SuihongSong

GeoModeling_GANSim-2D_Condition_to_Probability_Maps_and_Others

The second repository (GeoModeling_Conditional_ProGAN) is used for conditioning to well data and global features. This repository is for conditioning to geophysics-interpreted probability maps alone and together with well data and global features.

GeoModeling_GANSim-2D_Condition_to_Well_Facies_and_Global_Features

Directly Conditional Facies Modeling Using an Improved Progressive Growing of Generative Adversarial Networks (GANs)

GeoModeling_Unconditional_ProGAN

Unconditional Geomodeling related work (codes, data, and results)

GeoModeling_GANSim-3D_For_large_arbitrary_reservoirs

GANSim3D_v2

An updated version of original GANSim3D codes, with easier set up of training data dimensions, conditioning choices, etc.

Physics-informed_multi-grid_neural_operator

Generative-geomodelling-Deep-Learning-vs.-Geostatistics

Materials related to the paper "Generative geomodelling: Deep Learning vs. Geostatistics" by Suihong Song

ImageQuilting.jl

Fast image quilting simulation solver for the GeoStats.jl framework

LAMGeo-Initiative

Large generative AI Model for Geomodelling

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

RockPhysicsPy

meanderpy

Simple model of meander migration

progressive_growing_of_gans

Progressive Growing of GANs for Improved Quality, Stability, and Variation

stylegan

StyleGAN - Official TensorFlow Implementation

WassersteinGANTest_1D

Reproduction test of 1d Gaussian, uniform, and discrete distributions based on Wasserstein GAN