Become a sponsor to Justin Gosses
I used to work as a geologist. Now I work in a different industry as a data scientist and software engineer. When I worked as a geologist, I was frequently unhappy with the well log tools I used. Many had bugs that were years old, reflecting the low degree of importance vendors and enterprise buyers put on well log tools as opposed to other areas. Standard workflows only put into a computer what was previously done via paper and pencil.
Open-source Python and JavaScript packages focused on well logs offer potential to explore new ways to work with well logs in terms of processing, analysis, visualization, machine-learning, and uncertainty management. These side projects offer me a way to apply my current experience as a data scientist and software engineer to my domain knowledge in geology.
GitHub sponsors has provided a way to receive requests from an enduser who used wellioviz.js (open-source JavaScript visualization of well logs) in their own product and justify spending time on open-source development.
Other related work includes:
- Predictatops (Python machine-learning applied to chronostratigraphic surfaces in wells)
- wellio.js (conversion of LAS well logs into JSON for easier working with wells on web & interactive notebooks)
1 sponsor has funded JustinGOSSES’s work.
Featured work
-
JustinGOSSES/wellio.js
JavaScript for converting well-log standard .las file format to json format
Jupyter Notebook 34 -
JustinGOSSES/wellioviz
d3.js v5 visualization of well logs
JavaScript 52