Oil spills at sea are a major public concern as they represent risks to environment and coastal population. The growth of oil exploration and ship movement increases the possibility of accidents, in this context remote sensing is used as an indispensable tool for the detection and monitoring of oil slicks on the sea surface. The present work presents a review of the recent research developed in the area, which mainly aims to improve the accuracy of detection and classification of oil spill. Synthetic Aperture Radar (SAR) stands out as the most used sensor, being efficient even in the presence of clouds and at night. The current challenge is the need to create efficient methodologies in distinguishing oil slicks from other dark features that appear in the radar image formed by various phenomena that can generate lookalikes.