Geoscience Hackathon 2022 Results

Geoscience Hackathon 2022 Results in Impressive Mapping and Data Developments

It’s amazing what you can accomplish when you put your mind to it. That’s what four teams did at SeisWare this weekend. Over two days hackathon participants brainstormed, strategized, and coded their way through the SeisWare hackathon with the theme of ‘mapping’. All teams were given access to SeisWare software, the PetroNinja API, and whatever libraries, datasets, and resources they could find on their own. It can be a challenge to work with data. The teams managed this and the added challenge of working with new people and working within a very short time frame. Teams had only two days to complete their tasks and present their solutions.

Hacking is about playing around, making mistakes, and learning new things. Teams were judged not by the completeness of their code or readiness of their proposed apps, but rather for their exploration of ideas, creativity, learning, and presentation. The teams’ solutions were scored by a panel of three judges in the categories of “best use of theme”, “most creative”, “audience favourite”, and what the judges deemed to be”Best overall”. Judges were Stephen Bilston, CTO of Petro Niche Technology, maker of PetroNinja, Ed VanWieren, Product Manager and Founder of SeisWare International Inc., and Paige Mamer, Geoscientist and Marketing Coordinator at SeisWare International Inc.

The presentations were impressive! ‘Hacked’ solutions include,

• A map-based application to interactively view global carbon dioxide emissions over time and predict them in the future
• A program to plot and analyze lithium data in Alberta to identify concentrations and their relationships to other geologic parameters
• A map-based machine-learning program that uses well data and predicts information over several subsurface zones

It was the dynamic duo of Jieyu Zhang and Elias Carciente, that came away with the top prize for their idea, which was on-theme, creative, and made all the judges say “I want that”. Their map-based data QC tool solved a problem that all teams struggled with: messy data. Their tool identifies inconsistent well data at a glance and can be used at the start of any project to clean up bad data to accelerate projects and ensure high-quality results.

This year’s Hackathon emphasized open-source development and collaboration. In this vein, team solutions are available on GitHub.

• CO2 emissions: https://github.com/jrojas12/SWhackaton2022/tree/main
• Lithium Team: https://github.com/hyperiongeo/SeiswareHackathon2022-Leduc
• Machine Learning Prediction Team: https://github.com/JinjjLi/Hackathon2022_T5
• Data Cleanup Team: https://github.com/JieyuZhang97/hackathon2022