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Tackling the "Big Data" challenges in Upstream E&P: A review of approaches
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Duncan Irving
Teradata
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Talk Description
"Big Data" has become a convenient short-hand for the exponential growth of data volumes across many industry sectors. Upstream E&P has suffered from "Big Data" for longer than most, firstly in terms of the data volumes but more recently dealing with rapidly changing data and the need to bring complex analytical procedures to bear on it in an operational timeframe.
We present and discuss architectures that bring to bear the twin paradigms of massive knowledge discovery using MapReduce-based technologies and "operationalized" decision support using a massively parallel Relational Database Management System.
We explain how a single integrated data instance should drive rigorous geological, geophysical and engineering insight into right-time integrated operations generally, and short-interval time-lapse reservoir imaging specifically. We explain how we can incorporate this into production workflows to address, for example, HSE and reservoir injection objectives in hour-day timeframes.
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