Machine Learning: Practical Examples in Upstream Oil & Gas

Machine Learning: Practical Examples in Upstream Oil & Gas

Oil and Gas Analytics Breakfast Series: 
←  SPE - Calgary Section

Oil and Gas Analytics Breakfast Series 
Machine Learning: Practical Examples in Upstream Oil & Gas

Date: Thursday, May 31
Speaker: Tyler Schlosser, Chief Data Scientist at Verdazo
Location: Calgary Petroleum Club
Time: 7:30 am - 9:30 am
Cost: SPE Members $40.00, $50 Non-members
Discounted four pack breakfast series available HERE

Abstract:

Machine Learning has gained popularity – and hype – in recent years. The volume and complexity of available data in Oil & Gas continues to increase, and our industry is hungry for effective tools and technologies to derive insights and value. This presentation will provide a quick overview of Machine Learning, how it can be applied to O&G problems with a focus on time-to-value, the challenges it presents, and specific case studies to illustrate its power.

Speaker Bio:

Tyler is Chief Data Scientist at Verdazo Analytics and leads Verdazo’s Machine Learning Division. His diverse background includes reservoir engineering, economics, statistics and algorithmic trading. Tyler has worked in the Oil & Gas industry for over 10 years and was previously Director of Economics and Risk at GLJ Petroleum Consultants before recently moving to Verdazo to build on his 15 years of experience in Machine Learning. Tyler takes a practical approach to problem solving and prefers projects that can be directly tied to business value. He has actively shared his insights and experience with the industry through a variety of SPE and industry presentations, published articles and blog posts.




The SPE would like to thank our Platinum sponsor.Repsol_2012_logo.png


Thank you to our participating sponsors.
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May 31, 2018
From 7:30 AM to 9:30 AM
Calgary Petroleum Club
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