author = "Ibanez, Delano M. and Almeida Filho, Raimundo and Miranda, 
                         Fernando Pelon de",
          affiliation = "Petrobras Research and Development Center (CENPES), Cidade 
                         Universit{\'a}ria, Ilha do Fund{\~a}o, Av. Hor{\'a}cio Macedo, 
                         950, Rio de Janeiro, Brazil and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and Petrobras Research and Development Center 
                         (CENPES), Cidade Universit{\'a}ria, Ilha do Fund{\~a}o, Av. 
                         Hor{\'a}cio Macedo, 950, Rio de Janeiro, Brazil",
                title = "Analysis of SRTM data as an aid to hydrocarbon exploration in a 
                         frontier area of the Amazonas Sedimentary Basin, northern Brazil",
              journal = "Marine and Petroleum Geology",
                 year = "2016",
               volume = "73",
                pages = "528--538",
                month = "May",
             keywords = ": Environmental impact, Geological surveys, Hydrocarbons, Image 
                         reconstruction, Remote sensing, Sedimentology, Seismic 
                         prospecting, Settling tanks, Surveying, Tracking radar, Amazonas 
                         basin, Digital elevation model, Hydrocarbon exploration, 
                         Morphostructural analysis, Petroleum exploration, Shuttle radar 
                         topography mission, SRTM DEM, Topographic information, Petroleum 
                         prospecting, digital elevation model, drainage network, 
                         hydrocarbon exploration, morphostructure, remote sensing, 
                         sedimentary basin, Shuttle Radar Topography Mission, Amazonas 
                         [Brazil], Brazil FUNDING DETAILS: JAXA, Japan Aerospace 
                         Exploration Agency.",
             abstract = "The Shuttle Radar Topography Mission (SRTM) provided an 
                         unprecedented source of space-borne topographic information that 
                         has shown to be of particular interest for studies in densely 
                         vegetated tropical areas, such as Central Amazonia. The digital 
                         elevation models produced in that region show subtle details of 
                         the terrain that usually appear blurred in conventional remote 
                         sensing images. Interpretation of an SRTM-derived drainage network 
                         and geomorphometric features revealed several drainage anomalies, 
                         which are possibly the surface expression of buried 
                         morphostructural features. Integration with geological and 
                         geophysical ancillary data strongly suggested that interpreted 
                         features constitute potential structural sites for hydrocarbon 
                         exploration. However, due to their inferred nature, the structures 
                         herein identified are not by themselves a justification for 
                         drilling. However, they do provide information for planning 
                         seismic surveys, thus reducing costs of the exploration campaigns, 
                         as well as minimizing potential environmental impacts of such an 
                         enterprise in areas of tropical rain forests. Despite the 
                         relatively small size of the study area, it is expected that 
                         procedures presented in this paper can be successfully applied 
                         throughout the approximately 1,000,000 km2 of sedimentary basins 
                         in the Brazilian Amazonian region.",
                  doi = "10.1016/j.marpetgeo.2016.03.024",
                  url = "http://dx.doi.org/10.1016/j.marpetgeo.2016.03.024",
                 issn = "0264-8172",
             language = "en",
           targetfile = "ibanez_analysis.pdf",
        urlaccessdate = "25 nov. 2020"