Import/Export LAS files to/from GEOH5 format for geoscientific data
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Updated
Apr 17, 2026 - Python
Import/Export LAS files to/from GEOH5 format for geoscientific data
Meta-package that groups together packages for interoperability between GEOH5 and other file formats
MCP server exposing petroleum engineering data and tools to LLMs
TotalDepth is capable of processing and analysing petrophysical wireline logs.
JavaScript for converting well-log standard .las file format to json format
Per-well dossier manifest generator for the Equinor Volve dataset, producing structured well-centric artifact indexes with de-duplication and cross-well reference detection.
d3.js v5 visualization of well logs
Volve dataset index Content coverage analysis for the public Equinor Volve dataset, derived from a validated metadata index.
Petroleum-engineer-friendly coverage audit of the Equinor Volve dataset from a frozen filesystem catalog.
Python library for reading and writing well data using Log ASCII Standard (LAS) files
Official code snippets of paper "Spectral graph convolution networks for microbialite lithology identification based on conventional well logs"
Official code snippets of paper "Spatial–Stratigraphic Information and Dynamic Range Attention Assist Well-Logging Lithological Interpretation"
Official code snippets for "Spatial–Stratigraphic Information and Dynamic Range Attention Assist Well-Logging Lithological Interpretation"
Professional Well Log Analysis & Visualization Tool
LogSense is a machine learning platform that applies foundation model architectures to geophysical well log analysis. It enables pre-training on unlabeled sequential log data using masked autoencoders, followed by fine-tuning for specific downstream tasks.
Learning whilst drilling through real-time, near-bit prediction ahead of the drill-bit, using offset well log data.
This is my personal practice repository where I showcase the problems I have tried to solve using my Python skills.
Python package to read well logs and model geomechanical properties.
AI-assisted well-log interpreter: upload LAS → compute petrophysics, cross-plot, cluster, and auto-interpret net pay (Streamlit).
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