Introduction

Borehole image logs are false-color pseudo images of the borehole wall generated from different logging measurements/tools. How borehole images are acquired differs between wireline logging and logging while drilling (LWD). In the wireline environment measurements are made from buttons on pads that are pressed up against the borehole wall and provide limited coverage, but at a high resolution. In contrast, in the LWD environment measurements are made from sensors built into tools that form part of the drillstring/tool assembly, and using the tool rotation, provide full 360-degree coverage. LWD image data is often split into sectors, the number of which will vary depending on the tool technology. As the tool rotates the data is binned into the relevant sector and from it we can build up a pseudo image of the borehole wall.

The generated images are often viewed in two dimensions on a log plot as an ‘unwrapped borehole’ and as seen in the image above. The cylindrical borehole is cut along the north azimuth in vertical wells or along the highside of the borehole in deviated/horizontal wells. As a result of being projected onto a 2D surface, any planar features that intersect the borehole are represented as sinusoid shapes on the plot. By analyzing the amplitude and offset of these sinusoids geologists can gain an understanding of the geological structure of the subsurface. Borehole image data can also be used to identify and classify different geological facies/textures, identify thin-beds, fault and fracture analysis, and more.

In this article, I am going to work through displaying logging while drilling image data from azimuthal gamma ray and azimuthal density measurements using Python and matplotlib.

This article forms part of my Python & Petrophysics series. Details of which can be found here. For the examples below you can find my Jupyter Notebook and dataset on my GitHub repository at the following link.

#python #matplotlib