Our workshop's objective is to introduce the theory and practical applications of machine learning within the Energy industry as means to help improve data-driven decision making.

Course materials will consist of web-hosted lecture materials, instructor led, well-documented methods, workflow demonstrations, and coding examples. The workshop will be delivered via a cloud-based Jupyter Lab session, so the only thing you need to bring are your laptop and your fingers!

The course will be co-sponsored by daytum and the SPE GCS-Data Analytics Group and led by renowned Geostatistics and Reservoir Modeling expert, Dr. Michael Pyrcz, a leader at daytum and an Associate Professor at UT’s Hildebrand Department of Petroleum Engineering.

Intended Audience:

Reservoir Engineers, Drilling and Completion Engineers, Production Engineers, Geoscientists, Data Scientists, Managers, etc.

All participants will be given SPE Continuing Education Credits and Daytum Course Completion Certificate!

To add to the fun, we will be hosting a Happy Hour and Networking session at Rice University's Valhalla bar after the workshop.

Note: Before you register, we require registants to submit their github username at the time of registration. We will be using github usernames to provide access to the Jupyter Lab which contains classroom notes and coding exercises.

If you don't have a github account, please create a free one using this link - https://github.com/join?source=header-home. 

For any questions reagarding registration please contact Sunit Mathur @ sunit.mathur91@gmail.com and Sergey Parsegov @ parsegov@tamu.edu