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

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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.

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About Author

Alyssa Farrell

Advisory Industry Marketing Manager, SAS

Alyssa Farrell leads industry marketing for the SAS Global Health and Life Sciences Practice. In this role, she focuses on the SAS solutions that help optimize health outcomes for individuals and their communities. Alyssa is actively engaged in analyst relations, market research and influencer marketing to stay on top of industry trends and align SAS capabilities to customer needs. She has also supported the global energy and public sector teams during her career at SAS. Prior to joining SAS in 2004, Alyssa was a senior consultant in the Deloitte Public Sector practice. She earned her MBA degree with a concentration in Management Information Systems from the University of Arizona. She also holds a Bachelor of Arts degree with honors from Duke University. Follow Alyssa on Twitter @alyssa_farrell and LinkedIn at http://LinkedIn.com/in/alyssafarrell

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