## 1 Introduction  
The impact of mineral oil pollution is a widely spread source of environmental concern in various ecosystems [1; 2]. The detection of the sea surface expression of oil using space-borne surveillance systems is an extensively studied subject [3; 4; 5]. Oil floating on the surface of the ocean can be located, to some extent, with different types of remote sensing sensors--e.g., thermal infrared (AVHRR: Advanced Very High Resolution Radiometer [6]), visible/near infrared (MODIS: Moderate Resolution Imaging Spectroradiometer [7]), etc.--but generally, most attempts concentrate on usingsatellite-derived measurements from active microwave-imaging instruments (SAR: Synthetic Aperture Radars [8; 9; 10]), e.g., RADARSAT [11; 12]. Research projects using SAR measurements to study petrogenic oil slicks usually focus on understanding two major processes: (1) Identification of smoother regions observed at the sea surface with reduced radar backscattering signal, i.e., classification and segmentation for dark spot detection (e.g., [13]); and (2) Differentiation of radar signature of mineral oil slicks from what is commonly referred to as \"radar look-alikes\" (e.g., [14])--for instance, surface natural oil produced by plants or animals (i.e., biogenic oil films), atmospheric conditions (e.g., low wind and rain cells), oceanographic features (e.g., upwelling regions and internal gravitational waves), etc. [15]. Apart from the scientific effort studying these two processes [16], few investigations are directed at using remote sensing systems to differentiate the mineral oil-slick type--i.e., differences among types of anthropogenic oil slicks observed at the sea surface, for instance: oil slicks formed from heavy versus light oil [17]; or oil slicks from production oil tests (i.e., oil released at the surface of the ocean in the process of evaluating new drilling wells) versus oily water (i.e., oil slicks from leakages occurring during the exploration or production phases) [18]. The available literature covering the subject of identifying oil slicks at the surface of the ocean using space-borne surveillance systems, for the most part, does not address the petrogenic oil-slick category discrimination: telling apart the oil-slick sea surface expression in relation to their source, thus considering oil seeps (i.e., natural oil seepages from a hydrocarbon reservoirs) versus oil spills (i.e., mineral oil spillages from man-made activities) [19; 20; 21; 22]. The seep-spill discrimination mostly regards two points of view: economic and environmental. While the former deals with the discovery of new oil exploration frontiers in finding the presence of active petroleum systems, the latter is capable of improving the relationship between the oil- and gas-related industry and environmental organizations (and society as a whole) by reducing any origin uncertainty about the oil slick source (i.e., naturally-occurring seeps versus man-made spills). A third point of view is the one of the remote sensing community, in which if a certain methodology is capable of discriminating oil from oil using microwave measurements acquired from space [19; 20; 21; 22], it might be plausible to say that such methodology can also be applied to differentiate oil from look-alike features in SAR imagery. This framework scientifically strengthens the other two points of view. Notwithstanding the relative neglect of research projects on the use of satellite sensors for the discrimination of the oil-slick category, [PERSON] [19] showed it is feasible to use SAR-derived measurements for seep-spill discrimination--see also [20; 21; 22]. These authors have used a series of Multivariate Data Analysis Techniques to devise a novel idea to discriminate the oil-slick category while studying seeps and spills observed on the surface of the ocean in the Gulf of Mexico off the Mexican coast in the Campeche Bay region (Figure 1).