Sept. 26, 2019


Description

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 


Featured Speakers

Speaker: Dr. Michael Pyrcz
Speaker Dr. Michael Pyrcz
Dr. Michael Pyrcz is an Associate Professor at the University of Texas at Austin's Hildebrand Department of Petroleum and Geosystems Engineering. His current research focuses on improving reservoir characterization and modeling for enhanced development planning, minimized environmental impact, stronger profitability and better utilization of valuable natural resources. Dr. Pyrcz’s areas of …

Dr. Michael Pyrcz is an Associate Professor at the University of Texas at Austin's Hildebrand Department of Petroleum and Geosystems Engineering. His current research focuses on improving reservoir characterization and modeling for enhanced development planning, minimized environmental impact, stronger profitability and better utilization of valuable natural resources. Dr. Pyrcz’s areas of specialization include Geostatistics, Reservoir Characterization, Machine Learning, and Artificial Intelligence. A true Petroleum Engineer and Geologist, Pyrcz received his B.Sc. in Mining Engineering and his Ph.D. in Geostatistical Reservoir Modeling from the University of Alberta. After spending 13 years in industry at Chevron, Dr. Pyrcz brings industry experience and knowledge as a teacher, leader, and content developer for daytum, a Houston-based Energy Data Science Education company and to the University of Texas.

Full Description


Date and Time

Thu, Sept. 26, 2019

8 a.m. - 5 p.m.
(GMT-0600) US/Central

Event has ended

Location

Rice University

6100 Main Street MS-530
Houston, TX 77005
United States of America

Rice University - Rice Memorial Center 



Group(s): Data Analytics