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In this paper we propose a model-based oil spill detection approach using polarimetic SAR data. The underlying hypothesis is that the co-polarized phase difference is zero when assuming Bragg scattering mechanisms. From this hypothesis we may construct a (linear) model and derive features that discriminates oil slicks from sea water using dual-polarized (VV and HH) SAR data. We also investigate the model when assuming X-Bragg scattering, and derive a feature based on the Pauli decomposition that are invariant to the tilt angle reflection plane. The oil spill detection methodology is evaluated on a Radarsat-2 quad-pol image that covers various types of oil released in an oil-in-sea exercise in Norway. The results show that the oil spills are clearly visible in all of the derived feature-based images. Furthermore, the feature images have a more homogeneous background than the VV-polarized SAR image, in particular the Pauli-based feature image that suppresses a non-oil slick present in the VV-image.