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Machine Learning in Oil and Gas Conference


Houston, TX, United States

Note: This event was originally planned for 14-16 April, 2020 in Houston, TX, USA and has now been rescheduled

New date: 9-11 November, 2020

The 5th Annual Machine Learning in Oil and Gas Conference will include deep-dive informative case studies from oil and gas companies, technology passionate keynotes, interactive panel sessions designed to meet the needs of those on the business and IT side of the Machine Learning.

The 2019 Machine Learning in Oil & Gas Conference was one for the books, with 40+ speakers, 350+ attendees and 20+ sponsors.

The conference illustrated the power and opportunity the technology of Machine Learning has in oil and gas.

Graeme Gordon of Hess presented a session on the "Wells to Watch" application which was a standout session that more than adequately illustrated the power and reach of Machine Learning.

Repsol's German Larrazabal explored the geophysical applications of Machine Learning and spoke to how the technology simplifies his job and produces more accurate results.

Pioneer Natural Resources, Chevron, NOV and Halliburton all spoke on the absolute importance of cultivating new and existing talent to fill the need for more and more data driven position within their work forces.

The key take-away from the event?

There are boundless opportunities for optimization of current processes and Machine Learning is finding those opportunities.

The 2020 Machine Learning in Oil & Gas Conference will see an even greater number of real-world practical applications. Oil and Gas leaders now deploying Machine Learning models at scale, the 6th iteration of this renowned event will focus on how early adopters are gaining an edge - at the expense of slower moving competitors.

This is a rare opportunity to sidestep the hype and discover how budding technologies can be applied into practical and profitable Machine Learning that you can implement in your company today.

Attend Machine Learning in Oil and Gas to

  • Learn how the top oil and gas producers are using ML and data to solve business challenges
  • interactive discussions to network and problem-solve with data scientists
  • Understand how to use deep neural networks for image recognition, NLP and text-based sentiment analysis
  • Rethink company strategies in the age of AI and Machine Learning
  • Take predictive analytics to the next level - strategies for adding AI to your analytics toolbox
  • Listen to 40+ speakers

Predictive Maintenance and Reliability in Oil and Gas | April 14th

This pre conference briefing day is designed to give in-depth insight into one of the most mature applications of machine learning in the oil and gas industry.

Superfluous scheduled maintenance and damaging unscheduled down time are two of the biggest preventable expenses for many oil and gas operations, especially in more remote areas.

The digitalization of the oil and gas industry has created new intelligent solutions to these issues through a combination machine learning, edge computing, IoT, drones and advanced analytics.

Register now to learn how technology has helped shift maintenance from reactive to proactive and how these solutions could save your operations money, time and human resources.

Who should attend:

  • Data Scientists
  • Engineering Managers
  • Automation Specialists
  • Asset Managers
  • Maintenance Engineers
  • Reliability Managers
  • Environmental Specialists

Why attend:

  • Learn how your operations could save time and money through proactive maintenance
  • Stay ahead of the curve on the latest advances in predictive maintenance
  • Hear about successful predictive maintenance programmes from expert speakers
  • Networking with leading solution providers and predictive maintenance operators

Our Speakers

  • Afshean Talasaz, Senior Data Scientist, Chesapeake Energy
  • Jeremy Eade, Data Scientist, BP
  • Andrea Course, Venture Principal, Shell Ventures
  • Anuj Suhag, Research Fellow (ORISE), National Energy Technology Laboratory
  • Deepthi Bollu, Manager, Digital Innovations, Shell
  • Abdulaziz Rajab Moshaweh, Senior Corrosion Engineer, Saudi Aramco
  • Dr. Vikram Jayaram, Head of Data Science & Advanced Analytics, Pioneer Natural Resources
  • Paloma Urbano, Analytics Manager, ConocoPhillips
  • Kamarul A Amminudin, Senior Operation Engineer, Saudi Aramco
  • Shuxing Cheng, Senior Machine Learning Research Scientist, Chevron
  • Dr. Kenneth Bhalla, Principal & Chief Technology Officer, Stress Engineering Services, Inc.
  • MacKenzie Mark-Moser, M.Sc., Research Geoscientist, LRST/National Energy Technology Laboratory
  • Velimir V Vesselinov, Scientist/Principle Investigator, Los Alamos National Laboratory
  • Thor Schueler, Innovation Lead, Avanade
  • Dr. Dave Shook, PhD, P.Eng, President & CEO, ShookIOT Inc.
  • Amy Henry, CEO, Eunike Ventures
  • Jim Lawnin, Managing Partner, BBL Ventures
  • Michael Parham, Data Scientist, University of California Irvine
  • Anna Jarman, Senior Manager, Walmart Technology
  • Chris Buie, Director of Data Science, Warwick Group
  • Conrad Hess, Data Scientist, Warwick Group
  • Dr. Nansen G. Saleri, Chairman & CEO, Quantum Reservoir Impact (QRI)
  • Iurii Milovanov, Director AI / Data Science, SoftServe Inc.
  • Dave Heinicke, Data Scientist, DataRobot
  • Dave Lafferty, President, Scientific Technical Services
  • Chris Humphreys, CEO/Director, The Anfield Group
  • Peter Lemke, Technology Associate, BP
  • Omar Maher, Director of Artificial Intelligence, Esri
  • Sastry Malladi, Chief Technology Officer, FogHorn
  • Michael Zhang, Digital & Automation Research Engineer, Shell Technology
  • Reynaldo Gomez, Energy Partner Ecosystem Manager, NVIDIA
  • Bill Fairhurst, Manager, Industry Engagement and President / Co-Founder, Bureau of Economic Geology and Riverford Exploration, LLC

Please fill in your name and email to receive the Conference Agenda of this event.

Venue

JW Marriott Houston by The Galleria
5150 Westheimer Rd, 77056
Houston, TX, USA
(713) 961-1500
Hotel Website
28 SEP 29 SEP
Houston, TX
United States
Event details
Organizer : Energy Conference Network
Event type : Conference
Reference : ASDE-21959