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Articles by K.A. Elraies
Total Records ( 2 ) for K.A. Elraies
  Shehzad-Ahmed , K.A. Elraies and Shuaib Ahmed Khalwar
  Microemulsion behavior is an important aspect in chemical EOR because these can be used as an indicator for ultra low interfacial tension. At optimal salinity, type III microemulsion begins to form by solubilizing equal volume of aqueous phase and oil phase in the middle phase. However, salinity lower or higher than optimal causes significant increase in the interfacial tension, resulting in insufficient displacement efficiency. In this study, the behavior of microemulsion is investigated experimentally. Type III microemulsion were generated at different salinities using surfactant, co-surfactant, alcohol and crude oil to form gel and liquid crystal free clear microemulsion. As a result, alcohol alkoxy sulfates has shown good performance in term of solubilization for light oil and low temperature conditions. Effect of varying surfactant, co-surfactant and co-solvent concentration on microemulsion parameter has been presented. This systematic approach helps in efficient formulation screening and optimization of chemical EOR formulation in order to achieve ultra low interfacial tension between the residual oil and injection water.
  M.A. Ayoub and K.A. Elraies
  This study presents a universal pressure drop model in pipelines using the Group Method of Data Handling (GMDH)-type neural networks technique. The model has been generated and validated under three phase flow conditions. As it is quite known in production engineering that estimating pressure drop under different angles of inclination is of a massive value for design purposes. The new correlation was made simple for the purpose of eliminating the tedious and yet the inaccurate and cumbersome conventional methods such as empirical correlations and mechanistic methods. In this study, GMDH-type neural networks technique has been utilized as a powerful modeling tool to establish the complex relationship between the most relevant input parameters and the pressure drop in pipeline systems under wide range of angles of inclination. The performance of the model has been evaluated against the best commonly available empirical correlations and mechanistic models in the literature. Statistical and graphical tools were also utilized to show the significance of the generated model. The new developed model reduced the curse of dimensionality in terms of the low number of input parameters that have been utilized as compared to the existing models.
 
 
 
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