Interpretation of seismic multiattributes using a neural network
Michelle Chaves Kuroda, Alexandre Campane Vidal, Ancilla Maria Almeida de Carvalho
ARTIGO
Inglês
Agradecimentos: The authors acknowledge the financial support of Petrobras, and also thank ANP – National Petroleum Agency for providing the data
Abstract: Geological bodies in 2D seismic section are characterized by differences from the surrounding response. These differences can be highlighted by attributes that are sensitive to the desired feature. In this paper the attributes were carefully chosen and trained by a neural network. These...
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Abstract: Geological bodies in 2D seismic section are characterized by differences from the surrounding response. These differences can be highlighted by attributes that are sensitive to the desired feature. In this paper the attributes were carefully chosen and trained by a neural network. These seismic attributes are transformed into a new attribute that allows a different view of the seismic lines. The database used for this study is a 2D seismic line of the Taubaté Basin, São Paulo State, Brazil. Two seismic sets were analyzed and the results bring out the horizons and the boundary between seismic units, which helps a better understanding of the evolution of the Taubaté sedimentary basin
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Interpretation of seismic multiattributes using a neural network
Michelle Chaves Kuroda, Alexandre Campane Vidal, Ancilla Maria Almeida de Carvalho
Interpretation of seismic multiattributes using a neural network
Michelle Chaves Kuroda, Alexandre Campane Vidal, Ancilla Maria Almeida de Carvalho
Fontes
Journal of applied geophysics (Fonte avulsa) |