A petrophysics python package for geoscience python computing of conventional and unconventional formation evaluation. Reads las files and creates a pandas dataframe of the log data. Includes a basic petrophysical workflow and a simple log viewer based on XML templates.

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

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.

Notebooks on production optimisation and history matching

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.

Estimate Core-based Permeability from NMR well log data

Geological Reservoir Virtualization

We have used Mihai's PetroGG and modified the program to be used with our shaley-sand Gulf Coast data. In this version we are using Vshale and not Vclay, and we have added Waxman-Smits and Dual-Water saturation models appropriate for these data.

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

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

Predict Petrophysical Rock Types (PRT) using 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.

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.

Descriptive statistics about BHI fractures; Critically stressed faults

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

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.

We have used a novel supervised learning, Cluster Classify Regress algorithm (CCR) for approximating 2 phase flow in a synthetic toy reservoir with very high accuracy. We compared the performance of CCR with a single DNN architecture in recovering the evolving pressure and saturation fields. The method consists of creating different surrogate ma…

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.

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

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