ingful patterns in data, and refers to the use of Artificial Intelligence techniques such as machine learning, advanced statistics and natural language processing among others to model,
simulate and then predict what might happen in a process or
device, and potentially prescribe preventative or corrective
alternatives for taking action (such as predictive maintenance
on critical equipment).
The bottom layer of the stack is the familiar Operational
Technology (OT) layer where sensors, actuators, devices, controllers and SCADA systems reside. The next layer is the telecommunications network need to move data from the field,
to the Cloud, and to the office. These are not new as your ROCs
and SCADA systems have been around for more than a decade.
However, it’s the top three layers where most of the change
has occurred creating new capabilities. It’s also where many
of the current production operations workflow software, such
as production allocation, predictive maintenance or production
optimization, will reside. It is important to note that no one
vendor can deliver all the layers – more on this later.
WHY THE HYPE? WHAT’S DIFFERENT NOW?
IIo T has been hyped as a major disrupter of the status quo and
transformational in its impact on the business because of its
ability to connect things and people in ways that hadn’t been
done before, provide unique services and enabling capabilities
not previously possible, or certainly not as cost-effectively.
While this may be true in other industries, especially those
with a retail consumer component, oil and gas is taking a more
measured approach given lower oil prices, lower investment
overall and our reputation for a conservative approach to
the uptake of technologies. The industry usually wants to see
proof of a good business case before overcoming a general
resistance to change.
IIo T and BD&A represent the next stage of the Intelligent
Oilfield which we’ll call Digital Oilfield 2.0. The original Digital
Oilfield, also known as Smart Fields, iField, Field of the Future
and Integrated Operations, that began around the year 2000,
was I T-led and technology focused, and resulted in the expan-
sion of automation, the use of digital devices, the addition of
remote operation centers, standardization of selected work-
flows, and the practice of Management by Exception to operate
fields. Most Digital Oilfield activity was focused on offshore
production, especially deepwater, due to the value of the assets
Over time, it spread onshore to drilling, completions, and
beyond. Its success onshore was initially limited to larger
conventional fields, as the cost of automation for both smaller
greenfields and legacy brownfields was considered prohibitive.
Another shortcoming of Digital Oilfield was that while it
generated much more data from sensors and automation,
most of the data wasn’t being used to improve field
Things have indeed changed in the last 15 years. Today,
advances in computing power and data storage allow a server
to be put on a circuit board the size of a quarter and placed
on or near the device to be monitored–so called Edge Com-
puting. Add low power telecommunications, solar and battery
advances, the Cloud, wireless and lower cost sensors to the
equation and it is possible to monitor and connect almost
When multiple Edge devices work together in a network
connected to the Cloud, we call it Fog Computing, since not
F1: GROW TH IN THE INTERNE T OF THINGS
1988 1992 1996 2000 2004 2008 2012 2016 2020
Io T inception 2012 8.7B