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Tuesday, October 15 • 11:45am - 12:00pm
Automated Salt Top Interpretation

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The goal of this work is to demonstrate the detection and extraction of salt tops from seismic data via the application of deep learning. Motivations for automated salt top extraction is a growing necessity in the field of petroleum exploration. Synthetic data is used for automatic label generation and training of a convolutional neural network is capable of predict with higher accuracy the salt top in unseen data during the training. Several experiments were performed and evaluated for exploring the effects of changing various parameters during training. The best model produced in this study provides excellent results when is compared with the interpretation.


German Larrazabal

Technology Lab - Geophysics Repsol

Freddy Perozo

Technology Lab – Advance Mathematics Repsol

Pablo Guillen-Rondon

Presenter, University of Houston

Tuesday October 15, 2019 11:45am - 12:00pm CDT
BRC 103

Attendees (1)