lithofaciesml

Ensemble Learning to Classify Lithofacies in Carbonate Reservoirs

log-curve-prediction-webinar

machine-learning

Machine learning techniques applied to subsurface data.

machine-learning-1

Practicing machine learning (from scratch) with Python 🐍

machine-learning-for-physicists

Code for "Machine Learning for Physicists 2020" lecture series

machine_learning_bootcamp

machinelearningcourse

My graduate level machine learning course, including student machine learning projects.

mineral-exploration-machine-learning

This page lists resources for mineral exploration and machine learning, generally with useful code and examples.

ml-for-beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

ml_well_log

The code describes how unsupervised ML can be applied to well log data for efficient clustering. A part of the well log data is provided.

mlfromscratch

Machine Learning algorithm implementations from scratch.

new-carbonate-characterization-workflow-jupiter-notebook-modules-with-clerke-arab-d-calibration-data

Carbonate Reservoir Characterization workflow using Clerke’s carbonate Arab D Rosetta Stone calibration data to provide for a full pore system characterization with modeled saturations using Thomeer Capillary Pressure parameters for an Arab D complex carbonate reservoir

olutokijohn

Config files for my GitHub profile.

open_petro_elastic

Utility for calculating elastic properties of petroleum fields

peip

MATLAB code for examples and exercises for the 3rd edition of Parameter Estimation and Inverse Problems

petrophysics-python-series

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

practical-seismic-t21-tutorial

T21 tutorial using Volve data

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 ;)

project-combo

This repo is simply a collection of projects and mini-tasks carried out using the Python stack. It is well laid out and easy to surf through. Feel free to look through

pythondataanalysis

Python data repo, jupyter notebook, python scripts and data.

pythonnumericaldemos

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

rock_class_xgboost

Rock facies classification with xgboost and physics-motivated feature augmentation

segy_ml_inversion

segyio-notebooks

Notebooks with examples and demos of segyio

seiscomp3

SeisComP is a seismological software for data acquisition, processing, distribution and interactive analysis.

seismic-facies-analysis-dcae

Unsupervised seismic facies analysis via deep convolutional autoencoders.

seismic-inversion

Seismic inversion

seismic_deep_learning

A couple of python scripts to interpret geological structures from geophysical images using deep learning

seisproc

Some simple and useful seismic processing routines.

spe_naice-reservoir-facies-classification

This study employed formation samples for facies classification using Machine Learning techniques and classified different facies from well logs in seven (7) wells. The log data were trained using supervised machine learning algorithms to predict discrete facies groups. The analysis started with data preparation and examination where various features of the available well data were conditioned.