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Effect of Interfacially Active Fractions of Some Egyptian Crude Oils on Their Emulsion Stability
Authors:Thanaa Abdel‐Moghny  Elshafie Ahmed Gad  Yasser Mostafa
Institution:1. Egyptian Petroleum Research Institute , Cairo, Egypt thanaa_h@yahoo.com;3. Egyptian Petroleum Research Institute , Cairo, Egypt
Abstract:Four samples from different crude oils were used for this study: light and heavy crude oils from Iran and two crude oils from Egypt, namely, Ras Gharb and Suez mix. The asphaltenes were separated from these crude oils and then the maltene (non‐asphaltenic fraction) was fractionated into waxes, aromatics, and resins. All fractions were characterized using FTIR and UV spectroscopic analyses in addition to gel permeation chromatograph (GPC). These fractions were tested for their emulsion stability. For chemometric analysis different parameters (variables) have been used to study the effect of different fractions (objects) on the emulsion stability. Such variables included the integrated areas under the stretching absorption peaks of CH in the range of 3000–2800 cm?1, C?O in the range of 1750–1650 cm?1, and the aromatic C?C in the range of 1650–1550 cm?1, as well as UV absorption value at 235 nm and average molecular weight (MW). Principal component analysis (PCA) and multiple linear regression (MLR) were conducted for examining the relationship between multiple variables and the stability of water‐in‐crude oil emulsions. The results of PCA explain the interrelationships between the observations and variables in multivariate data. The correlation coefficients between different parameters derived from PCA reveals that the UV absorption value and MW are strongly correlated with emulsion stability. It also reveals that the resins, asphaltenes, and maltene have better emulsion stability than waxes and lower molecular weight aromatics. The linear relationship between the parameters and the stability of water‐in‐crude oil emulsions using MLR was modeled according to the better statistical results. The obtained mathematical model can be used to predict the stability of water‐in‐crude oil emulsions from the chemical groups and functionalities in each crude oil fraction.
Keywords:Emulsion stability  principal component analysis  multiple linear regression  quantitative structure property relationship (QSPR)  computational chemistry
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