Determinação do Tempo de Exposição e Condição de Emulsificação da Mistura Óleo-Água na Superfície do Oceano por Meio de Dados Hiperespectrais e Multiespectrais

This research aims to evaluate spectral reflectance properties of oil-water emulsions, fresh crude oils and fresh oil films over water and the use of their spectral identity to classify remote sensing imagery. Chemometric techniques (i.e. partial least square regression) were tested to estimate the age of water-oil emulsions based on their temporal spectral responses. The chemometric models proved to be efficient to predict oil status considering full-resolution spectra (2150 bands VNIR-SWIR) and spectra resampled to equivalent hyperspectral (ProspecTIR 357 bands) and multispectral (ASTER 9 bands) sensors resolutions. An oil seepage recorded by the ASTER sensor in November/2004 at the Brazilian coast was here approached to test the designed predictive model. Results indicate that the model can successfully forecast the timeframe of oil exposition in the ocean (i.e., the relative age of the seepage), although the limited spectral resolution of the ASTER sensor implies in less accurate estimates. The spectral libraries and the method proposed in this study can be reproduced to other oceanic areas in order to approximate the age of noticeable natural oil seepages or anthropogenic oil spills. This type of information is optimal for seepage or leakage tracing and, therefore, for petroleum exploration and environmental monitoring. .Pages: 3626-363

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

CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOOffshore 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 (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 monitoring39113119CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOsem informaçã

Avaliação de métodos para detecção e qualificação de exsudações oceânicas de hidrocarbonetos com base em sensoriamento remoto no espectro refletido

Natural hydrocarbons seeps are important to indicate the presence of a petroleum system in the subsurface. In the Gulf of Mexico the seepage phenomena are common and have been responsible for the discoveries of important oil fields in recent decades, most of them assisted by remote sensing techniques. This project aims to evaluate methods for the detection and classification of oil slicks that were produced by marine seeps, through the utilization of multispectral images of the Advanced Spaceborne Thermal Emission and Reflection Radiometer sensor (ASTER). Several tests have been conducted as part of this research to achieve this purpose. Using the data related to the acquisition geometry of ASTER images was possible to predict the appearance of the oil. The test of three supervised classification algorithms demonstrated the possibility to detect oil slicks on the ocean surface. Moreover, a predictive model was made based on spectral features from laboratory and ASTER images to estimate the API gravity values from oil seeps in the ASTER images. The results obtained using remote sensing was similar to those recorded nearby the oil fields in this region of the Gulf of Mexico.Pages: 1509-151

Espectroscopia de reflectância aplicada à detecção de exsudações: inferências a partir de dados ASTER e verificações de campo

Hydrocarbon (HC) seepages interact with the stratigraphic column and promote a series of distinguishing features that can be detected via remote sensing, such as the increase of kaolinite and bleaching of ferric-iron-rich rocks and soils. Considering the importance of seepages for HC exploration, this research aims the remote detection of this phenomena in the Itapecuru Formation of the Parnaíba basin, as well as its field validation. ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer sensor) data were processed for extraction of minerals of interest and spectral measurements were performed in the field and under laboratory conditions. Results were cross-referenced with soil gasometry analysis, which is used here as ground truth. The work demonstrated that both field and laboratory measurements are suitable to highlight features predicted in seepages. The relative increase of kaolinite shows a good correlation with sites rich in gaseous HCs. Therefore, it can be used as an indirect feature for remote seepage detection at the study area. Conversely, more comprehensive research is necessary to understand the relation between seepages and bleaching. Remote sensing detection of seepages in tropical areas with anthropic interference, as is the case here, is challenging and requires detailed studies strongly based on field checking, so that similar results as those accomplished in this work, can be closely reproduced.Pages: 3712-371