vkazei Goto Github PK

asofi3d

Anisotropic seismic modeling in time domain.

autokeras

Accessible AutoML for deep learning.

bruges

Geophysics library with various helpful functions

cuda_fdtd_2d_acoustic_wave_propagation

Acoustic wave propagation in 2D domain using CUDA, O(2,8). Solve second order wave equation in time domain using finite-differences.

deeplogs

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

deepwave

Wave propagation modules for PyTorch.

denise-black-edition

2D time-domain isotropic (visco)elastic FD modeling and full waveform inversion (FWI) code for P/SV-waves

fastfwi

Simple frequency domain full-waveform inversion (FWI) regularized by Sobolev space norm

fasthelmholtz

Helmholtz solver with 2nd order Clayton-Enquist boundary conditions + compared to analytics

keras

Deep Learning for humans

lbfgsb

L-BFGS-B, converted from Fortran to C, with Matlab wrapper

pysit

rsfsrc

Main Madagascar source

sava

3D seismic modelling, FWI and RTM code for wave propagation in isotropic (visco)-acoustic/elastic and anisotropic orthorhombic/triclinic elastic media

scatteringatlas

Scattering of plane body waves on arbitrary anisotropic elastic perturbations mapped to wavenumber domain. Kazei & Alkhalifah, 2019 JGR

segyio

Fast Python library for SEGY files.

segyio-notebooks

Notebooks with examples and demos of segyio

seismic-imaging-with-sgld

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

theory-of-seismic-waves-ii

Course material for the lecture "Theory of seismic waves II" (SS 2018) @ CAU Kiel

vkazei.github.io

My personal website

vsp2ssp

Converts VSP (receivers in a well) seismic data to SSP (virtual receivers on the surface) by correlation.

waveprop_in_matlab

Single-file codes in MATLAB for acoustic and elastic wave propagation in time domain using finite-differences(FDTD). As simple formulation and implementation as possible.