For the efficient real-time monitoring of reaction chemistry in a complex mixture using online spectroscopy, it is essential to develop a mathematical tool that can automatically resolve the spectra so that either the spectral or the concentration profile of the changing species can be tracked easily. While self modeling multivariate curve resolution (SMCR) is a well-suited tool when initial profiles are known beforehand, it is not straightforward to use when dealing with complex mixtures. In this study, a multivariate data analysis algorithm was designed for use with online infrared spectroscopy to provide an instant best estimate of the reaction chemistry of a complex mixture with no additional user input. The investigated process is thermal conversion of oil sands bitumen, and the study employed 43 infrared spectra from samples, collected offline, of products treated at different temperatures and time periods. The resolved spectral and concentration profiles can be used to understand the reaction mechanism of the system. In addition to the concentration and spectral profile, simple parameters were devised to monitor the changes in the key regions of the spectral profiles. In general, the results described the possible reaction mechanism of the investigated system and were consistent with other experimental findings in the literature. Computationally, the algorithm requires only a few seconds to converge and is therefore suitable for online monitoring.