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Carlos Henrique Beisl
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Proceedings Papers

Super-giant oil slick cluster identification using artificial intelligence (AI) and machine learning (ML), integrated with 4D inverse modeling and 2D and 3D seismic data, as direct seafloor oil seepage indicators in the ultra-deepwater outboard frontier areas of the presalt province of the Santos Basin, Brazil

Marcio Rocha Mello, Carlos Henrique Beisl, Oswaldo Antunes Pedrosa Junior, Vanessa Bonanno Haliburton, Cleverson Guizan Silva, Luiz Antonio Pierantoni Gamboa, Kenji Motoki, Sidney Luiz de Matos Mello, Zhao Junfeng, Guo Yuan, Manlio Mano
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4093460
https://doi.org/10.1190/image2024-4093460.1
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View Paper titled, Super-giant oil slick cluster identification using artificial intelligence (AI) and machine learning (ML), integrated with 4D inverse modeling and 2D and 3D seismic data, as direct seafloor oil seepage indicators in the ultra-deepwater outboard frontier areas of the presalt province of the Santos Basin, Brazil
Open the PDF for Super-giant oil slick cluster identification using artificial intelligence (AI) and machine learning (ML), integrated with 4D inverse modeling and 2D and 3D seismic data, as direct seafloor oil seepage indicators in the ultra-deepwater outboard frontier areas of the presalt province of the Santos Basin, Brazil in another window
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Proceedings Papers

Geometric Pattern Recognition to Distinguish Natural from Anthropic Oil Slicks in the Brazilian Equatorial Margin

Fernando Pellon de Miranda, Gil Márcio Avelino Silva, Patrícia Carneiro Genovez, Francisco Fábio de Araújo Ponte, Sarah Barrón Torres, Carlos Henrique Beisl, Italo de Oliveira Matias
Paper presented at the Offshore Technology Conference Brasil, October 24–26, 2023
Paper Number: OTC-32783-MS
https://doi.org/10.4043/32783-MS
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View Paper titled, Geometric Pattern Recognition to Distinguish Natural from Anthropic Oil Slicks in the Brazilian Equatorial Margin
Open the PDF for Geometric Pattern Recognition to Distinguish Natural from Anthropic Oil Slicks in the Brazilian Equatorial Margin in another window
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