Iranian Journal of Oil & Gas Science and Technology
Volume:8 Issue: 1, Winter 2019

In sour gas flares,  content like any other components in inlet gas influences adiabatic flame temperature, which, in turn, impacts on the pollutant emission. Wherever flame temperature increases, the endothermic reaction between  and  is accelerated, which means higher  emission to the atmosphere. In this work, we developed an in-house MATLAB code to provide an environment for combustion calculations. Then, this written code was used to perform sensitivity analyses on  content, air temperature, and excess air ratio in sour gas flares. We used Environmental Protection Agency (EPA) reports to assign weighting indexes to each air contaminant according to its harmfulness to environment; thereafter, sour gas flaring conditions were optimized for two real field case studies, namely Ahwaz (AMAK) and South Pars, to reach the minimum integrated pollutant concentrations. The results show that each 2% increase in the  content of the entrance feed may produce 0.3% additional  in the exhaust. The results also confirm that decreases of 20 °F and 50 °F in the oxidant temperature cause  emission to reduce by 0.5% to 1% respectively. Finally, to verify and validate our results acquired from the written MATLAB code, FRNC 2012 industrial software was used to duplicate the oxidation results for the two sour flare case studies.

Natural gas storage process in aquifer, due to fluid flow behavior of gas and water in the porous medium and because of their contact with each other under reservoir conditions, faces several challenges. Therefore, there should be a clear understanding of the injected gas behavior before and after the injection into the reservoir. This research simulates the natural gas storage in aquifer by using Eclipse 300 software. For this purpose, a core sample was considered as the porous medium for gas injection, and a composition of natural gas was injected into the core in different conditions. Moreover, by using Plackett-Burman method, all of the factors affected in this process were screened, and finally four main significant parameters, including the flow rate of injected gas, permeability, pressure, and irreducible water saturation were selected for designing a design of experiments (DOE) plan. Response surface method (RSM) is one of the best methods of experimental design used for optimizing the process and finding the best combination of parameters to have a high stored gas volume and a high recovered gas volume. The simulation includes 28 runs with four considered parameters, and the output is the recovered gas, which in turn is vital for the process accomplishment. Sensitivity analysis and grid independency test were checked. To this end, three grids with different number of cells in directions) was then chosen as the main grid. Uncertainty analysis and the validation of numerical simulations were carried out, and good agreement was observed between the numerical results and experimental data. In addition, the numerical results showed that the flow rate of the injected gas had a significant impact on the process in comparison with other parameters. Furthermore, increasing permeability and decreasing pressure and irreducible water saturation raise the amount of trapped gas in aquifers. Therefore, for having the maximum stored gas volume and a high recovered gas volume, the best combination of parameters is a high gas injection flow rate (0.9 cc/min), high permeability (1.54 md), a low pressure (2254 psi), and irreducible water saturation. (0.46). Finally, in a natural gas storage operation in an aquifer, both rock properties and operational parameters play important roles, and they should be optimized in order to have the highest amount of stored gas.

In matrix acidizing operations, the main goal is increasing permeability. For production engineers, it is desirable that acid could be injected into whole [M.N.1] [amehri.gh2] pay zone. Sometimes, this pay zone has a long height and various sub-layers which have different permeability values. To prevent acid from going completely into the most permeable sub-layer, one of the useful techniques is using diverters, and one of the major groups of diverters is gel diverters. Diverter viscosity changes by temperature and pH, and an increase in viscosity leads to a decrease in its permeability; thus, acid can permeate further through less permeable sub-layers. In this study, two kinds of different viscoelastic surfactants (VES) provided by two different companies were used to produce gel to divert acid into a core plug sample having lower permeability in a dual parallel acid injection set-up. The core plug samples were taken from the pay zone of Ahwaz oilfield, one of Iran southwest oilfields. Before performing the injection test, some viscosity measurement tests were carried out. Unfortunately, one of these two VES’s did not have an acceptable quality and failed to pass the injection tests. However, the other one passed all the tests successfully and diverted the injection fluid. The water permeability values of the low-perm and high-perm core plug samples were 0.91 md and 6.4 md respectively, whereas, after injection, they rose to 1.5 and 18.5 md respectively.

A series of copper oxide (CuOx) catalysts supported by oxidized multi-walled carbon nanotubes (OMWNT’s) were prepared by the wet impregnation method for the low temperature (200 °C) selective catalytic reduction of nitrogen oxides (NOx) using NH-TPR results of the best catalyst showed that the formation of CuO as the dominant phase of CuOx is the key factor in low temperature selective catalytic reduction (SCR) process.

Dilution is one of the various existing methods in reducing heavy crude oil viscosity. In this method, heavy crude oil is mixed with a solvent or lighter oil in order to achieve a certain viscosity. Thus, precise mixing rules are needed to estimate the viscosity of blend. In this work, new empirical models are developed for the calculation of the kinematic viscosity of crude oil and diluent blends. Genetic algorithm (GA) is utilized to determine the parameters of the proposed models. 850 data points on the viscosity of blends (i.e. 717 weight fraction-based data and 133 volume fraction-based data) were obtained from the literature. The prediction result for the volume fraction-based model in terms of the absolute average relative deviation (AARD (%)) was 8.73. The AARD values of the binary and ternary blends of the weight fraction-based model (AARD %) were 7.30 and 10.15 respectively. The proposed correlations were compared with other available correlations in the literature such as Koval, Chevron, Parkash, Maxwell, Wallace and Henry, and Cragoe. The comparison results confirm the better prediction accuracy of the newly proposed correlations.

Packed bed reactors have many applications in different industries such as chemical, petrochemical, and refinery industries. In this work, the effects of some parameters such as the shape and size of particles, bed size, and bed length on the hydrodynamics of the packed beds containing three spherical, cylindrical, and cubic particles types are investigated using CFD. The effect of the combination of three particles types in a packed bed was also simulated. The simulation results show that flow channeling occurs in some parts of the bed which are not suitably covered by particles. It was also seen that flow channeling in the packed bed with cubic particles are more than those containing spherical and cylindrical particles. According to the CFD simulations, wake and vortex flows are created in all the beds, and the shape of particles affects these phenomena. The comparison of the pressure drop created in the packed beds indicates that the pressure drop in the packed beds having three particle types is lower than the packed beds containing only spherical, cylindrical, or cubic particles. Finally, the numerical results were compared with empirical correlations in the literature and showed good agreement.