Institute Of Recherche En Genie Chimique Et Petrolier Irgcp

Le Touquet – Paris-Plage, France

Institute Of Recherche En Genie Chimique Et Petrolier Irgcp

Le Touquet – Paris-Plage, France

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Ahmadi M.H.,K. N. Toosi University of Technology | Dehghani S.,K. N. Toosi University of Technology | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp | Mohammadi A.H.,University of KwaZulu - Natal | And 2 more authors.
Energy Conversion and Management | Year: 2013

To study the optimum design factors and the optimal thermo-economical performances an optimal performance analysis of a solar driven heat engine system at maximum thermo-economical objective function conditions is done numerically. In the present investigation, thermodynamic analysis and NSGAII algorithm are employed to optimize objective function associated to the power output, thermal efficiency for a Solar driven engine system. Three decision-making procedures are applied to optimized answers from the results. The error through investigation is shown using error analysis. © 2013 Elsevier Ltd. All rights reserved.


Mohammadi A.,University of Bojnord | Manteghian M.,Tarbiat Modares University | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp | Mohammadi A.H.,University of KwaZulu - Natal
Journal of Chemical and Engineering Data | Year: 2013

One of the limitations in the process of hydrate formation to benefit its positive application is high pressure and low temperature conditions. Design and construction of a unit with the aforementioned conditions is therefore expensive and unsafe. Thus, an investigation of methods for moderation of hydrate formation conditions seems to be very important. As mentioned in literature, utilization of ammonium salts in water normally promotes the hydrate formation conditions. One of these salts is tetra-n-butylammonium fluoride (TBAF). In this research, the dissociation data of semiclathrate hydrates for the systems of methane + TBAF + water, carbon dioxide + TBAF + water, and nitrogen + TBAF + water have been measured and reported. Experimental measurements were performed at three concentrations of TBAF, that is, (0.02, 0.05, and 0.15) mass fraction. A comparison of hydrate dissociation data in the presence or absence of TBAF shows the promotion effect of TBAF on methane, carbon dioxide, and nitrogen hydrate formation. By increasing the concentration of TBAF from (0.02 to 0.15) mass fraction, its promotion effect increases, and the p-T curves of the double gas + TBAF semiclathrate systems shift to the low pressure and high temperature regions (moderate conditions). Results of the experiments show that, contrary to clathrate hydrates, a small increase in temperature of semiclathrate hydrates, studied herein, leads to a noticeable increase in dissociation pressure. © 2013 American Chemical Society.


Shokrollahi A.,Sharif University of Technology | Arabloo M.,Sharif University of Technology | Gharagheizi F.,University of KwaZulu - Natal | Gharagheizi F.,Islamic Azad University at Buinzahra | And 2 more authors.
Fuel | Year: 2013

Multiple contact miscible floods such as injection of relatively inexpensive gases into oil reservoirs are considered as well-established enhanced oil recovery (EOR) techniques for conventional reservoirs. A fundamental factor in the design of gas injection project is the minimum miscibility pressure (MMP), whereas local sweep efficiency from gas injection is very much dependent on the MMP. Slim tube displacements, and rising bubble apparatus (RBA) are two main tests that are used for experimentally determination of MMP but these tests are both costly and time consuming. Hence, searching for quick and accurate mathematical determination of gas-oil MMP is inevitable. The objective of this study is to present a reliable, and predictive model namely, Least-Squares Support Vector Machine (LSSVM) to predict pure and impure CO2 MMP. To this end, about 147 data sets belonging to experimental CO2 MMP values from the literature and corresponding gas/oil compositional information was used to construct and evaluate the reliability of the model. The results show that the proposed model significantly outperforms all the existing methods and provide predictions in acceptable agreement with experimental data. Moreover, it is shown that the proposed model is capable of simulating the actual physical trend of CO2 MMP versus five most important input parameters: reservoir temperature, molecular weight of pentane plus, hydrogen sulfide and nitrogen concentration. Finally, for detection of the probable doubtful CO2 MMP data, outlier diagnosis was performed on the data sets. © 2013 Elsevier Ltd. All rights reserved.


Arabloo M.,Sharif University of Technology | Shokrollahi A.,Sharif University of Technology | Gharagheizi F.,University of KwaZulu - Natal | Gharagheizi F.,Islamic Azad University at Buinzahra | And 2 more authors.
Fuel Processing Technology | Year: 2013

Dew-point pressure is one of the most important quantities for characterizing and successful prediction of the future performance of gas condensate reservoirs. The objective of this study is to present a reliable, computer-based predictive model for prediction of dew-point pressure in gas condensate reservoirs. An intelligent approach based on least square support vector machine (LSSVM) modeling was developed for this purpose. To this end, the model was developed and tested using a total set of 562 experimental data points from different retrograde gas condensate fluids covering a wide range of variables. Coupled simulated annealing (CSA) was employed for optimization of hyper-parameters of the model. The results showed that the developed model significantly outperforms all the existing methods and provide predictions in acceptable agreement with experimental data. In addition, it is shown that the proposed model is capable of simulating the actual physical trend of the dew-point pressure versus temperature for a constant composition fluid on the phase envelope. © 2013 Elsevier B.V.


Arabloo M.,Sharif University of Technology | Amooie M.-A.,Sharif University of Technology | Hemmati-Sarapardeh A.,Sharif University of Technology | Ghazanfari M.-H.,Sharif University of Technology | And 2 more authors.
Fluid Phase Equilibria | Year: 2014

Accurate prediction of the PVT properties of reservoir oil is of primary importance for improved oilfield development strategies. Experimental determination of these properties is expensive and time-consuming. Therefore, new empirical models for universal reservoir oils have been developed as a function of commonly available field data. In this communication, more than 750 experimental data series were gathered from different geographical locations worldwide. Successive linear programming and generalized reduced gradient algorithm as two constrained multivariable search methods were incorporated for modeling and expediting the process of achieving a good feasible solution. Moreover, branch-and-bound method has been utilized to overcome the problem of stalling to local optimal points. In-depth comparative studies have been carried out between the developed models and other published correlations. Finally, a group error analysis was performed to study the behavior of the proposed models as well as existing correlations at different ranges of independent variables. It is shown that the developed models are accurate, reliable and superior to all other published correlations. © 2013 Elsevier B.V.


Fayazi A.,Petroleum University of Technology of Iran | Arabloo M.,Petroleum University of Technology of Iran | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp | Mohammadi A.H.,University of KwaZulu - Natal
Journal of Natural Gas Science and Engineering | Year: 2014

The compressibility factor (Z-factor) of natural gases is necessary in many gas reservoir engineering calculations. Accurate determination of this parameter is of crucial need and challenges a large number of used simulators in petroleum engineering. Although numerous studies for prediction of gas compressibility factor have been reported in the literature, the accurate prediction of this parameter has been a topic of debate in the literature. For this purpose, a new soft computing approach namely, least square support vector machine (LSSVM) modeling optimized with coupled simulated annealing optimization technique is implemented. The model is developed and tested using a large database consisting of more than 2200 samples of sour and sweet gas compositions. The developed model can predict the natural gas compressibility factor as a function of the gas composition (mole percent of C1-C7+, H2S, CO2, and N2), molecular weight of the C7+, pressure and temperature. The calculated Z-factor values by developed intelligent model are also compared with predictions of other well-known empirical correlations. Statistical error analysis shows that the developed LSSVM model outperforms all existing predictive models with average absolute relative error of 0.19% and correlation coefficient of 0.999. Results from present study show that implementation of LSSVM can lead to more accurate and reliable estimation of natural gas compressibility factor. © 2013 Elsevier B.V.


Ahmadi M.H.,K. N. Toosi University of Technology | Sayyaadi H.,K. N. Toosi University of Technology | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp | Mohammadi A.H.,University of KwaZulu - Natal | Barranco-Jimenez M.A.,Escuela Superior de cOmputodel IPN
Energy Conversion and Management | Year: 2013

In the recent years, remarkable attention is drawn to Stirling engine due to noticeable advantages, for instance a lot of resources such as biomass, fossil fuels and solar energy can be applied as heat source. Great number of studies are conducted on Stirling engine and finite time thermo-economic is one of them. In the present study, the dimensionless thermo-economic objective function, thermal efficiency and dimensionless power output are optimized for a dish-Stirling system using finite time thermo-economic analysis and NSGA-II algorithm. Optimized answers are chosen from the results using three decision-making methods. Error analysis is done to find out the error through investigation. © 2013 Elsevier B.V. All rights reserved.


Ahmadi M.H.,K. N. Toosi University of Technology | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp | Mohammadi A.H.,University of KwaZulu - Natal | Dehghani S.,K. N. Toosi University of Technology
Energy Conversion and Management | Year: 2013

In this communication, the optimal power of an endoreversible Stirling cycle with perfect regeneration is investigated. In the endoreversible cycle, external heat transfer processes are irreversible. Optimal temperature of the heat source leading to a maximum power for the cycle is detained. Moreover, effect of design parameters of the Stirling engine on the maximized power of the engine and its corresponding thermal efficiency is studied. © 2013 Elsevier Ltd. All rights reserved.


Ahmadi M.H.,K. N. Toosi University of Technology | Hosseinzade H.,K. N. Toosi University of Technology | Sayyaadi H.,K. N. Toosi University of Technology | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp | And 2 more authors.
Renewable Energy | Year: 2013

In the recent years, numerous studies have been done on Stirling cycle and Stirling engine which have been resulted in different output power and engine thermal efficiency analyses. Finite speed thermodynamic analysis is one of the most prominent ways which considers external irreversibilities. In the present study, output power and engine thermal efficiency are optimized and total pressure losses are minimized using NSGA algorithm and finite speed thermodynamic analysis. The results are successfully verified against experimental data. © 2013 Elsevier Ltd.


Kamari A.,University of KwaZulu - Natal | Safiri A.,Petroleum University of Technology of Iran | Mohammadi A.H.,University of KwaZulu - Natal | Mohammadi A.H.,Institute Of Recherche En Genie Chimique Et Petrolier Irgcp
Journal of Dispersion Science and Technology | Year: 2015

Asphaltenes form the most polar fractions in crude oil, which decrease considerably the rock permeability and the oil recovery and in total can cause operational problems. Hence, it is important to estimate the asphaltene precipitation as a function of operating conditions, crude oil composition, and characterization. In this article, a reliable and robust model, namely, the least squares support vector machine, is applied to predict the onset pressures of asphaltene precipitation in live oil systems as well as oil saturation conditions. To pursue our objective, we used literature-reported onset and saturation (bubble point) pressures data of various live oils from different regions, but mostly from the Middle East, with different amounts of asphaltenes. The results indicate that the proposed strategy provides reasonably satisfactory predictive results. Additionally, the obtained results demonstrate not only the validation of the proposed method but also pose an interesting alternative to the classic methods of estimating asphaltene precipitation due to the low number of adjustable parameters used in our model. (Figure presented.). © 2015, Taylor & Francis Group, LLC.

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