Subsurface Analytics: Operationalizing the Original “Big Data”

“Big Data” has become a convenient short-hand for the exponential growth of data volumes across many industry sectors. This is nothing new in the subsurface domain but E&P DM practitioners can learn from “new” industries how best to deal with complexity and timeliness in their analytical ecosystems. We present an architecture that brings to bear the twin paradigms of massive knowledge discovery using Map-Reduce and “operationalized” decision support using a Relational Database Management System. We describe how this single data instance drives rigorous geological, geophysical and engineering insight into right-time integrated operations generally and allows data, and insight derived from it, to drive business decisions across the enterprise.