Machine Learning Challenge – Using AI to Validate Carbon Containment in the Illinois Basin
This challenge aims to use time series injection information and monitoring data on a carbon capture well to predict carbon capture well injection rates deltas. Correlating the change in injection rate to the behavior of other parameters in the well can be used to provide a checkpoint against carbon migration from the well or other losses during the process. The code developed to predict injection rate deltas based on monitoring well data can be used to validate carbon containment throughout the injection of the well.
Data Source: Department of Energy - https://edx.netl.doe.gov/reference-shelf/faqs/
Please register here as well: https://xeek.ai/challenges/using-ai-to-validate-carbon-containment-in-the-illinois-basin
Frequently asked questions (FAQs):
1. Each team consists of 1-4 person(s)
2. Each team pays $5 for registration
3. Everyone can participate in this challenge
4. Challenge is open to the public starting from April 10th to April 24th
5. Judging is open for four weeks starting from April 24th to May 15th
6. Print winners' certificates from May 15th to May 29th
7. For any question(s), please send us an email: SPEMLChallenge@gmail.com
Prize recognition for winner(s):
1st winner: certificate and tickets to DSC (Data Science Convention) and featured at DCS, featured on SPE GCS DASG website (sponsor to provide check directly to the winner)
2nd winner: certificate and tickets to DSC and featured at DCS, featured on SPE GCS DASG website
3rd winner: innovation award for the most innovative participant
For further information, please contact: Nelia Mazula