Analysis of oil volume fluxes of hydrocarbon seep formations on the Green Canyon and Mississippi Canyon: a study using 3-d seismic attributes in combination with satellite and acoustic data.

摘要

Analyzing the magnitude of oil discharges from natural hydrocarbon seeps is important for improving our understanding oftheir role in the carbon cycle and in the Gulf of Mexico (GOM) ecosystem. Hydrocarbon seepage in the deep water of theGOM is associated with deep cutting faults, generated by vertical salt movement, that provide conduits for the upwardmigration of oil and gas. Seeps transform surface geology and generate prominent geophysical targets that can be identifiedin 3‐D seismic data. Seafloor amplitude anomalies in plan view correlate with the underlying fault systems.Based on 3D seismic data, detailed mapping of the northern GOM has identified more than 24,000 geophysical anomaliesacross the basin. In addition to seismic data, Synthetic Aperture Radar (SAR) images have proven to be a reliable tool forlocalizing natural seepage of oil. We used a Texture Classifier Neural Network Algorithm (TCNNA) to process more than1200 SAR images collected over the GOM. We quantified more than 1000 individual seep formations distributed along theouter continental shelf and in deep water. Comparison of the geophysical anomalies with the SAR oil slick targets showsgood general agreement between the distributions of the two indicators. However, there are far fewer active oil seeps thangeophysical anomalies, probably due to 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 pressure (e.g. warm core eddies, storms, etc).We found that oil slicks in the Mississippi Canyon protraction area tend to be more sensitive to pressure changes than GreenCanyon protraction area seeps.