Detecting Outliers Using Python’s Scikit-learn Library — Isolation Forest is a popular unsupervised machine learning algorithm for detecting anomalies (outliers) within datasets. Anomaly detection is a crucial part of any machine learning and data science workflow. …

Using your passion to build multiple revenue streams — Over the past few years, the popularity of earning money online whilst maintaining a full-time 9–5 job has grown considerably, especially during the pandemic years. Some lucky few have managed to make their side hustle their full-time job once they reached a certain goal. …

Simple and easy pieces of code to enhance your seaborn scatter plots — Seaborn is a popular python data visualisation library that is built on top of matplotlib. Even though matplotlib is one of the most popular data visualisation libraries it has a number of shortcomings. This includes requiring more code for creating advanced graphics. This is where seaborn comes in. …

Convert raw well survey data to complete positional data with wellpathpy — Depth is an essential measurement when working with subsurface data. It is used to tie multiple sets of data to a single reference. There are numerous depth references used to identify a position within the subsurface. …

Integrating subsurface measurements with Python — When working with subsurface data we often deal with datasets that have been sampled in different ways. For example, well log measurements are continuously recorded over intervals of the subsurface at regular increments (e.g. measurements every 0.1 m), whereas formation tops are single depth points.

Improve your matplotlib figures with these simple steps — Matplotlib is one of the most popular data visualisation libraries available within Python. It is typically the first data visualisation library that you come across when learning python. …

An overview of a popular machine learning algorithm applied to petrophysics — Random Forest is a very popular and relatively easy to understand machine learning algorithm. In my previous article on Random Forest we attempted to predict categorical data (lithology) from a series of well log measurements. Within this article we are going to focus on the prediction of continuous measurements. Introduction to Random Forest for Regression

Classifying the Subsurface With Machine Learning — Random Forest is a very popular machine learning algorithm that can be used for both classification, where we are trying to predict a category or class, and regression, where we are trying to predict a continuous variable. Within petrophysics and geoscience, we can use this algorithm for predicting lithologies from…

Visualise how well features correlate with each other with a simple heatmap — Heatmaps are a great tool for creating beautiful figures and can provide us with insights on trends and allow us to easily identify potential outliers within a dataset. Within this tutorial, we are going to look at one of the uses for a heatmap — the correlation matrix heatmap. A…