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algotom

Data processing algorithms for tomography: https://algotom.readthedocs.io

blueing-reflectivity-integration-bri-

Seismic Spectral Enhancement Technique

core_features

curvelops

Python wrapper for CurveLab's 2D and 3D curvelet transforms

deep_learning_101

jupyter notebook for python, numpy, pytorch, cnn

fracture-trace-point-analysis

Fracture Trace Point analysis

geone

DeeSse interface, utilities and examples

geoslicer

gissom

Self-organizing maps (SOM) and k-means clustering for analyzing geospatial data.

glcm

Gray-level Co-occurence Matrix

grev-porousmedia

This repository implements the 3D GLSZM

inpaintingnmf

This is the accompanying repository for the article Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization authored by Ondřej Mokrý, Paul Magron, Thomas Oberlin and Cédric Févotte, submitted to Elsevier Signal Processing.

karstseg3d

Karst segmentation in 3D seismic images

mamaskitchen

A demo repository for learning more about GitHub and Git in Equinor

ml-pitfalls

Pitfalls in machine learning

mlgeo

Exploration of machine learning in geoscience use cases

nmr_log_visualization

Simple example to visualize wellbore NMR T2_distribution

petrophysics-python-series

A series of Jupyter notebooks showing how to load well log and petrophysical data in python.

petrophysics-with-python

Python scripts to visualize LAS well log data

segmenteverygrain

A SAM-based model for instance segmentation of images of grains

seismic-data-interactive-visualization-2d-3d

2D/3D post-stack seismic amplitude/reservoir property in sgy/segy format

stratigraph

A set of tools for visualizing stratigraphic models

style-transfer-downscaling-paper

ST method applied to CT images

upen2dtool

Upen2DTool is a 2-dimensional (2D) inversion MATLAB® script package developed at the University of Bologna (Bologna, Italy), that processes 2D Nuclear Magnetic Resonance relaxometry data. Upen2DTool applies the Upen2D algorithm, the 2D extension of the Uniform PENalty principle, to compute locally adapted regularization parameters and approximate solutions by solving a sequence of regularized least squares problems. The software is written in Matlab® 2018b script language and consists of a main folder ("Upen2DTool") containing the script files and two sub-folders: one with the data files ("DATA") and the other one ("output_files") with the output files creates by a run of the software. It comes also with a compiled version for windows (the executable version "Upen2DTool_Exe_ver.1.0" and the runtime MatLab® library are both available in the download area).