The Digital Oil Field (DOF) has been a major area of investment for all the majors and a fair few others since the mid part of last decade. It was one of those times where all the issues swirling around the ether suddenly coalesced and screamed a common and overwhelming answer. Whether the issue was difficult plays, attracting skilled labor, improving safety, mitigating environmental impact, improving day to day running and monitoring, or maximizing recoverable reserves, the answer was IT and lots of it.
But has the DOF passed by the finance department? Has all the benefit accrued to the engineers and while finance has picked up the cost of placing sensors of anything that moves? To answer that question maybe we first need to look outside of oil and gas.
Look at the average manufacturing company and what they call “Shop Floor Data Capture” was started in the 1970’s. And in the decades since it has been used to monitor and record at increasing levels of detail across motor manufacture, high tech, food processing and apparel. Even at the “craft” end of these industries the move to digital has been inexorable: the cylinders in your Aston Martin are no longer finished by hand using apricot stones, but then they’re also likely to last 200,000 miles. The Digital Factory (pioneered in Japan) has been used to drive quality, efficiency and cost reductions, not just to monitor what is happening and to avoid shutdowns and accidents.
So how do we get these more interesting benefits out of our DOF investment? The answer lies in being able to capture the trends and outliers in the huge swathes of data that is produced and to analyze it meaningfully. Writing in Strategy and Business in 2008 (Issue 50) Steinhubl and Klimchuk offered the following definition of the DOF:
“The digital oil field is a suite of interactive and complementary technologies that let companies gather and analyze data.”
The question is, are you analyzing the data? Or are you just using it for operational reasons and then either storing it on servers or just throwing it away?
Unknown Casualties in Data Explosion
One problem to overcome is that storage and analysis can sometimes work against each other. The more we gather, the less we can analyze. That’s a factor of volume, yes, but more importantly it is a factor of source. Recording and generating new data types, from new systems, has been a necessary consequence of the DOF. But our Business Intelligence systems (BI) are still analyzing the old world. Where is the sensor data in your SAP BW? These systems are difficult and expensive to implement, and arguably harder and more costly to change. Accommodating entirely new data sources means changing and building new structures of data – aggregations, dimensions and hierarchies.
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