Vitrinite reflectance (VR) is routinely measured as an indicator of the thermal maturity of source rocks. Since the 1970s, algorithms that model VR have been used to calibrate thermal models. The modelled thermal history can vary significantly depending on the choice of VR model. Over the last few years, numerous VR models have been proposed and it is unclear which one should be used. The choice of the appropriate VR model is often left to the user or modelling software and is used without determining the suitability of the chosen model for the region or dataset. To avoid such biases, we explore a comprehensive VR dataset from the Norwegian North Sea to determine the VR model that best fits measurements. We use a 1D basin model that simulates VR in the well and combine it with global optimization algorithms to determine which of the currently favoured VR models fits the data best. We find that the EasyRo DL model best fits data from the Norwegian North Sea.
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