growth." Appl. Env. Mic., pp. 323-331.
J. Chem. Pet. Eng. University of Tehran Journal of Chemical and Petroleum Engineering 2423-673X University of Tehran 8 10.22059/jchpe.2014.7563 Original Paper Artificial Intelligent Modeling and Optimizing of an Industrial Hydrocracker Plant Artificial Intelligent Modeling and Optimizing of an Industrial Hydrocracker Plant Vasseghian Yasser Chemical Engineering Department, Faculty of Engineering, Razi University, Kermanshah, Iran Ahmadi Mojtaba Chemical Engineering Department, Faculty of Engineering, Razi University, Kermanshah, Iran 01 12 2014 48 2 125 137 16 06 2014 25 08 2014 Copyright © 2014, University of Tehran. 2014 https://jchpe.ut.ac.ir/article_7563.html

The main objective of this study is the modelling and optimization of an industrial Hydrocracker Unit (HU) by means of Adaptive Neuro Fuzzy Inference System (ANFIS) model. In this case, some data were collected from an industrial hydrocracker plant. Inputs of an ANFIS include flow rate of fresh feed and recycle hydrogen, temperature of reactors, mole percentage of H2 and H2S, feed flow rate and temperature of debutanizer, pressure of debutanizer receiver, top and bottom temperature and pressure of fractionator column. The network was employed to calculate the flow rate of gas oil, kerosene, Light Naphtha (LN), and Heavy Naphtha (HN).Unseen data points were used to check generalization capability of the best network. There were good adjustment between network estimations and unseen data. Finally optimization was performed to maximize the production volume percent of gas oil, kerosene, HN and LN and to identify the sets of optimum operating parameters in order to maximize yields of mentioned product. Optimum conditions were found as feed flow rate of 90.9 m3/h, reactor temperature of 378.4 °C, hydrogen flow rate of 54.31 MSCM/h and LN (feed vol.%) of 9.34.

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J. Chem. Pet. Eng. University of Tehran Journal of Chemical and Petroleum Engineering 2423-673X University of Tehran 8 10.22059/jchpe.2014.7565 Original Paper Optimization of Dogleg Severity in Directional Drilling Oil Wells Using Particle Swarm Algorithm (Short Communication) Optimization of Dogleg Severity in Directional Drilling Oil Wells Using Particle Swarm Algorithm (Short Communication) Hosseini Siamak Mechanical Engineering, Islamic Azad University, Ahwaz Branch, Ahvaz, Iran Ghanbarzadeh Afshin Faculty of Mechanic, Ahwaz Chamran University, Ahvaz, Iran Hashemi Abdolnabi Faculty of Petroleum, Petroleum University of Technology, Ahwaz, Iran 01 12 2014 48 2 139 151 05 03 2013 09 07 2014 Copyright © 2014, University of Tehran. 2014 https://jchpe.ut.ac.ir/article_7565.html

The dogleg severity is one of the most important parameters in directional drilling. Improvement of these indicators actually means choosing the best conditions for the directional drilling in order to reach the target point. Selection of high levels of the dogleg severity actually means minimizing well trajectory, but on the other hand, increases fatigue in drill string, increases torque and drag, particularly in the rotation mode. Therefore the aim is to define the index in an optimal range which meets both requirements. Particle swarm algorithm was used for optimization the dogleg severity. The final measured depth and directional well pattern were considered as an objective function and Build & Hold, respectively. Then the fatigue caused by the stresses exerted on the drill string, evaluated by modified Goodman equation simultaneously. The relationship between path parameters and the obligation to reach a target point in directional wells, converts the problem into a constrained optimization problem. Comparing the proposed directional drilling path in a drilled well in the Ahwaz oilfield with the responses obtained from the particle swarm algorithm indicated that the particle swarm algorithm is converged in finding the shortest path, and on the other hand, it decreases the time of using directional drilling equipment due to the selection of the proper dogleg severity. Note that it is likely to add other constraints to the optimization process which indicates the particle swarm algorithm efficiency in solving these problems.

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