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
Derisking geological carbon storage from high-resolution time-lapse seismic to explainable leakage detection
Synthetic demonstration of Eikonal tomography
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.
A collection of 3 research note books: inverse problem, sesmic image and mathematical optimization
Modeling, inversion and migration focusing on seismic first-arrivals.
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