MODELLING OF DEMULSIFICATION PROCESS OF WATER IN CRUDE OIL EMULSION BY NEW DEMULSIFIER

  View PDF

  Download PDF

  Noor kassem Mohssen   |      Mustafa Al-Faize   |      Salah Abdul Wahab   |   

Castor Oil is a natural raw material, used to prepare Brominated Castor Oil (BCO) and quaternary ammonium salt-based castor oil (TEt-CO). The two products were tested as demulsifiers and compared with a commercial demulsifier (Chimec 2439) by using the bottle test method. BCO showed a high ability on the water separation efficiency of 90 % with a dose of 150 μl at 120 min time settling while TEt-CO showed a low water separation efficiency reached 10 %. The effect of the demulsifier BCO was tested by varying different variables which have an obvious effect on water separation efficiencies such as dose, temperature, time of mixing emulsion, pH, and salinity of aqueous phase of the emulsion, and water ratio. The effect of some additives (i.e. methanol, ethanol, xylene, and toluene) on the efficiency of the BCO was tested for the purpose of enhancing its effectiveness to break the crude oil emulsion. The experimental data obtained by using BCO were formulated as a model using the Artificial Neural Networks (ANNs) to evaluating the water separation efficiency. A multi-layer perceptron artificial neural network was developed based on the collected data of this study. The results showed that the training algorithm of backpropagation (BP) is sufficient enough in predicting BCO efficiency under different operation conditions. It was found that the correlation coefficient values are 0.9995 and 0.9999 for the testing and training data, respectively and the mean square error (MSE) was 6.18*10^-5 at 200 epochs.