Deep Learning for Seismic Imaging and Interpretation

Kaggle | 9th place single model solution for TGS Salt Identification Challenge

Julia Devito inversion.

Teleseismic body wave modeling through stacks of (dipping/anisotropic) layers

An automatic seismology toolset for global P-to-S and S-to-P receiver function imaging

Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.

Julia package to perform Kirchhoff migration and demigration

Seismic inversion

Developing project for shallow seismic structure imaging

Image gather tools

Auto-Correlogram Calculation in seismology

Synthetic demonstration of Eikonal tomography

Derisking geological carbon storage from high-resolution time-lapse seismic to explainable leakage detection

FBD: Multi-channel blind deconvolution with focusing constraints

A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification by Siahkoohi, A., Rizzuti, G., and Herrmann, F.J.

For Southeast Tibet

Shot-profile prestack depth migration algorithm based on a phase-shift plus interpolation (PSPI) wave propagation method.

Modeling, inversion and migration focusing on seismic first-arrivals.

A collection of 3 research note books: inverse problem, sesmic image and mathematical optimization

The importance of transfer learning in seismic modeling and imaging by Siahkoohi, A., Louboutin, M., and Herrmann, F. J.