Deep-learning seismic facies on state-of-the-art CNN architectures

Abstract

We explore propagation of seismic interpretation by deep learning in stacked 2D sections. We show the application of state-of-the-art image classification algorithms on seismic data. These algorithms were trained on big labeled photograph databases. We use transfer learning to benefit from pre-trained networks and evaluate their performance on seismic data.

Presentation Date: Wednesday, October 17, 2018

Start Time: 8:30:00 AM

Location: 204B (Anaheim Convention Center)

Presentation Type: Oral