Educational Vibration programs. Intended for undergraduate and early graduate students.
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Updated
Jul 15, 2021 - Python
Educational Vibration programs. Intended for undergraduate and early graduate students.
Machine learning framework for reservoir simulation
FlowNet - Data-Driven Reservoir Predictions
R package for Arps decline curve analysis.
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 availab…
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
Repository of upcoming abstract submission deadlines for geoscience conferences
Estimate Core-based Permeability from NMR well log data
Calculate a Chart Book type of Neutron Density log analysis Porosity using Python's KNN
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.
A "simple" decline-curve analysis example in Python
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
Mihai's PetroGG modified to be used with our shaly-sand Gulf Coast NMR data.
Shaley-Sand Log Analysis Tutorial using Waxman-Smits and Dual-Water
This repository contains a Python script that uses the Plotly library to create an interactive web-based application for plotting seismic data sections from SEG-Y files.
Python Automatic Decline Curve Analysis (DCA) For Petroleum Producing wells
Use of Sklearn to predict Petrophysical Rock Types (PRT) in an Arab D carbonate based on Clerke's Rosetta Stone Calibration data
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