Real-time Hydrocarbon Composition Measurement

In the global refining marketplace the single biggest cost is the raw feedstock: crude oil. To improve margins, increasing, the use of 'opportunity crudes' helps to lowers the cost of the crude blend.

However, as these oils are new to the marketplace and many refineries have never processed them before it brings about challenges including, lack of understanding of the quality of the crude oil being processed (shale oils for example can come from many thousands of wells) and how these oils interact with the more conventional blended crude oils.

Intertek are a Total Quality Assurance provider to industries worldwide including the oil and gas sector. Their Interpret software package uses NIR Spectroscopy alongside data analysis techniques to provide real-time prediction of the properties of Hydrocarbon streams without the need for time consuming lab experiments. Enabling the end user to have a better understanding of how their specific feedstock will behave in their process.

This project will seek to investigate the development and incorporation of new state-of-art clustering and classification algorithms into the Interpret software package, with the objective of improving the predictive performance of their software package, allowing Intertek to stay at the forefront of their competition in providing their customers with real-time, traceable insight on crude oil compositions.