In this paper, the slow evolution of combinatorial chemistry from its dawn in 1980’s to today’s oil field product development is discussed.

Combinatorial chemistry comprises chemical synthetic methods that make it possible to prepare a vast number of compounds in a single process. These compound libraries can be made as mixtures, sets of individual compounds or chemical structures generated by computer software. This phenomenon was first invented by Arpad Furka (Lorand University, Budapest) in 1982. He described the principle of it, the combinatorial synthesis and a deconvolution procedure. The methodology was first used in drug discovery using a wide range of linear or wide range of macrocyclic chemical molecules: peptides, non-peptide oligomers, peptidomimetics, small-molecules, and natural product-like organic molecules. However, handling vast amounts of data and extremely small chemical recovery were a very difficult endeavor. To avoid this problem and help to refine the size of the chemical libraries, various software programs were utilized. This was achieved by utilizing a tool known as Design of Experiment (DoE).
In this paper, the high throughput product screening to identify corrosion inhibitors was performed by utilizing critical micelle concentration (CMC). CMC was used to differentiate performance of libraries of chemical blends. Combinatorial synthesis (or blends) and combinatorial screening were performed by utilizing robotics methodologies.

The corrosion inhibitor formulations predicted by DoE were built out by using combinatorial chemical methods and the arrays of chemical formulations were screened by utilizing high throughput robotics, using CMC as the selection guide. To validate the concept, several known corrosion inhibitor formulas were selected to optimize their efficacy. Each formula contained several active ingredients and a solvent package. These raw materials were blended in random but in a control, manner using combinatorial methodologies. After formulation of a vast array of formulation by using Design Expert solvent package. These raw materials were blended in random but in a control, manner using combinatorial methodologies. After formulation of a vast array of formulation by using Design Expert (DE) software, the products were screened for by CMC using automated surface tension workstation. Several formulations with lower CMC than the reference products were selected.

The selected corrosion inhibitor formulations were identified and blended in larger scales. The efficacy of these products was tested by classical laboratory testing methods such as rotating cylinder electrode (RCE) and rotating cage autoclave (RCA) to determine their performance as anti-corrosion agents. These tests were performed against the original reference corrosion inhibitor. The testing indicated that several corrosion inhibitor formulations outperform the original blend thus validating the proof of concept.