Hi-tech cowboys: Applying analytics to oil and gas exploration


I just returned from the largest annual gathering of upstream oil and gas technology professionals. Some of the brightest minds in resource exploration – from graduate students to 50-year professionals – enjoyed the masquerade carnival that filled the exhibit hall on Halloween night.

But the real entertainment was in the sessions. My objective was to learn about the challenges and applications for data management and analytics in unconventional resource exploration.  This includes shale gas, tight sands, and ultra-deep water.  The behavior of these resources during exploration and production is not as easy to predict as “traditional” oil wells because historical data may not provide any statistically relevant insights to guide decisions, and the geology is likely “anisotropic[1]” (one of my new vocab words from the week) leading to many variables that are not within the engineer’s control.

If you haven’t been to a technical session at an energy conference, here’s a primer:  The speaker presents research (based either on actual field development or engineering/geomechanical models) and their conclusions to a crowd of 100-300 people.  A formula with lots of Greek letters may show up on a few slides. Inevitably, seismic readings fill the screen and people nod as they draw their own inferences and conclusions. Then, the speaker's peers stand up to challenge assumptions in their model, from homogeneity of rock formations, analytical models selected, validity of data, etc.  A lively debate often ensues, which may spill out into the hallways and continue until the next conference and next paper.

For a practitioner, it’s a great way of learning the “ah-ha” moments that colleagues have faced (and you hope to avoid).  Veterans of the industry reference the pressure to achieve production levels that were estimated in a corporate office two states over, the challenges of comparing effectiveness of new fracing technologies, and the ever-present need to move beyond “tribal knowledge” to data driven decisions.

The key take-away is this:  Exploration and Production is still an art AND a science. And these are not your typical cowboys.  These professionals want the job done right and they know that better information can lead to better results.  Fortunately, SAS has proven solutions and an experienced team who is ready to help.  Prop up your boots and read these informative papers and case studies from Petrobras and others to learn more.

[1] From Wikipedia:  Anisotropy is the property of being directionally dependent, as opposed to isotropy, which implies identical properties in all directions. This property is used in the gas and oil exploration industry to identify hydrocarbon-bearing sands in sequences of sand and shale.


About Author

Alyssa Farrell

Product Marketing Manager, Energy and Sustainability

Alyssa Farrell leads global industry marketing for SAS’ business within the energy sector, including Utilities, Oil and Gas. In this role, she focuses on the SAS solutions that help optimize our energy infrastructure by applying predictive analytics to complex data. She currently serves on the Advisory Committee of the Research Triangle Cleantech Council and co-leads the Program and Communications Action Committee, as well as a Working Group of the Utility Analytics Institute. She is a member of the Society of Petroleum Engineers (SPE). Farrell regularly speaks with trade associations, analysts, and the press about the opportunities organizations have to effectively manage a sustainable energy analytics strategy and drive healthy economic growth. Prior to joining SAS, Farrell was a senior consultant in the Deloitte Public Sector practice. In this capacity, she was a project manager for state-wide and county-wide systems implementations and was responsible for user acceptance testing, change management and training, and middleware technology selection. She is a graduate of the Eller College of Management at the University of Arizona, where she earned her MBA degree with a concentration in Management Information Systems. She also holds a Bachelor of Arts degree from Duke University.

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