Gholamreza Vakili-Nezhaad

CALCULATION OF THE BINARY INTERACTION AND NONRANDOMNESS PARAMETERS OF NRTL, NRTL1, AND NRTL2 MODELS USING GENETIC ALGORITHM FOR TERNARY IONIC LIQUID SYSTEMS

One of the most important applications of thermodynamics is the accurate prediction of fluid phase equilibria problems related to real chemical engineering processes. Various equations of state as well as activity coefficient models have been developed for such calculations with many interaction, size, and randomness parameters, which should be optimized based on powerful and effective computational methods. Leading to globally optimal values, genetic algorithm (GA) as a powerful and effective tool can be used for prediction of the interaction parameters of thermodynamic models in complex liquid-liquid equilibrium (LLE) systems. It requires only lower and upper bounds for the interaction parameters and the necessary initial guesses are produced automatically. In the present work, based on the GA method, a global optimization procedure is introduced for calculation of the binary interaction and nonrandomness parameters of NRTL, NRTL1, and NRTL2 activity coefficient models for 20 ternary aromatic extraction systems containing 16 different ionic liquids at various temperatures. The values of the parameters along with the root-mean-square deviations (rmsd) are reported. The results, in terms of rmsd for NRTL, NRTL1, and NRTL2 models, are very satisfactory, with global values of 0.0031, 0.0020, and 0.0053 for 187 tie-lines respectively. The obtained rmsd values for the NRTL model using the GA method are better than those reported in the literature. The rmsd results for the three studied models show that NRTL1 can handle the LLE calculations with more accuracy than the original NRTL and NRTL2 activity coefficient models.

Applications of Equations of State in the Oil and Gas Industry

Reservoir fluids contain a variety of substances of diverse chemical nature that include hydrocarbons and nonhydrocarbons. Hydrocarbons range from methane to substances that may contain 100 carbon atoms. The chemistry of hydrocarbon reservoir fluids is very complex. In spite of the complexity of hydrocarbon fluids found in underground reservoirs, equations of state have shown surprising performance in the phase-behavior calculations of these complex fluids. An equation of state (EOS) is an analytical expression relating pressure to the volume and temperature. The expression is used to describe the volumetric behavior, the vapor/liquid equilibria (VLE), and the thermal properties of pure substances and mixtures. Numerous EOS have been proposed since Van der Waals introduced his expression in 1873. Currently, a number of EOS are used in reservoir engineering which have shown more reliability in reservoir fluids calculations. In this chapter, a review over the most commonly used EOS in the oil and gas industry has been provided. We explore their strengths and weaknesses and to examine the predictive capability of these equations. A brief introduction to Soave-RedlichKwong (SRK), Peng-Robinson (PR), Patel-Teja (PT), Schmit-Wenzel (SW), and EsmaeilzadehRoshanfekr (ER) equations of state has been provided with intention to compare their efficiency in predicting different reservoir fluids properties. The Progress in developing EOS for the calculation of thermodynamic data and phase behavior is also reviewed. Effect of characterization on VLE predictions as well as advances in application of equations of state for heavy hydrocarbons has been considered in this work. Finally, as a case-study, phase behavior of a typical Omani crude oil as well as application of EOS with proper characterization method for this real oil sample has been examined.

Investigation on the effectiveness of an innovative airfoil-type degasser

ABSTRACT A framework to analyze the fluid mechanisms in baffle type degassers is presented and particularly applied to an innovative airfoil-type degasser. Major fluid events in conventional baffle type degassers such as bubbles rising inside the oil layer and the flow of the oil layer itself were taken into account. However, in the current airfoil-type degasser oil flows over an airfoil surface and at the same time is exposed to an air jet. This air jet attaches to the airfoil surface due to the so called Coanda effect as observed in some trial runs of the system. A curved strip model is suggested to estimate the pressure reduction due to the jet curvature. Then we have performed a convective mass transfer analysis in order to determine the jet effect in reducing the partial pressure of the gas on the oil surface and increasing the rate of bubble formation.