Machine learning framework for reservoir simulation

Educational Vibration programs. Intended for undergraduate and early graduate students.

FlowNet - Data-Driven Reservoir Predictions

Capacitance resistance models for waterflood connectivity

Time series forecasting (TSF) is the task of predicting future values of a given sequence using historical data. Recently, this task has attracted the attention of researchers in the area of machine learning to address the limitations of traditional forecasting methods, which are time-consuming and full of complexity. With the increasing availability of extensive amounts of historical data along with the need of performing accurate production forecasting, particularly a powerful forecasting technique infers the stochastic dependency between past and future values is highly needed. In this research, we applied machine learning approach capable to address the limitations of traditional forecasting approaches and show accurate predictions and showed comparison of different machine learning models. For evaluation purpose, a case study from the petroleum industry domain is carried out using the production data of an actual gas field of Bangladesh. Toward a fair evaluation, the performance of the models were evaluated by measuring the goodness of fit through the coefficient of determination (R2 ) and Root Mean Square Error (RMSE), Mean Squared Error (MSE) , Mean Absolute Error(MAE) and model Accuracy

R package for Arps decline curve analysis.

Gas compressibility z-factor calculator package in Python

Python Automatic Decline Curve Analysis (DCA) For Petroleum Producing wells

No description provided.

Carbonate Reservoir Characterization workflow using Clerke’s carbonate Arab D Rosetta Stone calibration data to provide for a full pore system characterization with modeled saturations using Thomeer Capillary Pressure parameters for an Arab D complex carbonate reservoir

Estimate Core-based Permeability from NMR well log data

The objective of this GitHub repository is to develop code that can effectively display well log parameter plots and their animations.

Open source petroleum engineering projects, useful scripts, functions, and jupyter notebooks

3D Graphical Output of well producers and injectors in oil reservoir.

Repository of upcoming abstract submission deadlines for geoscience conferences

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

A "simple" decline-curve analysis example in Python

The objective of this project is to interactively interrogate oil field production data using Altair

Scaling solutions for production analysis from unconventional oil and gas wells

Shaley-Sand Log Analysis Tutorial using Waxman-Smits and Dual-Water

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

My RE (reservoir engineering) Python code

Load cases for tubulars

Official repo of the ManyWells project - sharing data and code for simulating multiphase flow in oil and gas wells

Repo that contains an exploratory data analysis of pre-salt wells and geo data from ANP data base

An open-source Python package for writing DLIS files.

R interface to Eclipse parser of binary files

Pore Pressure Analysis workflow using Eaton's Equation

Discounted cash flow analysis for oil and gas