🌍 30 AI-powered geoscience skills for Claude Code, Cursor & GitHub Copilot. Seismic, well logs, 3D modelling, inversion, geostatistics, spatial regression, NetCDF, and more.
TotalDepth is capable of processing and analysing petrophysical wireline logs.
An open-source Python package for writing DLIS files.
Machine learning project for lithology classification from well log data using XGBoost. Predicts Sandstone, Shale, and Limestone from petrophysical logs.
Engineering-grade platform for well log intelligence: Featuring automated LAS parsing, interactive curve visualization, and context-aware AI petrophysical interpretation.
XGBoost-based sonic log prediction from conventional well logs in the Sergipe-Alagoas Basin, Brazil.
Automatic vug detection and quantification in ultrasonic borehole image logs, read directly from DLIS. All thresholds in millimetres and decibels, so a parameter set carries between wells.
Pore pressure prediction in well 15/9-F-12 (Volve field) using machine learning regression models.
This repository contains various versions of the 'Well Log Viewer". These can be used to generate well logs for various types of data storage formats and strictly structural based record of the data in a log file.
Parse CWLS LAS 2.0 Files in Rust
Cement Bond Log (CBL) Interpreter: A browser-based, zero-dependency tool for acoustic cement evaluation of oil & gas wells.
WELLA is a well log interpretation system. It imports LAS files and opens WLA (WELLA’s native format), supports log displays, cross-plots, editable formulas, and map-based well location viewing.
It includes a collection of modules for petrophysical analysis, along with tools for data streaming and interactive visualization, with a primary focus on petrophysical workflows.
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