The chemical make-up of over one hundred demulsifiers was characterized by nuclear magnetic resonance spectroscopy and compared to their effectiveness as determined by standard bottle tests. Principal component analysis was used to handle the extensive data generated from the nmr and bottle tests. The demulsifiers clustered into only a few distinctly different chemical groups. These similar chemical types were shown to have similar demulsification performance which means that demulsifier evaluations can be made on the basis of demulsifier chemistry. Therefore only a few of the chemically distinct ones need to be tested before optimization can begin. Since the nmr chemical characterization takes only a fraction of the time of a bottle test, it is possible to more rapidly identify the best demulsifier and to focus on optimization of demulsifter dosage.

This characterization method would be especially useful for chemical suppliers as a way to significantly decrease the number of demulsifters that are evaluated in the field before work begins on optimization.

Future research will develop and expand the database to relate demulsifier chemistry to oil and emulsion properties; ultimately to predict demulsiftcation performance from first principles.


Chemical demulsification is commonly used to separate water from heavy oils in order to produce a fluid suitable for pipelining (typically less than 0.5 percent solids and water). A wide range of chemical demulsifiers are available in order to effect this separation. In principle, a complete chemical and physical characterization of both the demulsifier and the emulsion to be separated would allow one to develop a fundamental understanding of the demulsification mechanism and therefore to optimize the demulsifier selection or allow synthesis of tailored demulsifiers for separation of particular emulsions.

In practice, this is not yet possible because of the wide range of factors that can affect demulsifier performance. Aside from demulsifier chemistry, factors like oil chemistry. the presence and wettability of solids, oil viscosity and the size distribution of the dispersed water phase can all influence demulsifier effectiveness. As a result, an empirical approach involving the testing of many, (often hundreds), of demulsifiers is undertaken to determine the best candidates for optimization based on dosage.

As a first step in developing a fundamental understanding of the relationship between demulsifier chemistry and effectiveness, 121 different demulsifiers (or demulsifier bases) and six different produced oil samples were evaluated.

Clearly, it would be prohibitive to develop derailed chemical and physical analyses of such a large number of demulsiflers and In any case, such a detailed analyses of the demulsifiers may not completely account for their performances on different oil emulsion samples. However. if performance on a given emulsion were related to chemical composition, it would be possible to rapidly optimise demulsifier selection by testing selected members of chemically distinct demulsifier groups and doing more detailed bottle tests only on members of the groups that showed the best results.

Principal component analysis (PCA) is one method that allows one to relatively quickly develop correlations between similar members of large data sets l,2.

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