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 ...
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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
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 ...
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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.
Chemical Engineering
Saeed Mohammadi; Mohammad Amin Sobati; Mohammad Sadeghi
Abstract
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 ...
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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.