Well Log Analysis & Formation Evaluation Case-Study

This repository contains a comprehensive analysis of well log data and formation evaluation aimed at solving key geological problems. The project is divided into two primary sections: Well Log Analysis (Case Study) and Formation Evaluation (Case Study), with data drawn from real-world well logs to provide detailed insights into subsurface characteristics.

Objectives

Well Log Analysis (Case Study)

The well log analysis focuses on addressing the following key problems:

1. Gamma Ray Tool Design: Propose necessary instrumentation requirements for designing a gamma ray tool if the department intends to build one.
2. Quality Control: Perform quality control of wireline logs and identify outliers in the basic well logs.
3. Total Porosity Calculation: Calculate total porosity from the combination of density and neutron logs, and identify zones with the highest porosity.
4. Velocity-Depth Profile: Plot velocity-depth profiles (compressional and shear), color-coded with volume of shale.
5. Water Saturation (Sw) Calculation: Use Archie’s method to calculate water saturation (Sw) and flag reservoir zones where volume of shale (Vsh) ≤ 0.4 and Sw ≤ 0.7.
6. Reservoir Zone Reporting: Report total porosity, water saturation, and Vsh along with their standard deviations for the reservoir zone.

Formation Evaluation (Case Study)

This section involves the interpretation of well data for the Gorgonichthys-1 well, located in the NWS, Western Australia. The formation evaluation is focused on the Brewster Member, and involves the following steps:

1. Optimize Porosity Calculation: Calibrate neutron and density log-derived porosity with core data to optimize total porosity calculation.
2. Water Saturation Comparison: Calculate water saturation using both Archie and Simandoux methods, then compare the results.
3. Net-to-Gross (NTG) Estimation: Estimate the NTG ratio with cutoffs: Vsh < 50%, φ > 5%, and Sw < 50%.
4. Porosity-Permeability Relationship: Build an empirical porosity-permeability relationship from core data, discard anomalous data points during regression analysis, and compute a continuous permeability profile from the porosity log.

Data Sources

• Digital log datasets, formation tops, porosity-permeability database, and well completion reports for Gorgonichthys-1 well located in Western Australia.

Links to download the well data:

• Gorgonichthys-1 Well Information
• Additional Formation Data

Key Technologies

• Python
• NumPy, Pandas for data manipulation
• Matplotlib, Seaborn for data visualization
• Scikit-learn for machine learning algorithms used in lithofacies classification
• Petrophysics tools for well log interpretation and formation evaluation

Results

The project provides insights into:

• Total porosity and water saturation estimation using advanced methods.
• Continuous permeability profile derived from porosity logs, improving the understanding of subsurface characteristics.
• Best-performing machine learning models for lithofacies classification using well log data.

License

This project is licensed under the MIT License.