Heterogeneous geobodies retrieval in seismic imagesPP

Geological bodies of various kinds may be found in the underground. Automatic retrieval of such objects in seismic images would be a rapid, objective help for interpreters. As shown in our application on real data, our methodology allows to retrieve heterogeneous objects. Texture characterization and a two-stage segmentation first produce object-presence probability images; then, object filtering according to predefined criteria is applied to postprocess the images, yielding heterogeneous geobodies extension and characterization.

This is poster number 48 in Poster Session

Pauline Le Bouteiller (Université Pierre et Marie Curie)
Jean Charléty (IFP Energies Nouvelles)
Florence Delprat-Jannaud (IFP Energies Nouvelles)
Christian Gorini (Université Pierre et Marie Curie)
Didier Granjeon (IFP Energies Nouvelles)
image segmentation, machine learning