Seismic Interpretation
3 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Seismic Interpretation
Most implemented papers
A Machine Learning Benchmark for Facies Classification
In addition to making the dataset and the code publicly available, this work helps advance research in this area by creating an objective benchmark for comparing the results of different machine learning approaches for facies classification.
Man-recon: manifold learning for reconstruction with deep autoencoder for smart seismic interpretation
Deep learning can extract rich data representations if provided sufficient quantities of labeled training data.
Learning to Decouple and Generate Seismic Random Noise via Invertible Neural Network
Then, by manipulating the latent variable’s partitions encoding high- and low-frequency information, INN can generate quality-controlled fake field data and decouple useful signal and field noise parts from field data in its backward pass.