Tomographic Velocity Images by Artificial Neural Networks
By
Djarfour Noureddine1, Baddari Kamel1, Djeddi Mabrouk2
(1) Université de Boumérdes, Boumérdes, Algeria (2) Université de Boumérdes, Boumérdes, Algeria
In order to obtain velocity image from a borehole
to
borehole
seismic
tomographic experiment, the artificial neurone networks of Elmen type, were
trained to reconstruct the velocity from the traveltime. This type of network
offers an advantage of training simplicity by the Back-propagation conjugate
gradient algorithm. The behavior observed of networks on training data is very
similar to the one observed on test data. The efficiency of these networks is
tested with the complex geologic model, and the results were very encouraging. A
comparison with algorithms ART and SIRT was made, and the superiority of
networks of neurons was noted.
Keywords : neurones networks; training; Elmen; Back-propagation; velocity; tomography; ART; SIRT