Summary
Natural hydrocarbon seeps have an important role in the carbon cycle and in the Gulf of Mexico (GOM) ecosystem. The magnitude of these natural oil seeps was analyzed with 3D-seismic attributes in combination with satellite and acoustic data. Hydrocarbon seepage in the deep water of the GOM is associated with deep cutting faults, generated by vertical salt movement, that provide conduits for the upward migration of oil and gas. Seeps transform surface geology and generate prominent geophysical targets that can be identified in 3D-seismic data. Seafloor-amplitude anomalies in plain view correlate with the underlying fault systems.
On the basis of 3D-seismic data, detailed mapping of the northern GOM has identified more than 24,000 geophysical anomalies across the basin. In addition to seismic data, synthetic-aperture-radar (SAR) images have proved to be a reliable tool for localizing natural seepage of oil. We used a texture-classifier neural-network algorithm (TCNNA) to process more than 1,200 SAR images collected over the GOM. We quantified more than 1,000 individual seep formations distributed along the outer continental shelf and in deep water. Comparison of the geophysical anomalies with the SAR oil-slick targets shows good general agreement between the distributions of the two indicators. However, there are far fewer active oil seeps than geophysical anomalies, probably because of timing constraints during the basin evolution.
Studying the size of the oil slicks on the surface (normalized to weather conditions), we found that the average flux rate of oil (per seep) may be affected by the local change in the baroclinic and barotrophic pressures [e.g., warm core eddies (WCEs) and storms]. We found that oil slicks in the Mississippi Canyon (MC) protraction area tend to be more sensitive to pressure changes than Green Canyon (GC) protraction-area seeps.
3D mapping of intruding salt bodies in the subsurface of the Gulf of Mexico using 3D seismic data