Using Python to Explore and Understand Equations in Petrophysics
A simple way to understand parameters to the Archie Water Saturation equation using Python
PETROPHYSICS / PYTHON / AI & MACHINE LEARNING
Subsurface data, made usable.
Hi, I'm Andy McDonald and welcome to my corner of the internet.
I'm a petrophysicist and product manager who uses AI to solve real subsurface problems, with a focus on data quality first. Clean data is a luxury, so I spend my time turning messy logs into something usable, trusted, and ready for models and people alike. A lot of the data I work with is noisy or incomplete, so my job is to make sense of it before the machine learning ever gets a look in. I write and share ideas on Python, AI, and working with real data, especially in the subsurface world.
Selected writing
View all writingA few selected articles that you may find useful.
Python in Geoscience: An Essential Skill
How Python can help your daily subsurface geoscience workflows
Data Quality Considerations for Machine Learning Models
Reducing the Impacts of Garbage In Garbage Out on Machine Learning Models
Projects
A small selection of python, petrophysics and machine learning projects that I have worked on over the years.
Python & Petrophysics Notebook Series
A series of notebooks showing how I load, QC, analyse, and visualise well log and petrophysical data in Python, using real-world messy datasets rather than perfect examples.
- Log QC, conditioning, and basic repair
- Petrophysical calculations and crossplots
- Visualisation patterns for subsurface data
SPWLA 2021 Machine Learning Workshop
Co-instructor workshop materials covering applied ML workflows for well logs, with emphasis on QA/QC, interpretability, and what breaks when real data gets involved.
- Supervised + unsupervised log workflows
- Practical QA/QC and outlier handling
- Hands-on tutorials and examples
Building Consistent Sand Flags at Regional Scale
Standardised QC and sand flagging across a large mixed-vintage dataset to produce comparable sand flags for fairway, reservoir, and seal analysis.
- Standardised sand flags from logs
- Gross sand thickness and sand %
- Coverage checks and gap handling
Petrophysics & Geomechanics Under Incomplete Log Data
QA/QC, conditioning, and repair of log data to support 1D/3D geomechanical modelling, including synthetic shear where key inputs were missing.
- Washout/coal identification and conditioning
- Synthetic shear via regression + neural nets
- Geomechanical properties and fluid substitution
Field-Scale Gas Reservoir Re-evaluation
Re-interpreted multiple gas intervals across a compartmentalised field, integrating MDT pressure data to support contact interpretation and bypassed pay assessment within dolomitic intervals.
- Multi-interval interpretation across wells
- MDT review and pressure gradient analysis
- Compartmentalised reservoir intervals and FWL determination
Reservoir Rock Typing Using Unsupervised Methods
Integrated petrophysics and reservoir rock typing across 23 wells, deriving petrophysical groups from SCAL (MICP) and facies information, then predicting continuous rock types and permeability using self-organising maps.
- Petrophysical groups from MICP and facies data
- SOM-based prediction with blind testing per zone
- Permeability prediction per group and mapping