Carlos Henrique Beisl

Analysis of RADARSAT-1 data for offshore monitoring activities in the Cantarell Complex, Gulf of Mexico, using the unsupervised semivariogram textural classifier (USTC)

Understanding the temporal dynamics and spatial distribution of natural seepage phenomena in the Gulf of Mexico is fundamental for the definition of proper environmental management practices in this often cloud-covered region. RADARSAT-1 images analyzed in this paper were acquired using the wide 1 and wide 2 (W1, W2) and ScanSAR narrow 1 (SCN1) beam modes. Image processing was carried out using the unsupervised semivariogram textural classifier (USTC). In combination with RADARSAT-1 satellite images, and essential ancillary data, this technology enhances the detection of seepage slicks on the ocean surface based on radar texture. USTC classification of RADARSAT-1 data provided systematic evidence from space of the presence of prolific, present-day petroleum generation and migration in the Cantarell Complex of oil fields.

Operational applications of RADARSAT-1 for the monitoring of natural oil seeps in the South Gulf of Mexico

The origin of the oil activity in Campeche Sound is closely related to the activity of the natural oil seeps. At the moment, the operational areas with greater production in the Cantarell field from PEMEX Exploration and Production (PEP), coincide with the activity of the most important seep in the south of the Gulf of Mexico. With the intention of establishing the origin and magnitude of the hydrocarbon contributions of the natural seeps in this area, the Northeast Marine Region (RMNE) of PEP, with the support of the Subdivision of Technology and Development (STDP) of PEP and the Corporative Unit of Geographic Information Systems (SICORI) developed during the 2000-2001 with RADARSAT International and RADARSAT Resource Center in Brazil a progressive application of the RADARSAT-1 satellite to evaluate oil seep potentiality in detection and measurement, being allowed to establish a proven method for the monitoring of oil seep behavior. The methodology is applied in a continuous way from 2002 and includes a regional criterion for the selection of images, basic and advanced digital analysis utilizing the Unsupervised Semivariogram Textural Classifier (USTC), and meteo-oceanographic calibration. The methodology also correlates geologic and environmental information. The results shown activity of the Cantarell seep in 79.5% of the 83 images analyzed during 2000-2002. Area coverage of Cantarell seep from 66 images ranks between 0.04 to 207.4 km2, with an average area of 32 km2.RADARSAT-1 analysis identified that the main hydrocarbon contribution, in area as well as frequency for South Gulf of Mexico, comes from the natural oil seeps, particularly from the Cantarell field. This project also demonstrates the viability of the integration of disciplinary groups within PEMEX for the development of new technologies with multiple applications that allow the optimization of resources and enhance the availability of environmental tools.

RADARSAT-1 images in support of petroleum exploration: the offshore Amazon River mouth example

RADARSAT-1 images were used as an attempt to identify seepage slicks in the Foz do Amazonas Basin, one of the most promising oil and gas exploration frontiers in the Brazilian equatorial margin, a region that is cloud-covered for most of the year. An unsupervised semivariogram textural classifier algorithm was used to enhance areas of smooth texture and low radar backscatter, indicative of these seepage slick targets. Complementary information related to sea surface temperature, cloud top temperature, wind velocity, and modelling for the tidal regime (all obtained as close as possible to the RADARSAT-1 acquisition) was used to support image interpretation and to exclude false targets also characterized by low radar backscatter (e.g., local upwelling, heavy rain cells). Twenty-one target areas were interpreted as seepage slicks. Considering the influence of the oceanographic and environmental conditions on drifting of the interpreted seepage slicks, they were spatially compared with available geological information, including seismically derived structural and isopach maps, and bathymetric data. Most of the interpreted seepage slicks occur in an extensional structural domain of growth faults. These structures are related to Cenozoic gravity tectonics that result from tensional stress in the continental slope due to the huge load of fluvial sediments transported by the Amazon River. Together with previously discovered subcommercial shallow water oil accumulations, the remote detection of seepage slicks is additional evidence of present-day generation and migration phenomena. The results indicate that the use of a remote, swift method to identify offshore natural oil seepage related to active petroleum systems may constitute a well-accepted approach to support exploration in frontier areas like the Foz do Amazonas Basin.

Use of genetic algorithm to identify the source point of seepage slick clusters interpreted from Radarsat-1 images in the Gulf of Mexico

A large multitemporal set of RADARSAT-1 ScanSAR Narrow 1 images obtained in offshore regions of the Gulf of Mexico enabled the identification of a seepage slick cluster, which is considered to share a common geologic origin. The existence of seepage slick clusters is a positive indicator of present-day hydrocarbon generation and migration. Therefore, their correct location reduces the risk of acquiring piston cores with oil at the sea floor for further geochemical studies. A cluster is interpreted as a group of seepage slick polygons which share the same source point in geographic space. The source point can be tentatively defined as the intersection of overlaying polygons or as the intersection of the forward prolongation of closely spaced and converging polygons. The present study aims to identify quantitatively the origin of a seepage slick cluster at the sea surface using a genetic algorithms (GA). The model employ the Euclidian or the Mahalanobis distance function in order to determine the minimum distance among points within one seepage slick cluster and a population of points randomly generated. We used points in UTM coordinates system generated within a grid cell (x,y) of fifty meters defined in the seepage slick polygons that constitute a cluster In addition, one hundred points are generated randomly as the initial population. The fitness function provides the 10 best ranked points in UTM coordinates system that represent the candidates source point of the seepage slick cluster. The best source point identified using GA (considering both the Euclidian and Mahalanobis distance functions) coincided with a salt dome and fault seismically identified at the sea floor. The methodology have been tested elsewhere in the Gulf of Mexico, in order to identify with enhanced precision possible source points of seepage slick clusters detected using RADARSAT-1 images

Assessment of environmental sensitivity index of flooding areas in western Amazonia using fuzzy logic in the dual season GRFM JERS-1 SAR image mosaics

This study focuses on improving information about oil spill environmental sensitivity in Western Amazonia, Brazil, using a pair of multiseasonal (1995 low flood to 1996 - high flood) GRFM JERS-1 SAR mosaics. Fuzzy analysis is carried out to extract information about landscape modifications within half hydrological cycle. The oil spill hazard information derived from JERS-1 SAR data is straightforward to interpret and constitutes a representation of the original Environmental Sensitivity Index (ESI) product conceived by PETROBRAS.

Environmental sensitivity mapping for oil spill in the Amazon coast using remote sensing and GIS technology

Accidental oil spills may impact sensitive wetlands in the Amazon coast. To generate an environmental sensitivity index (ESI) maps were used: (1) JERS-1 SAR data; (2) RADARSAT-1 data in the W1 beam mode; (3) X-band mosaics of the RADAM Project; and (4) SRTM digital elevation models. As result was identified artificial structures (break water and peers) and nineteen coastal features and environments subject to oil spill. The lowest ESI was assigned to cliffs (ESI 1) and the highest to mangroves and fresh wetland zones (ESI 10a and 10b). An annual monitoring of both natural and human-induced changes would provide invaluable information for the construction of multitemporal sensitivity index maps to oil spills in different seasons and tidal cycles

Environmental sensitivity map of Solimões River basin using SAR images and fuzzy modeling

The Amazon is a region characterized by ecologically complex environments subject to constant and rapid seasonal changes. In Central Amazonia, the seasonal differences in water level caused by flooding changes the landscape and require the production of one sensitivity maps for each season: dry, full ebb and flow. Potential applications of the the Synthetic Aperture Radar (SAR) system on board the JERS-1 satellite for environmental protection in Amazonia include understanding and management of flood hazards. This presents a methodology to compute a multitemporal environmental sensitivity to oil spill map in regional scale, according to the change in flooding conditions. The differences of image patterns from low flow to high flow derives the classes of change, which represent the types of landscape change within half hydrological cycle. A fuzzy system is implemented within a geographic information system (GIS) to map oil-sensitive environments for environmental risk assessment along the Solimões River oil transportation route, Western Amazonia, Brazil.

The mega capture of the negro river, central amazônia, brazil: a novel feature revealed by SRTM data

In Central Amazonia, Brazil, the Solimoes and Negro rivers converge to form the Amazonas, the largest river in the world. Interferometric-derived topographic data, generated during the Shuttle Radar Topography Mission (SRTM), indicate that the present-day lower course of the Negro River is the result of a mega fluvial capture governed by neotectonics. The data indicated that the ancient confluence of the Negro River with the Solimoes River was located where today is the mouth of Manacapuru River, 60 km west of the present location in the vicinity of the city of Manaus.

Exploration assessment in a petroleum frontier area offshore the Amazon River mouth using RADARSAT-1 images

The study discusses the use of RADARSAT-1 images to identify oil seepage in the Foz do Amazonas Basin, an oil and gas exploration frontier in the Brazilian Equatorial margin. An unsupervised semivariogram textural classifier algorithm was used to enhance areas of smooth texture and low radar backscatter, indicative of these targets. Complementary information related to cloud top temperature, wind velocity, and modelling for the tidal regime (all obtained as close as possible to the RADARSAT-1 images acquisition) was used to support image interpretation and to exclude false-targets. Together with previously discovered sub-commercial shallow water oil accumulations, the detection of seepage slicks an additional evidence of oil generation in the study area. Results also indicate that radar remote sensing can be used as a tool to reduce risks in the exploration of frontier areas like the Foz do Amazonas Basin

Operational approach for oil spill monitoring

This paper presents the methodological approach of the oil spill monitoring system that is being put into operation by the National Petroleum Agency (NPA) in Brazil. The methodology is based on integrated analysis of multi-sensor data which includes satellites products, such as, GOES and AVHRR Sea Surface Temperature (SST), SeaWiFs chlorophyll concentration, QuikScat near sea surface wind field, GOES and AVHRR convective rain areas, and Synthetic Aperture RADAR (SAR) data from RADARSAT-1 satellite. The methodology is implemented by means of a system composed by four subsystems called, data reception (SAR, GOES, NOAA and QuikScat), Integrator, hydrodynamic model and database. The methodology was applied to the accidental oil spill caused by PETROBRAS oil rig P-36. A RADARSAT-1 image was acquired during accident period at 21:07 (GMT) on 22nd of March 2001 and used. The results are presented and discussed.