This series of Jupyter Notebooks take you through various aspects of working with Python and Petrophysical data.
This series consists of:
- Loading and Displaying Well Data
- Displaying a Well Plot with matplotlib
- Displaying histograms and crossplots
- Displaying core data and deriving a regression
- Petrophysical Calculations
- Displaying Formations on Log Plots
- Working with LASIO
- Prediction of missing data using Machine Learning
- Poro-perm resgression analysis
- Data QC
- More working with LAS files
- Pickling and Unpickling
- Interactive Petrophysical Plotting
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.
- 15_9-19.csv
- 15-9-19_SR_COMP.LAS
Information on the Volve dataset can be found at: https://www.equinor.com/en/what-we-do/norwegian-continental-shelf-platforms/volve.html
- L0509WellData.csv
Dutch offshore and onshore well data can be accessed from: https://nlog.nl/en
If you have any suggestions of what you would like to see, please raise a new issue and I will put something together.