Accounting
Vahab Montazeri; Atefeh Ghazi
Abstract
AbstractIt is essential to separate two immiscible liquids from gas to produce the light liquid, heavy liquid, and vapor phases. The separation of water from hydrocarbons is a practical example in the oil industry. For such separation in industry, three phase separator is used. In this study, different ...
Read More
AbstractIt is essential to separate two immiscible liquids from gas to produce the light liquid, heavy liquid, and vapor phases. The separation of water from hydrocarbons is a practical example in the oil industry. For such separation in industry, three phase separator is used. In this study, different parameter and the weight of the three-phase separator was optimized with the genetic algorithm (G.A.) and finally, the total cost of manufacturing the separator was decreased. Different types of three-phase separators are vertical, horizontal, and spherical. The separator works in the operating condition of 172 kPa and 445 K, respectively and the real weight of the separator is 8131 kg. For the optimization target, the flow of vapor, light liquid, and heavy liquid was considered constant during the optimization process. The objective function (O.F.) is obtained from the weight of the separator and 3 multiparameter equations. Also, 7 parameters which include: separator aspect ratio (L/D), the height of heavy liquid (HHL), height of light liquid (HLL), hold-up time (TH), surge time (TS), low liquid level (HLLL) and vapor level (Hv) are used in G.A. as constraints. The weight of the optimized separator was calculated 6001 kg approximately. So, with this method, the total weight of the separator decreases by about 26.2 % as compared to the real weight of the separator. On the other hand, the maximum difference between the answers was 3.3%, which is acceptable. Also, error analysis of the predicted results is calculated by mean absolute percentage error (MAPE) for 7 design parameters of the three-phase separator and separator weight, which are in an acceptable level of accuracy. The presented approach can have potential application for the development of low-cost manufacturing of three-phase separators in the petroleum industry.
Petroleum Engineering
Ali Moazami Goodarzi; Arman Darvish Sarvestani; Ali Hadipour
Abstract
Nowadays, the increasing demand for energy in the world is one of the main concerns for energy supply. In fact, the required energy can be obtained by increasing the production rate of fossil fuels such as oil and natural gas. However, improving the efficiency of the equipment and facilities might have ...
Read More
Nowadays, the increasing demand for energy in the world is one of the main concerns for energy supply. In fact, the required energy can be obtained by increasing the production rate of fossil fuels such as oil and natural gas. However, improving the efficiency of the equipment and facilities might have a significant impact on production from hydrocarbon resources. With respect to this subject, the optimization of separation facilities will be a simple and economic choice to increase the amount of the liquid obtained from production units all over the world. One of the parameters which have a noticeable effect on the yield of the production units is the separator pressure. Also, there are other factors such as heptane plus fraction properties, well head pressure, and ambient temperature which can change the optimum separator conditions. In this study, the influence of crude oil properties on the number of stages and pressure of each separator is investigated. The result shows that the most important property of the feed which has the greatest influence on the conditions of separators is the percentage of heptane plus fraction in crude oil. Therefore, a method for the estimation of the number of separators based on the percentage of C7+ component is developed. Moreover, the threshold of heptane plus fraction for selecting the optimum number of separator stages was observed to be around 30% in the feed composition. Hence, three separators and a stock tank can separate samples with a C7+ molar fraction lower than 30%, but two separators and a stock tank are needed for samples with a heptane plus fraction higher than 30%. Finally, the results indicate an increase of about 1.3% in the oil production for the new optimization method compared to the constant-ratio method.
Petroleum Engineering
Shahin Kord; Omid Ourahmadi; Arman Namaee-Ghasemi
Abstract
Production strategy from a hydrocarbon reservoir plays an important role in optimal field development in the sense of maximizing oil recovery and economic profits. To this end, self-adapting optimization algorithms are necessary due to the great number of variables and the excessive time required for ...
Read More
Production strategy from a hydrocarbon reservoir plays an important role in optimal field development in the sense of maximizing oil recovery and economic profits. To this end, self-adapting optimization algorithms are necessary due to the great number of variables and the excessive time required for exhaustive simulation runs. Thus, this paper utilizes genetic algorithm (GA), and the objective function is defined as net present value (NPV). After developing a suitable program code and coupling it with a commercial simulator, the accuracy of the code was ensured using a synthetic reservoir. Afterward, the program was applied to an Iranian southwest oil reservoir in order to attain the optimum scenario for primary and secondary production. Different hybrid water/gas injection scenarios were studied, and the type of wells, the number of wells, well coordination/location, and the flow rate (production/injection) of each well were optimized. The results from these scenarios were compared, and simultaneous water and gas (SWAG) injection was found to have the highest overall profit representing an NPV of about 28.1 billion dollars. The application of automated optimization procedures gives rise to the possibility of including additional decision variables with less time consumption, and thus pushing the scopes of optimization projects even further.
Petroleum Engineering
Arezou Jafari; Peyman Sadirli; Reza Gharibshahi; Esmaeel Kazemi Tooseh; Masoud Samivand; Ali Teymouri
Abstract
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 ...
Read More
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 x-direction were generated, and by analyzing the results of gas saturation in the porous medium for each model, a grid with 11250 cells (50 elements in x-direction and 15 elements in y- and z-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.
Chemical Engineering – Gas Processing and Transmission
Mahnaz Pourkhalil
Abstract
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 NH3 as a reductant agent in the presence of excess ...
Read More
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 NH3 as a reductant agent in the presence of excess oxygen. These catalysts were characterized by FTIR, XRD, SEM-EDS, and H2-TPR methods. The response surface methodology was employed to model and optimize the effective parameters in the preparation of CuOx/OMWNT’s catalysts in NOx removal by NH3-SCR process. Three experimental parameters, including calcination temperature, calcination time, and CuOx loading were chosen as the independent variables. The central composite design was utilized to establish a quadratic model as a functional relationship between the conversion of NOx as a response factor and independent variables. The ANOVA results showed that the NOx conversion is significantly affected by calcination temperature and CuOx loading. At the optimal values of the studied parameters, the maximum conversion of NOx, 86.3 %, was obtained at a calcination temperature of 318 °C, a calcination time of 3.4 hr., and CuOx loading of 16.73 wt.%; the reaction conditions was as follows: T= 200 °C, P= 1 bar, NO = NH3 = 900 ppm, O2 = 5 vol.%, and GHSV = 30,000 hr.−1. The regression analysis with an R2value of 0.9908 revealed a satisfactory correlation between the experimental data and the values predicted for the conversion of NOx. The XRD and H2-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.
Seyed Ali Hosseini; Sirus Nouri; Sajad Hashemi; Mansor Akbari
Abstract
The removal of sulfur compounds from petroleum is extremely necessary for industrial and environmental reasons. Sulfur in transportation fuels is a major air pollution source. In this work, the efficiency of nanostructured Ni-clinoptilolite adsorbent was investigated in the removal of sulfur from gas ...
Read More
The removal of sulfur compounds from petroleum is extremely necessary for industrial and environmental reasons. Sulfur in transportation fuels is a major air pollution source. In this work, the efficiency of nanostructured Ni-clinoptilolite adsorbent was investigated in the removal of sulfur from gas oil. For this purpose, the design of experiments was performed by selecting effective factors in desulfurization process. Response surface methodology was selected to model the desulfurization process. Ni-containing nanoadsorbents were prepared by a wet-impregnation method. Gas oil model containing 300 ppmW [M. N.1] sulfur was prepared by dissolving a calculated amount of dibenzothiophene (DBT) in n-decane. The concentration of DBT in n-decane was determined by UV-Visible spectrophotometer. The results revealed that sulfur removal extremely depended on the amount of metal and the nature of both metal and support. 5% Ni/support adsorbent resulted in higher sulfur removal efficiency. The optimum ratio of H2O2 to gas oil in the studied conditions was in the range of 5% (v/v) and 240 minutes for the best desulfurization performance during the process.
Turaj Behrouz; Mohammad Reza Rasaei; Rahim Masoudi
Abstract
Intelligent well technology has provided facility for real time production control through use of subsurface instrumentation. Early detection of water production allows for a prompt remedial action. Effective water control requires the appropriate performance of individual devices in wells on maintaining ...
Read More
Intelligent well technology has provided facility for real time production control through use of subsurface instrumentation. Early detection of water production allows for a prompt remedial action. Effective water control requires the appropriate performance of individual devices in wells on maintaining the equilibrium between water and oil production over the entire field life. However, there is still an incomplete understanding of using intelligent well concept to control unwanted fluids and the way this leads to improving hydrocarbon recovery. The present study proposes using intelligent well technology to develop a new integrated methodology for selecting/ranking the candidate wells/fields, interval control valve (ICV) size determination, and ICV setting optimization. Various technical and economical parameters weighted by expert opinions are used for candidate well/field ranking to implement the intelligent technology. A workflow is proposed for ICV size determination based on its effect on a predefined objective function. Inappropriate ICV size selection leads to suboptimum production scenarios. Furthermore, this study proposes an efficient ICV setting optimization in an intelligent well. The objective function can maximize cumulative oil, minimize water production, or conduct both. It was shown that for selecting the optimized cases, the balance between water and oil production under predefined criteria should be practiced. Real case studies were considered to demonstrate the effectiveness and robustness of the proposed methodology. A considerable improvement in the objective function was achieved using the developed methodology.