A comprehensive Open Source repository for Petrophysics, providing tools, scripts, and resources for analyzing subsurface data. Ideal for geoscientists, engineers, and researchers working with porosity, permeability, and other petrophysical properties. Join us in advancing the science of subsurface exploration and reservoir characterization.

In this repository we provide the python code used to Closure correct and model HPMI data employing the Thomeer hyperbola for up to two pore systems.

Notebooks on production optimisation and history matching

Petrophysic is a Python library developed to assist in the processing of Nuclear Magnetic Resonance (NMR) data, obtaining parameters such as porosity, T2 components, and permeability, as well as providing tools for data visualization. This project is part of a postgraduate work and aims to provide efficient tools for relaxation data analysis.

This project implements a method to balance the injection rate between multiple injectors in a CCS project in aquifers.

We have used the new hierarchical carbonate reservoir benchmarking case study created by Costa Gomes J, Geiger S, Arnold D to be used for reservoir characterization, uncertainty quantification and history matching.

This is some very simple python code to view thin sections from a porosity vs. permeability cross plot using python's Altair and Pane

Geological Reservoir Virtualization

This project contains machine learning solution to automate reservoir quality prediction process. It's our team submission when joining hackathon held by Schlumberger.

We are using Altair to Select Samples from a Poro-Perm Cross Plot and the respective Pc Curves or other data are then shown for the selected samples

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

Estimate Core-based Permeability from NMR well log data

Predict Petrophysical Rock Types (PRT) using KNN

Generate a Representative Thin Sections and Capillary Pressure Curves from any poro-perm combination using normalized core data with kNN backed by the Rosetta Stone Arab D Carbonate core database as calibration data.

Calculate a Chart Book type of Neutron Density log analysis Porosity using Python's KNN

The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG Technical Program Expanded Abstracts, 2019.

Python script that conducts Reservoir History matching using the ES-MDA method

Descriptive statistics about BHI fractures; Critically stressed faults

The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG Technical Program Expanded Abstracts, 2019.

PhazeOpt is a set of tools for Reservoir Fluid Characterization.