Building a Log Viewer - Concept

Start a company from scratch. Base it on your last 10 years of work. What do you need to get going? In Petrophysics you need a way to visualize data efficiently. The software platform options range from out of reach expensive to free but clunky. It is all about building your work flow into something efficient.

What's out there?

SpotFire, Excel, Tableau, Orange, Matplotlib

Techlog, IP, Powerlog, Geolog, Recall, TerraStation

Petrel, GeoGraphix, Petra, DecisionSpace

How about your build your own?

With cost heavy on a start-up company's heart, I've decided to build my own log viewer while using a free program for scatter plots and histograms. In about 4 days I had a complete log viewer that would read an LAS file, create tracks, display curves and perform some very nice color fills based on settings in an XML file. As an extra challenge I decided to not use Matplotlib. This is because I wanted more control on the theme and display style.

Here was my pre-build checklist:

1) Use XML format for log templates
2) Read LAS files
3) Use Python and minimal libraries
4) Do not use Matplotlib
5) Display information on each curve in a header
6) Scroll up and down log
7) HTML colors for curves
8) Multiple scales per track
9) Fill to the right or left
10) Logarithmic track

Big list but when you spell it out first then the solutions start pilling in pretty quickly. More posts to come on how to build your own Log Viewer.

#LAS_File #Petrophysics #Log_Viewer #Python #Tkinter #Canvas

Comparison against MatPlotLib

Example log with auto generated header