Talita Lammoglia

Unraveling Hydrocarbon Microseepages in Onshore Basins Using Spectral-Spatial Processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data

This study focuses on the spectral characterization of superficial effects caused by natural gaseous hydrocarbon (HC) escapes (microseepages) on onshore basins and means to detect the phenomena using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. The Northern Tucano basin (NTB) (Brazil) displays archetypal onshore microseepages, and it is used here as a case study area. Regional HC geochemical data yielded from NTB soil samples helped to outline the strategies for imagery processing and assessment of results. We firstly devised a generic detection model for onshore basins in which microseepages indicated by HC geochemistry should spatially match a number of surface expressions with key remote sensing signatures, such as bleached soil and rocks (i.e., reduction in Fe3+ to Fe2+), concentration of specific clays (kaolinite), and carbonates (siderite) and geobotanical markers. These evidences guided the use of remote sensing data and information extraction techniques to find more sites favorable to host HC microseepages in the NTB. ASTER data processed through spectral mixing analysis and supervised and unsupervised neural network systems highlighted sites where features predicted in the detection model concurred seamlessly with geochemical anomalies. The approach also revealed other sites with similar characteristics, but for which no geochemical data exist. These sites are taken as new potential targets for the presence of microseepages and possibly HC reservoirs. The research demonstrated the potential of remote sensing data and spectral–spatial methodologies for economical, onshore detection of HCs for exploration purposes. Potential ramifications of the study include indirect detection of gaseous HC reservoirs in terrestrial planets (fostering the search for signs of life) and depiction of non-negligible, replenishable continental sources of HC emissions on Earth that may contribute to global warming.

Chronology and backtracking of oil slick trajectory to source in offshore environments using ultraspectral to multispectral remotely sensed data

Offshore natural seepage confirms the occurrence of an active petroleum system with thermal maturation and migration, regardless its economic viability for petroleum production. Ocean dynamics, however, impose a challenge for correlation between oil seeps detected on the water surface and its source at the ocean floor. This hinders the potential use of seeps in petroleum exploration. The present study aims to estimate oil exposure time on the water surface via remote sensing in order to help locating ocean floor seepage sources. Spectral reflectance properties of a variety of fresh crude oils, oil films on water and oil–water emulsions were determined. Their spectral identity was used to estimate the duration of exposure of oil–water emulsions based on their temporal spectral responses. Laboratory models efficiently predicted oil status using ultraspectral (>2000 bands), hyperspectral (>300 bands), and multispectral (<10 bands) sensors covering near infrared and shortwave infrared wavelengths. An oil seepage recorded by the ASTER sensor on the Brazilian coast was used to test the designed predictive model. Results indicate that the model can successfully forecast the timeframe of crude oil exposure in the ocean (i.e., the relative “age” of the seepage). The limited spectral resolution of the ASTER sensor, though, implies less accurate estimates compared to higher resolution sensors. The spectral libraries and the method proposed here can be reproduced for other oceanic areas in order to approximate the duration of exposure of noticeable natural oil seepages. This type of information is optimal for seepage tracing and, therefore, for oceanic petroleum exploration and environmental monitoring.