Deep Learning for Seismic Imaging and Interpretation
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Updated
Sep 18, 2020 - Python
Deep Learning for Seismic Imaging and Interpretation
Kaggle | 9th place single model solution for TGS Salt Identification Challenge
Julia Devito inversion.
Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.
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
Auto-Correlogram Calculation in seismology
Julia package to perform Kirchhoff migration and demigration
Seismic inversion
Developing project for shallow seismic structure imaging
Synthetic demonstration of Eikonal tomography
FBD: Multi-channel blind deconvolution with focusing constraints
A collection of 3 research note books: inverse problem, sesmic image and mathematical optimization
For Southeast Tibet
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification by Siahkoohi, A., Rizzuti, G., and Herrmann, F.J.
Derisking geological carbon storage from high-resolution time-lapse seismic to explainable leakage detection
Software in support of Gravimeters able to detect the vector tidal acceleration of the sun and moon
Modeling, inversion and migration focusing on seismic first-arrivals.
Modeling, inversion and migration focusing on seismic first-arrivals.
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