- Download 30 gigs of LAS from UTLands
- Write Python code to read each LAS and save curve name, units and description to SQL table
- Query SQL for curves that have keywords in their description
My little table of logging curves for this one data source is just over 270k rows. Neat.
When going through the curves there were enough instances with descriptions I didn't need to query the SPWLA mnemonic search. If a curve was in the list that I didn't recognize I could quickly query all instances of that curve and look at the available descriptions.
I wonder what I could learn by mapping out various header information? Stay tuned.