The burgeoning world of unconventional resource play exploration and exploitation has forced the petroleum E&P industry to confront issues of uncertainty and risk on an unprecedented scale. Additionally, the digital oilfield revolution continues to drive ever-vaster streams of data from every aspect of our operations—but the information contained within this data is not so simple to extract. As industry practice outpaces theoretical understanding, operators are turning to quantitative techniques honed on "big data?? in far-flung industries in order to make evidence-based decisions. These techniques fly the various flags of "statistics,?? "data mining,?? and "machine learning?? but can be usefully united under the banner of analytics: the discovery and communication of meaningful patterns in data.
Our first steps into this arena revealed that analytics could be a boon to more than E&P; indeed, the approach could benefit the entire business. Deriving maximum value from analytics would require a vision and a strategy for analytics at the enterprise scale—as well as appropriate action to bring these to fruition. In this paper, we present our experience over the first year of the initiative to build an internal "center of excellence?? for analytics at Devon.
We describe our initial work defining "analytics?? at Devon and crafting a strategy to realize this vision. This includes our design of a process for analytics, definition of the R3 criteria for analytics projects, and our experiences with our initial "pilot?? projects and their results.
We share key lessons learned from these projects: the importance of answering the right question, accessing the right data, applying the right tools, and—critically—assembling the right people.
Finally, we present our vision for the future of analytics at Devon.
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