This document summarizes research on using SAR satellite imagery and machine learning algorithms to detect oil slicks in the Gulf of Mexico, and tracking their movement using the NOAA GNOME oil spill model. It describes algorithms developed for detecting oil slicks in single-polarization SAR images, and techniques for analyzing multi-polarization SAR data. A case study is presented on simulating an oil pipeline leak using GNOME forced by ocean current and wind data, validated against satellite observations.