A knowledge-based approach of seismic interpretation : horizon and dip-fault detection by means of cognitive vision.

Philippe Verney (1) , Jean-Francois Rainaud (1) , Michel Perrin (2) , Monique Thonnat (3)

1 IFPEN - IFP Energies nouvelles
2 École des Mines de Paris
3 PULSAR - Perception Understanding Learning Systems for Activity Recognition

The present paper presents preliminary results obtained through a new seismic interpretation methodology based on cognitive vision. This methodology consists in associating to the geological objects to be detected, horizons or faults, visual characteristics that allow to easily identify and correlate them on seismic images. The results presented show that the method is performing well and is easy to be integrated in Shared Earth Modeling workflows.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Géophysique [physics.geo-ph]; Géophysique [physics.geo-ph]; Milieux et Changements globaux; Intelligence artificielle [cs.AI]

Philippe Verney, Jean-Francois Rainaud, Michel Perrin, Monique Thonnat. A knowledge-based approach of seismic interpretation : horizon and dip-fault detection by means of cognitive vision.. SEG, International Exposition and 78th Annual Meeting, Nov 2008, Las Vegas, United States. ⟨inria-00507016⟩