Petrophysics-Python-Series

This series of Jupyter Notebooks take you through various aspects of working with Python and Petrophysical data. A number of the notebooks are accompanied by either a Blog Post or a Medium article. You can find the full list on my website at: http://andymcdonald.scot/python-and-petrophysics

This series consists of:

1. Loading and Displaying Well Data
2. Displaying a Well Plot with matplotlib
3. Displaying histograms and crossplots
4. Displaying core data and deriving a regression
5. Petrophysical Calculations
6. Displaying Formations on Log Plots
7. Working with LASIO
8. Curve Normalization
9. Visualising Data Coverage - Multi Well
10. Exploratory Data Analysis with Well Log Data
11. Deriving a Porosity - Permeability Relationship

Still to come

• Prediction of missing data using Machine Learning
• Data QC
• More working with LAS files
• Pickling and Unpickling
• Interactive Petrophysical Plotting

Data Sets Used

Data for each workbook can be found with this repo's data sub folder.

All data has been obtained from publicly accessible data repositories. Details for the origins of each file is presented below.

Equinor Volve Dataset

• 15_9-19.csv
• 15_9-19A-CORE.csv
• 15-9-19_SR_COMP.LAS
• VolveWells.csv

Information on the Volve dataset can be found at: https://www.equinor.com/en/what-we-do/norwegian-continental-shelf-platforms/volve.html

NLOG - Netherlands Well Log and Data Repository

• L0509WellData.csv

Dutch offshore and onshore well data can be accessed from: https://nlog.nl/en

Force 2020 XEEK

• xeek_train_subset.csv

FORCE: Machine Predicted Lithology https://xeek.ai/challenges/force-well-logs/overview

Suggestions

If you have any suggestions of what you would like to see, please raise a new issue and I will put something together.