This R Notebook project illustrates how Artificial Neural Network can be applied to Reservoir Characterization dataset. It illustrates the relationship between a dependent variable and several independent variables using ANN.

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

PhazeOpt is a set of tools for Reservoir Fluid Characterization.

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.

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.

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.

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

Codes associated with PhD thesis titled "Structural and Shape construction using inverse problems and machine earning techniques"

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.

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.

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

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

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…

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.

Predict Petrophysical Rock Types (PRT) using KNN

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

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