Reproducible material for A self-supervised learning framework for seismic low-frequency extrapolation
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Updated
Jul 15, 2024 - Python
Reproducible material for A self-supervised learning framework for seismic low-frequency extrapolation
WISE: full-Waveform variational Inference via Subsurface Extensions
Official repository for the "Learned regularizations for multi-parameter elastic full waveform inversion using diffusion models" paper.
PGNN-FWI: performing physics-guided neural network for FWI
WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction
This repository is for PyFWI, a Python package for seismic FWI and reservoir monitoring (time-lapse FWI)
Seismic Waveform Inversion Toolbox
Radar and DC resistivity 2.5D multi-physics inversion suite. Forward modeling, separate inversions, joint inversions.
Forward code for the P-SV wave equation on a staggered grid, with full waveform inversion interfaces. Finite difference approach according to stress-velocity formulation.
This is an open source program that contains 3D isotropic forward modeling and full waveform inversion.]
Simple frequency domain full-waveform inversion (FWI) regularized by Sobolev space norm
Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.
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