فهرست مطالب

Chemical and Petroleum Engineering - Volume:53 Issue:2, 2019
  • Volume:53 Issue:2, 2019
  • تاریخ انتشار: 1398/09/10
  • تعداد عناوین: 12
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  • Saeideh Mohammadi, Elnaz Khodapanah *, Seyyed Alireza Tabatabaei Nejad Pages 137-152

    In this study, simulation of low salinity polymer flooding in the core scale is investigated using Eclipse-100 simulator. For this purpose, two sets of data are used. The first set of data were adopted from the results of experimental studies conducted at the University of Bergen, performed using Berea sandstone and intermediate oil. The second data set, related to sand pack and heavy oil system, was obtained from experiments performed at Sahand Oil and Gas Research Institute. To obtain relative permeability and capillary pressure curves, automatic history matching is implemented by coupling Eclipse-100 and MATLAB software. Three different correlations are used for relative permeability. The parameters of each model are calculated using four different optimization algorithms, including Levenberg-Marquardt, Trust-region, Fminsearch, and Pattern search. The results showed that regardless of the optimization algorithm being used, applying relative permeability model of Lomeland et al., known as LET model, best matches the experimental oil recovery data in comparison with those of Corey and Skjeaveland et al.’s relative permeability correlations. The LET model and the Trust-region algorithm were selected for simulation of low salinity polymer flooding process. Simulation of the first set of data showed that using low salinity water flooding before polymer flooding, oil recovery was increased about 16%. In addition, using the second set of data, simulation of low salinity polymer flooding scenario is investigated in a long core model, taken from one of the southwestern fields of Iran. Simulation results show an increase of about 34% in the recovery of low salinity polymer flooding compared to the water flooding scenario.

    Keywords: Eclipse-100 Simulator, History Matching, Low Salinity Polymer Injection, MATLAB Software, Optimization Algorithm, Relative Permeability
  • Zeinab Hosseini Dastgerdi, Saeid Jafarzadeh Ghoushchi * Pages 153-167

    The precipitation of asphaltene, one of the components of oil, in reservoirs, transfer lines, and equipment causes many problems. Accordingly, researchers are prompted to determine the factors affecting asphaltene precipitation and methods of avoiding its formation. Predicting precipitation and examining the simultaneous effect of operational variables on asphaltene precipitation are difficult because of the multiplicity, complexity, and nonlinearity of factors affecting asphaltene precipitation and the high cost of experiments. This study combined the use of response surface methodology and the artificial neural network to predict asphaltene precipitation under the mutual effects of various parameters. The values of such parameters were determined to reach the minimum amount of precipitation. We initially selected the appropriate algorithm for predicting asphaltene precipitation from the two neural network algorithms. The outputs of designed experiments in response surface methodology were determined using the optimum algorithm of the neural network. The effects of variables on asphaltene precipitation were then investigated by response surface methodology. According to the results, the minimum precipitation of asphaltene achieved at zero mole percent of injected nitrogen and methane, 10–20 mole percent of injected carbon dioxide, asphaltene content of 0.46, the resin content of 16.8 weight percent, the pressure of 333 psi, and temperature of 180 . Results showed that despite the complexities of asphaltene precipitation, the combination of artificial neural network with response surface methodology can be successfully used to investigate the mutual effect of different variables affecting asphaltene precipitation.

    Keywords: Artificial Neural Network Asphaltene, desirability, Precipitation, response surface methodology
  • Mohsen Samimi *, Ali Hojatnia Pages 169-176
    In this study, a novel amine ionic liquid “Diethanolamine Lactic” [DEA][Lac] was synthesized. The replacement of halogenated ion fluid was used as a modified methodology for the preparation of diethanolamine based on lactic acid. The ionic liquid was characterized using the Fourier transform infrared (FTIR) spectra and the nuclear magnetic resonance (NMR) spectroscopy. The changes in bands' wavelengths and the peaks of the participating elements and process materials have been confirmed before and after synthesis based on the results of FTIR analysis which demonstrate the successful synthesis of diethanolamine lactic. The NMR analysis also clearly confirms the synthesis of diethanolamine lactic acid. Analysis results were shown in the successful synthesis of the [diethanolamine] [lactic].
    Keywords: diethanolamine, HCl, Ionic liquids, lactic acid, synthesis
  • Afshin Dehghani Kiadehi, Bahman Mehdizadeh, Kamyar Movagharnejad * Pages 177-189
    Bubble point pressure is an important parameter in equilibrium calculations of reservoir fluids and having other applications in reservoir engineering. In this work, an artificial neural network (ANN) and a least square support vector machine (LS-SVM) have been used to predict the bubble point pressure of reservoir fluids. Also, the accuracy of the models have been compared to two-equation state-based models, i.e. SRK-EOS and PR-EOS and four empirical equations, i.e. Whitson, Standing, Wilson and Ghafoori et al. Compared to the experimental data, the average relative deviations (ARD) of bubble pressure prediction for these equations were obtained to be 14%, 29%, 66%, 30%, 38%, and 11%, respectively. The best semi-empirical equation has an ARD of about 11% while, the ANN and LS-SVM models have an ARD of 8% and 4.68%, respectively. Thus, it can be concluded that generally, these soft computing models appear to be more accurate than the empirical and EOS based methods for prediction of bubble point pressure of reservoir fluids.
    Keywords: Artificial Neural Network, Bubble pressure, empirical correlations, Genetic Algorithm, reservoir fluids, Support vector machine
  • Sohrab Fathi, Abbas Rezaei, Majid Mohadesi *, Mona Nazari Pages 191-201
    In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (SA), temperature (T), and pressure (P) were related to the output parameter which is propylene or propane adsorption. A thorough comparison between the experimental, artificial neural network and particle swarm optimization-adaptive neuro-fuzzy inference system models was carried out to prove its efficiency in accurate prediction and computation time. The obtained results show that both investigated methods have good agreements in comparison with the experimental data, but the proposed artificial neural network structure is more precise than our proposed PSO-ANFIS structure. Mean absolute error (MAE) for ANN and ANFIS models were 0.111 and 0.421, respectively.
    Keywords: Adsorption, ANN, Cu-BTC, Propylene, Propane, PSO-ANFIS
  • Hassan Panahi, Abdolmajid Eslami * Pages 203-210
    The present study focused on stress corrosion cracking (SCC) and corrosion behavior of ferritic stainless steel (grade 430) in activated methyl diethanolamine (aMDEA) solution, which is classified as a tertiary amine. In this regard, cyclic polarization and U-bend tests were performed in CO2 loaded aMDEA with different concentrations at 25 and 70 °C to observe corrosion behavior and also the possibility of crack initiation. Based on the obtained results, it was found that the corrosion rate increased in concentrated amine solutions. Also, by increasing temperature from 25 to 70 °C both corrosion rate and susceptibility to SCC initiation were intensified. Increment of amine concentration and also increase in temperature led to more absorption of CO2, generating a more acidic solution. Overall it could be stated that while for the grade 430 stainless steel investigated in this study corrosion and cracking was observed Therefore it could be concluded that in amine-containing environments this steel is not a very suitable alternative for carbon steels, which are commonly used in these environments.
    Keywords: aMDEA, Corrosion, Ferritic Stainless-Steel Tertiary Amine Solution Stress, Corrosion Cracking
  • Farid Ghodusi, Hossein Jalalifar *, Saeed Jafari Pages 211-225
    Casing collapse is one of the major problems in oil fields, imposing a lot of costs on oil companies. This problem occurs not only at drilling times in some formations but also after the completion and production can lead to many problems. Analysis of the behavior of casing collapse in terms of geo-mechanics and solid mechanics could significantly meet the needs of the oil industry of Iran. In this study, at first, casing collapse behavior is investigated by considering the formation creep and casing production defects using numerical methods. Then, the effect of some solid mechanics parameters on the casing collapse is investigated. The results showed that casing construction defects, such as ovality and eccentricity and residual stress, could greatly reduce the casing collapse resistance. The resistance reduction of the casing is about 30.37, 9.65, and 46.87 percent respectively, so that when the casing is placed into the well, it undergoes high strain and finally could be reached to collapse.  In addition, it was found that the construction defects show a higher effect on casing collapse than the salt rock creep.
    Keywords: Casing Collapse, Casing Production Defects, Salt Rock Creep, Geomechanics Numerical Modeling
  • Amirhossein Saali, Mohammad Shokouhi, Hossein Sakhaeinia * Pages 227-236
    Thermodynamic consistency test of isothermal vapor-liquid equilibrium (VLE) data of various binary systems containing Carbon dioxide (CO2)/Room temperature ionic liquids (RTILs) have been investigated in wide ranges of pressures in each isotherm precisely. In this paper Generic van der Waals (GvdW) equation of state (EoS) coupled with modified van der Waals Berthelot mixing rule has successfully been applied for correlating P-T-x binary data. The optimum parameters were obtained by minimizing the average relative deviation between modeled and experimental data based on the bubble pressure algorithm. Modeling is highly shown satisfactory in all cases which means that deviations in correlated data are low subsequently can prove that the flexibility and capability of the proposed model for thermodynamic consistency. Results of the consistency test represented ten isothermal experimental data set to be thermodynamically consistent, fourteen were declared to be not fully consistent and just four isothermal experimental data sets were represented to be thermodynamically inconsistent.
    Keywords: carbon dioxide, Equation of State, Generic Van Der Waals, Room-Temperature Ionic Liquids, Thermodynamic consistency test
  • Nadia Al Khalifin, Adel Al Ajmi *, Hamoud Al Hadrami Pages 237-244

    Sand production is a universally encountered issue during the exploration of unconsolidated sandstone reservoirs particularly during production. The production of sand particles with the reservoir fluids depends on the stress around a wellbore and the properties of the reservoir rocks and fluids. Therefore, it is crucial to predict under what production conditions sanding will occur and when sand control is needed to come up with the optimal field development plan. This paper presents new geomechanical stability charts for Oman that have been generated to predict sand production in sandstone formations during the production process. The produced stability charts simplified the complicated task of geomechanical analysis, and they are ready for direct applications by petroleum engineers with no need to be specialized in rock mechanics. This was achieved by utilizing a three-dimensional model which was previously justified. The applied model utilized the linear poroelastic constitutive model for the stresses around a borehole in conjunction with Mogi-Coulomb law to predict the failure of sandstone formations. In this work, moreover, the optimum well trajectories for Omani oil fields are reported.

    Keywords: Critical drawdown pressure, Mogi-Coulomb criterion, optimum well path, sand production, wellbore stability
  • Mohammad Hasan Badizad, Amir Hossein Saeedi Dehaghani * Pages 245-251
    This study is an attempt to investigate the mechanical behavior of proppant packs deforming under compression loading. A generalized confined compression test (CCT) was simulated in the present study to investigate the deformation of walnut/ceramic proppants against compression. In this way, the CCT was simulated using ABAQUS explicit code. Unlike ordinary CCT, we obtained permeability of compressed packs through image processing of deformed packs. It was observed that a pack with small particles could markedly withstand deformation, however, at the expense of having lower permeability. Also, selecting a proper proppant pack strongly depends on the prevailing stress regime, where at low stress (<30 MPa) uniform walnut pack has the same permeability as a medley of walnut/ceramic pack. But, at greater stresses (> 40 Mpa), the pack with more ceramic is the best choice. Mixtures of walnut and ceramic proppants showed greatly strength improvement compared to similar cases with pure walnut granules. As a result, making use of such packing is highly recommended due to significant mechanical stability and also being of lower price compared to packs of pure ceramic granules.
    Keywords: Confined compression test, Deformation, Hydraulic fracture, Permeability, Proppant
  • Behzad Vaferi * Pages 253-264
    Gas hydrate often occurs in natural gas pipelines and process equipment at high pressure and low temperature. Methanol as a hydrate inhibitor injects to the potential hydrate systems and then recovers from the gas phase and re-injects to the system. Since methanol loss imposes an extra cost on the gas processing plants, designing a process for its reduction is necessary. In this study, an accurate back propagation neural network (BPNN) is designed for the prediction of methanol loss by the gas phase as a function of temperature, pressure, and methanol composition in the aqueous phase. Different configurations of BPNN were trained, tested, and a configuration providing the smallest absolute average relative deviation (AARD%) was chosen as an optimum structure. Finally, comparisons made among the accuracy of the developed BPNN model, process simulators, and probabilistic neural network (PNN). Results confirm that the designed BPNN model is more accurate than the other considered predictive tools. The BPNN provided an AARD=5.75% for prediction of experimental data, while Aspen-HYSYS, Aspen-Plus, and PNN presented an AARD% of 9.71, 12.57, and 13.27, respectively.
    Keywords: Artificial Neural Networks, commonly used process simulators, hydrocarbon gas phase, hydrate inhibition unit, methanol loss
  • Hooman Fatoorehchi *, Sohrab Ali Ghorbanian Pages 265-272
    In this paper, we have exploited the first-order sliding mode control method to track the ECG data of the human heart by three different nonlinear control laws. In order to lessen the intrinsic chattering of the classic sliding mode control system, smooth function approximations of the control input, by means of the hyperbolic tangent and the saturation function, were used. The fast Fourier transform was used to evaluate the average chattering frequency of the control inputs. The synthesized control schemes namely SMC-sign, SMC-tanh, and SMC-sat, were able to track the real-world ECG signal with an average root mean square error of 0.0306 and a chattering frequency of 92.7 Hz. The findings show that the sliding mode controllers can be implemented in electronic artificial pacemakers to provide the intended results successfully. Based on today's electronics, the involved frequency range (556.4 Hz for the worst case) is quite acceptable and practical.
    Keywords: chattering phenomenon, electrocardiogram signal, electronic pacemaker, human heart, nonlinear control, Sliding mode control