Reproducible material for Guided Diffusion Posterior Sampling for Elastic Parameter Inversion with Angle-Stack Seismic Data - Dixit A., Brandolin F., Alkhalifah T.
This repository is organized as follows:
- 📂 diffavoinv: python library containing routines for DPS based AVO Inversion and editing;
- 📂 asset: folder containing logo;
- 📂 data: folder containing test data of 2D Otway synthetic data and Poseidon Field angle-stack seismic (note: right now contains only the test data, no trained weight and/or datasets, because of GitHub memory issues)
- 📂 notebooks: set of jupyter notebooks reproducing the experiments in the paper (see below for more details);
- 📂 scripts: set of python scripts used to run multiple experiments ...
The following notebooks are provided:
- 📙
AVOUQ_synth_otway.ipynb: notebook performing uncertaninty quantification on synthetic otway model; - 📙
avo_inversion_guided_ddim.ipynb: notebook performing DPS based AVO Inversion and editing; - 📙
dataset_avo.ipynb: notebook performing training data and unconditional samples visulization; - 📙
field_avo_inversion_guided_ddim_UQ.ipynb: notebook performing DPS based avo inversion on field data and uncertanity quantification;
Note: to run the notebook, please download the trained model weights from the checkpoints folder
To ensure reproducibility of the results, we suggest using the environment.yml file when creating an environment.
Simply run:
./install_env.sh
It will take some time, if at the end you see the word Done! on your terminal you are ready to go.
Remember to always activate the environment by typing:
conda activate diffseisavo
After that you can simply install your package:
pip install .
or in developer mode
pip install -e .
Disclaimer: All experiments have been carried on a Intel(R) Xeon(R) CPU @ 2.10GHz equipped with a single NVIDIA GEForce RTX 3090 GPU. Different environment configurations may be required for different combinations of workstation and GPU.
DW0127 - Dixit A., Brandolin F., Alkhalifah T. (2026) Guided Diffusion Posterior Sampling for Elastic Parameter Inversion with Angle-Stack Seismic Data.
