Time filter

Source Type

Behrouzifar A.,Iran University of Science and Technology | Asadi A.A.,Iran University of Science and Technology | Mohammadi T.,Iran University of Science and Technology | Pak A.,Iranian Central Oil Fields Company
Ceramics International | Year: 2012

Ba 0.5Sr 0.5Co 0.8Fe 0.2O 3-δ (BSCF) perovskite powder was synthesized via EDTA/citrate complexation method. BSCF membranes were formed by pressing powder at 400 MPa and sintering at 1100°C for 10 h. XRD patterns showed that a high pure powder with cubic structure was obtained. SEM micrographs revealed that the membranes are dense with large grains. Effects of temperature, feed and permeate side oxygen partial pressures, flow rates and membrane thickness on oxygen permeation flux were studied experimentally. A Nernst-Planck based mathematical model, including surface exchange kinetics and bulk diffusion, was developed to predict oxygen permeation flux. Considering non-elementary surface reactions and introducing system hydrodynamics into the model resulted in an excellent agreement (RMSD = 0.0617, AAD = 0.0487 and R 2 = 0.985) between predicted and measured fluxes. The results showed that oxygen permeation flux increases with temperature, feed side oxygen partial pressure and flow rates, however decreases with permeate side oxygen partial pressure and membrane thickness. Contribution of feed side surface exchange reactions, bulk diffusion and permeate side surface exchange reactions resistances in the total resistance are in the range of 8-32%, 10-81% and 11-59%, respectively. Permeation rate-limiting step was determined using the membrane dimensionless characteristic thickness. © 2012 Elsevier Ltd and Techna Group S.r.l. All rights reserved. Source

Rahmani Y.,National Iranian Oil Company | Rahmani Y.,Iranian Central Oil Fields Company | Ganji D.D.,Babol Noshirvani University of Technology
Journal of Thermophysics and Heat Transfer | Year: 2014

The phenomenon of the Newtonian and non-Newtonian fluid flows in ring-shaped pipe has been assessed by the homotopy perturbation method (HPM). An incompressible flow in a ring-shaped pipe by a powerlaw model known as a non-Newtonian fluid was assumed. A direct numerical solution (the fourth-order Runge-Kutta) is implemented to show the preciseness of the results. The effects of the pressure gradient, material parameters, and Brinkman number on the velocity and temperature profiles were investigated and graphically presented. A comparison between analytical and numerical solutions was made. The results show that the velocity increases as the pressure gradient decreases. Moreover, the temperature also increases as the pressure gradient decreases. Source

Amiri M.,University of Technology Malaysia | Ghiasi-Freez J.,Iranian Central Oil Fields Company | Golkar B.,Petroleum University of Technology of Iran | Hatampourd A.,Shahid Bahonar University of Kerman
Journal of Petroleum Science and Engineering | Year: 2015

Tight reservoir refers to reservoirs with low porosity and permeability. Estimating Petrophysical parameters of Tight Gas Sand (TGS) reservoirs is one of the most difficult tasks in reservoir characterization studies. These reservoirs usually produce from multiple layers with different and complex properties. Water saturation is an important petrophysical property representing the fraction of pore volume occupied by formation water that needs to be determined accurately when attempting to characterize hydrocarbon reservoirs. The exact determination of water saturation leads to a precise evaluation of initial hydrocarbon in place, which in turn provides valuable insight into future oil field development plans. In this paper, a model based on feed-forward - back propagation error Artificial Neural Network (ANN) optimized by Imperialist Competitive Algorithm (ICA) to predict water saturation in TGS reservoirs is proposed. ICA is employed to obtain the optimal contribution of ANN for a better water saturation prediction. Conventional well log data are used as input and water saturation data measured on core samples as output variables to the ANN model. In the current study, a number of 2200 data taken from 12 wells selected from a number of TGS basins are used to build a database. The performance of the proposed ICA-ANN model has been compared with the conventional petrophysical and ANN models. Based on cross validation measures, the results clearly show that the ICA-ANN model has outperformed the conventional methods in terms of effectiveness, robustness and compatibility. © 2015 Elsevier B.V. Source

Nasriani H.R.,Iranian Central Oil Fields Company | Kalantariasl A.,University of Adelaide
Society of Petroleum Engineers - SPE Asia Pacific Oil and Gas Conference and Exhibition 2011 | Year: 2011

Multiphase flow occurs in almost all producing oil and gas/condensate wells. Wellhead chokes are special equipment that widely used in the petroleum industry to control flow rate, to maintain well allowable, to protect surface equipments, to prevent water and gas coning and to provide the necessary backpressure to reservoir to avoid formation damage from excessive drawdown. Accurate modeling of choke performance and selection of optimum choke size is vitally important for a petroleum engineer in production from reservoirs due to high sensitivity of oil and gas production to choke size. Two main approaches have been proposed for prediction of multiphase flow through chokes can be classified as either analytical or empirical and majority of correlations were developed for critical flow conditions. Although most of the correlations available to petroleum engineers are for critical flow but in lots of high rate gas/condensate wells subcritical flow occurs in large choke sizes.There is no empirical correlation for wellhead choke performance under subcritical condition for high rate gas condensate wells, especially in large choke sizes. The first aim of this paper is to develop a new simple empirical Gilbert type correlation for high rate gas condensate wells under subcritical flow in large choke sizes (40/64 in. to 192/64 in.) using non-linear regression analysis based on 61 field data points of 15 wells from ten different fields. The second is to extend the work of Al-Attar for high rate gas condensate wells flowing through large choke size under subcritical flow conditions and check the applicability and advantages. Finally, statistical comparison between these two approaches is done with different error parameters. Copyright 2011. Society of Petroleum Engineers. Source

Hatampour A.,Pars Oil And Gas Company | Ghiasi-Freez J.,Iranian Central Oil Fields Company
Petroleum Science and Technology | Year: 2013

Sonic wave velocities, including compressional, shear, and Stoneley, are functional and practical parameters for various branches of reservoir characterization. In the last few years, several tools such as the dipole shear sonic imager (DSI) were introduced for measuring sonic wave velocities. Most of these instruments are expensive and drilling companies do not run them in all wells of a field because of economical restrictions. In this study, an accurate, intelligent, and indirect method was presented for prediction of sonic wave velocities, which are directly obtained from dipole shear sonic log, utilizing conventional well log data and fuzzy logic technique. Furthermore, the proposed methodology was applied on a carbonate reservoir of Iran. The results of the case study demonstrated the capabilities of fuzzy logic for estimation of sonic wave velocities, where DSI may not be run. The MSEs of the predicted Vp, Vs, and Vst in the test data calculated 1.47 (US/F), 4.96 (US/F), and 2.219 (US/F), respectively, which correspond to the R 2 values of 91.8%, 89.3%, and 90.4%, respectively. © 2013 Copyright Taylor and Francis Group, LLC. Source

Discover hidden collaborations