unclebb31's starred repositories

geospatial-machine-learning

A curated list of resources focused on Machine Learning in Geospatial Data Science.

LoopStructural

LoopStructural is an open-source 3D structural geological modelling library.

Language:PythonLicense:MITStargazers:185Issues:10Issues:72

Basic-Well-Log-Interpretation

Basic Well Log Interpretation with python, pandas, matplotlib

Language:LassoLicense:GPL-3.0Stargazers:133Issues:24Issues:3

spotfire-mods

Spotfire® Mods

Language:TypeScriptLicense:NOASSERTIONStargazers:56Issues:24Issues:68

wellio.js

JavaScript for converting well-log standard .las file format to json format

Language:Jupyter NotebookLicense:MITStargazers:34Issues:9Issues:37

CorePy

Python tools designed to integrate and visualize geological core data

Language:PythonLicense:MITStargazers:25Issues:4Issues:0

enverus-developer-api

Enverus Developer API Python Client

Language:PythonLicense:MITStargazers:19Issues:12Issues:17

pypetrophysics

Library of petrophysical calculations

Language:PythonLicense:Apache-2.0Stargazers:16Issues:2Issues:0

Spotfire-IronPython

IronPython Scripts for TIBCO Spotfire

Language:PythonStargazers:12Issues:2Issues:0
Language:Jupyter NotebookLicense:MITStargazers:10Issues:3Issues:0

Prediction-of-reservoir-properties-using-Neural-Network

With available well logging data, prediction of porosity, water saturation using Deep Learning techniques.

GeostatsPy_Course_2

Course on the GeostatsPy Python geostatistics package covering uncertainty modeling with declustering and simulation.

Language:Jupyter NotebookLicense:MITStargazers:9Issues:4Issues:0

logASCII_viewer

Upload well LAS (log ASCII) files and view the raw logs interactively in streamlit

Modeling-NMR-Derived-T2-Porosity-using-Conventional-Open-Hole-Logs

Machine Learning Modeling of NMR-Derived T2 Porosity using Quad Combo, Wolfcamp and Spraberry Formations, Reagan County Texas

Language:LassoStargazers:9Issues:1Issues:0

spotfire-cheatsheet

Cheatsheet for Spotfire OVER expressions

Language:PythonStargazers:8Issues:2Issues:0

Spotfire-Ironpython

This repository contains only Ironpython scripts that one can use in Tibco Spotfire to make available some basic features.

Language:PythonStargazers:8Issues:1Issues:0

SKLEARN-used-to-predict-Petrophysical-Rock-Types-in-Arab-D-Carbonate

Use of Sklearn to predict Petrophysical Rock Types (PRT) in an Arab D carbonate based on Clerke's Rosetta Stone Calibration data

Language:Jupyter NotebookLicense:MITStargazers:8Issues:2Issues:0

Estimations-of-Mode-of-Pore-Throat-Distribution-using-Tensorflow

Utilized Tensorflow to estimate the Mode of a Pore Throat Distribution based on Carbonate Core Data

Language:LassoLicense:MITStargazers:7Issues:2Issues:0
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Older-Combined_NMR_Conventional_Logs-Shaley-Sand-Analysis-using-PetroGG

Mihai's PetroGG modified to be used with our shaly-sand Gulf Coast NMR data.

Language:Jupyter NotebookLicense:MITStargazers:4Issues:2Issues:0
Language:Jupyter NotebookLicense:NOASSERTIONStargazers:3Issues:7Issues:6

Clastics--Assess-Depth-Interval-from-NMR-log-to-Generate-Thin-Sections-and-Pc-Curves-using-KNN

Assess discrete depth interval to estimate the Petrophysical properties for that interval

Language:Jupyter NotebookStargazers:3Issues:2Issues:0

Utilize-Continuous-Core-Images-to-Calibrate-Borehole-Image-Logs

Take continuous high-resolution digital core images of the reservoir rock and process these images to define sand vs. shale for Borehole Imagelog calibration and Sand Count

GeologicalToolbox

This repository includes python modules for storing and processing geological base data.

Language:PythonLicense:MITStargazers:3Issues:0Issues:0
Language:Jupyter NotebookStargazers:2Issues:2Issues:0

Spotfire_GeoAnalytics_Builder

Snippet to fetch data from TIBCO GeoAnalytics Builder.

Language:RLicense:GPL-3.0Stargazers:1Issues:1Issues:0