Petroleum Engineering
Naser Akhlaghi; Siavash Riahi
Abstract
One of the tertiary methods for enhanced oil recovery (EOR) is the injection of chemicals into oil reservoirs, and surface active agents (surfactants) are among the most used chemicals. Surfactants lead to increased oil production by decreasing interfacial tension (IFT) between oil and the injected water ...
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One of the tertiary methods for enhanced oil recovery (EOR) is the injection of chemicals into oil reservoirs, and surface active agents (surfactants) are among the most used chemicals. Surfactants lead to increased oil production by decreasing interfacial tension (IFT) between oil and the injected water and to the wettability alteration of the oil reservoir rock. Since surfactants are predominantly expensive materials, it is required to consider an appropriate and high-performance plan for project economics when they are injected into oil reservoirs. One of the operational issues in surfactant flooding is the critical micelle concentration (CMC), which is usually achieved by the injection of surfactant at concentrations higher than CMC. Therefore, the lower the CMC is, the lower the amount of the material needed to be injected into the reservoir becomes, so it will help to economize the project. The salinity of the aqueous phase is a factor affecting the CMC, and with its optimal design, it can reduce the CMC. In this study, the variations of Triton X-100 CMC’s as a nonionic surfactant were measured by altering the concentration of three salts with divalent ions (CaCl2, MgCl2, and Na2SO4) and a single-capacity ion salt (NaCl), as the predominant salts in the porous medium of oil reservoirs, using surface tension (ST) method at ambient temperature and pressure. Each of these salts was dissolved at three concentrations of 0.1, 0.5, and 1 wt.% in distilled water containing specific concentrations of surfactant, and the surfactant CMC in the presence of these salt concentrations was measured. The results showed that increasing the concentration of each salt resulted in a decrease in the CMC, and, in the studied salts, NaCl produced the lowest CMC.
Ali Khazaei; Hossein Parhizgar; Mohammad Reza Dehghani
Abstract
In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures ...
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In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocarbon components. The ANN model has been developed as a function of temperature, critical properties, and acentric factor of the mixture according to conventional corresponding-state models. 80% of the data points were employed for training ANN and the remaining data were utilized for testing the generated model. The average absolute relative deviations (AARD%) of the model for the training set, the testing set, and the total data points were obtained 1.69, 1.86, and 1.72 respectively. Comparing the results with Flory theory, Brok-Bird equation, and group contribution theory has proved the high prediction capability of the attained model.