Discover our reproducible research

These frameworks feature open-source GitHub repositories containing executable examples available as Python scripts or Jupyter notebooks. Click through to explore these tools and seamlessly integrate them into your own work.

Self-supervised surface-related multiple suppression with multidimensional convolution

https://github.com/DeepWave-KAUST/SSL-Multiples-Attenuation-pub

Guided Diffusion PosteriorSampling for Elastic ParameterInversion with Angle-Stack SeismicData

https://github.com/DeepWave-KAUST/dpsAVAinversion-pub

SiameseFit: Latent Seismic Data Comparison for Enhanced Full Waveform Inversion and Cycle Skipping Mitigation

https://github.com/DeepWave-KAUST/SiameseFit-pub

Self-supervised Seismic Resolution Enhancement

https://github.com/DeepWave-KAUST/SSL-Resolution-Enhancement

Reproducible material for Annealed Stein Variational Gradient Descent for Improved Uncertainty Estimation in Full-Waveform Inversion

https://github.com/DeepWave-KAUST/AnnealedSVGD_FWI

Deep Learning-based 3D Microseismic Event Direct Location Using Simultaneous Surface and Borehole Data

https://github.com/DeepWave-KAUST/Microseismic_with_SF_BH

Regularization strategies for Seis2Rock-based petrophysical inversion of pre-stack seismic data

https://github.com/DeepWave-KAUST/Regularized_Seis2Rock

Wavenumber-aware diffusion sampling to regularize multi-parameter elastic full waveform inversion

https://github.com/DeepWave-KAUST/ilvrefwi

Multiple Wavefield Solutions in Physics-Informed Neural Networks using Latent Representation

https://github.com/DeepWave-KAUST/latentpinn

Noise attenuation in distributed acoustic sensing data using a guided unsupervised deep learning network

https://github.com/DeepWave-KAUST/DLDAS_Denoising-pub

A self-supervised learning framework for seismic low-frequency extrapolation

https://github.com/DeepWave-KAUST/SSL-Lowfrequency-extrapolation

Seis2Rock: A Data-Driven Approach to Direct Petrophysical Inversion of Pre-Stack Seismic Data

https://github.com/DeepWave-KAUST/Seis2Rock

Learned regularizations for elastic full waveform inversion using diffusion models

https://github.com/DeepWave-KAUST/diffefwi

Robust Full Waveform Inversion with deep Hessian deblurring

https://github.com/DeepWave-KAUST/DeepFWIHessian

IntraSeismic: Using Coordinate-Based Learning for Seismic Inversion

https://github.com/DeepWave-KAUST/IntraSeismic

Meta-Processing: A robust framework for multi-tasks seismic processing

https://github.com/DeepWave-KAUST/Meta-Processing

PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks

https://github.com/DeepWave-KAUST/PINNslope

GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks

https://github.com/DeepWave-KAUST/PINNgabor