Popular GitHub Repositories for Seismic

Deep Learning for Seismic Imaging and Interpretation

Official Implementation of "Stochastic seismic waveform inversion using generative adversarial networks as a geological prior"

Interpolation of seismic data through Deep Priors

FWIGAN: Full-Waveform Inversion with Deep Adversarial Learning

Our project revolutionizes seismic image interpretation with advanced deep learning, using Convolutional Neural Networks (CNNs) to automate workflows and improve accuracy in subsurface exploration. Trained on synthetic seismic data from coal mines, our algorithm excels in identifying faults, folds, and flat layers.

Novel PINN framework for simultaneous seismic data interpolation and local slope estimation

Reproducible material for Generative Diffusion Model for Seismic Imaging Improvement of Sparsely Acquired Data and Uncertainty Quantification

Open Seismic is an open-source toolbox for conducting inference on seismic data. We use OpenVINO while inference.

? This repository contains unsupervised analysis of seismic data using Kmeans and Deep Embedded Clustering to identify different types of signals recorded in Seismograph ??

Next-generation non-linear and collapse prediction models for short to long period systems via machine learning methods

Salt Body Segmentation in Seismic Imaging using Semi-Supervised Learning

The logistic regression, K-nearest neighbors, support vector machine, and artificial neural network (ANN) algorithms were developed to automatically classify seismic observations.

Collection of parallel codes for (RTM) seismic processing, techniques. The codes utilize various libraries to facilitate experimentation and comparison of different techniques.

This repository contains the official implementation of the paper "Seismic Source Recovery Algorithm via Internal Learning in the Cross-spread Domain" published by European Association of Geoscientists & Engineers

Controllable Synthetic Seismic Waveform Generation framework - ConSeisGen

Trabalho dau aula 2 da disciplina Mlops do MBA Data Science.

Analysis of Seismic data of Mars and Inferences and about the seismic wave properties and the Interior structure of Mars using Signal processing, machine learning and Physics informed neural networks.