Digital Energy: Machine Learning: Fundamentals and E&P Applications

Speaker Mark Reynolds
Mark Reynolds has been creating answers in diverse industries and disciplines including avionics systems, performance analysis, process management, real-time solutions, and knowledge research. His broad experience covers a wide range of engineering solutions for operations-centric knowledge systems. His mantra is “focus on bottom-line solutions by improving operations, developing solutions, and ...

Mark Reynolds has been creating answers in diverse industries and disciplines including avionics systems, performance analysis, process management, real-time solutions, and knowledge research. His broad experience covers a wide range of engineering solutions for operations-centric knowledge systems. His mantra is “focus on bottom-line solutions by improving operations, developing solutions, and finding synergy within the organization.”


 


At Southwestern Energy, Mark Reynolds provides the vision and innovation necessary to identify and implement solutions in real-time operations, analytics, and Machine Learning that pull together individual systems, repositories, and operation centers to add value, efficiency, and safety to the upstream exploration and production environments.

Full Description

Machine Learning encompasses data acquisition, transmission, retention, analysis, and knowledge. The expected outgrowth of 24x7 data systems and operations centers is Knowledge Engineering and Data Intensive Analytics AKA Machine Learning. This presentation will develop and apply Machine Learning concepts to the Upstream O&G industry. Specific focus will be given to the fundamental concepts and definitions of Machine Learning along with the application of Machine Learning.

Organizer Tim Loser

When?

Wed, Mar. 16, 2016
11:30 a.m. - 1:15 p.m. US/Central

How Much?

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Where?

Norris Center - Westchase
9990 Richmond Avenue - Suite 102
Houston, Texas 77042
United States

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