Using the missingno Python library to Identify and Visualise Missing Data Prior to Machine Learning An example using petrophysical well log measurements Photo by Tim Mossholder on Unsplash Data exploration and pre-processing are important steps within any data science or machine learning workflow. When working on tutorial or training datasets it can be the case that they

Thanks for the comment Elena. I am glad you have found this article helpful. Working with Python and geoscience data is great and there is so much potential that ML and Python can bring to it. Looking forward to seeing articles from you on the subject. 🙂

How to Use Unsupervised Clustering on Well Log Data with Python Subdividing the subsurface using Python Application of unsupervised cluster analysis on well log data to identify lithofacies (Image by Author) Understanding the subsurface lithology is an important task in geoscience and petrophysics. Using a variety of electrical measurements generated from well logging technology we are able to

Adding Formation Data to a Well Log Plot Taking well log plots one step further using Python and matplotlib Final well log plot generated using Python’s matplotlib library and contains variable fill on the gamma ray, and a neutron-density crossover fill. Image by author. Well log plots are a common visualization tool within geoscience and petrophysics. They

Thanks Tim. Interesting suggestion. Would you be suggesting appending the dataframes generated in the for loop to something like a pickle file? Would there be any memory issues holding that file open while all las files are being read and appended?

Loading Multiple Well Log LAS Files Using Python Appending Multiple LAS Files to a Pandas Dataframe Crossplots of density vs neutron porosity from multiple wells using the Python library matplotlib. Imagae created by the author. Log ASCII Standard (LAS) files are a common Oil & Gas industry format for storing and transferring well log data. The data

Displaying Lithology Data on a Well Log Plot Using Python Using fill_betweenx() in matplotlib to add variable color fills and hatches for geological lithology data Well log plot with gamma ray, neutron porosity and bulk density data plotted alongside lithology data. Image created by the author. Adding lithology information to a well log plot can enhance a

Enhancing Visualization of Well Logs With Plot Fills Applying Color Infill to Well Log Data Using matplotlib and fill_betweenx() Log plot shading using fill_betweenx. [Image Created by Author] Matplotlib is a great library to work with in Python and it is one that I always go back to time and time again to work with well logs.

Porosity-Permeability Relationships Using Linear Regression in Python A short guide on applying a linear regression in Python to semi-log data Photo by Ekaterina Novitskaya on Unsplash Core data analysis is a key component in the evaluation of a field or discovery, as it provides direct samples of the geological formations in the subsurface over the interval of interest.

Exploratory Data Analysis with Well Log Data Photo by Lukas Blazek on Unsplash Once data has been collated and sorted through, the next step in the Data Science process is to carry out Exploratory Data Analysis (EDA). This step allows us to identify patterns within the data, understand relationships between the features (well logs) and identify possible