Dec 14, 11:30 AM - 1:00 PM (CT)
December SPE OKC Monthly Luncheon
Will Rogers Theater, December 14th, 2017, 11:30 AM - 1:00 PM
The Rise of the Machines, Analytics and the Digital Oilfield: Artificial Intelligence in the Age of Machine Learning and Cognitive Analytics (SPE Paper 2668073, 2017 URTEC Conference Paper)
Presented by Tristan Arbus and Jess Sneed, Devon Energy
In the next ten years, instantaneous value from digital oilfield systems will dramatically alter the oil and gas landscape as cost and operational efficiencies are attained through the reliance on artificial intelligence. The digital oilfield will radically change how oilfield workers, machines, and the holistic enterprise operate to achieve results and compete in the new digital world. The new digital oilfield will be a disruptive technology that creates new value streams for exploration and production ranging from automated decisions and reactions in real time to massively improved operational efficiencies, connected infrastructure platforms, and much better interaction between machines and humans. The days of collecting and storing large volumes of data for later analysis will become a distant memory. The digital oilfield will change expectations for all aspects of our industry ranging from how fast decisions are made to detecting patterns the human eye cannot see in order to take advantage of the insights quicker. Data silos will be reduced and information shared across all areas of the oil company. At a simple level, artificial intelligence will be used to increase the accuracy of predictions to near-cognitive robotic comprehension in machine learning.
To quote Erik Brynjolfsson, director of the MIT Initiative on the Digital Economy, "Humans must adapt to collaborate with machines, and when that collaboration happens, the end result is stronger." This session will outline three ways advanced analytics and artificial intelligence can help bridge the gap between the digital oilfield and analytics: (1) predictive analytics from a case study in predictive asset failures, (2) machine learning in completions, and (3) text analytics in drilling. The session will outline the people, process and technologies needed to enable this infrastructure. Additionally, key pitfalls to avoid regarding systems, silos, and the human barriers to understanding artificial intelligence and getting past the hype associated with new technologies will be discussed.
Tristan Arbus graduated from Johns Hopkins University in 2010 with a BS in Physics and a BS in Engineering Mechanics. He started in the oil and gas industry in 2011 as a drill site supervisor for Pittsburgh-based Consol Energy where he acted as company man for all phases of drilling operations with a focus on the Marcellus and Utica shales. He has been with Devon Energy since 2014, first as a drilling engineer in their decision support center and currently as an analytics expert and data scientist on Devon’s Advanced Analytics team. Tristan is focused on collaborating with other drilling, operations, and subject matter experts to solve complex oil and gas problems through the use of technology and artificial intelligence. Jess Sneed graduated from Northwestern University in 2011 with a BS in Industrial Engineering and earned her Masters of Public Health in Epidemiology from Emory University in 2013. She has worked as a data scientist on the Advanced Analytics team at Devon for over three years providing analytics support to various groups across the company. Her areas of expertise include text mining, production operations analytics, and data visualization.
Registration URL: https://attendee.gotowebinar.com/register/8884370998332736001 Webinar ID: 608-803-643
Oklahoma City, OK, United States