American Oil and Gas Reporter - February 2019 - 79

netically attached the sensor to an overhead
steel cable, and dropped the sensor into
the pond. Now, the company is able to
comply with regulations without constant
routine checks. This simple and low-cost,
yet highly effective, solution provides
everything the site operator needs.
As IIoT sensors continue to decrease
in size and cost over the next few years,
most of the value in remote monitoring
likely will be captured by simple, generalized sensors. With low-cost, easy-touse sensors, all equipment that is not now
being monitored will be brought online
using pressure, tank level, motor speed,
vibration and temperature sensors. Routine
field work, reporting and accounting will
be largely automated and equipment failures will trigger immediate alarms. The
net outcome of ubiquitous monitoring
will be more efficient and safer operations
with minimized downtime.
Artificial Intelligence
Looking forward, the proliferation of
low-cost sensors will pave the way for
bringing artificial intelligence to ordinary
equipment. The most immediate value
of AI is that it takes data from basic
sensors such as pressure, temperature
and vibration, and delivers deep insights.
There is a huge amount of interest in
applying machine learning to the oil
field. Large oil companies have scores
of data scientists and researchers who
are taking data from SCADA monitoring
systems on highly automated fields and
then are generating insights and suggestions for optimizing production. Many
high-tech startups are springing up and
are offering optimization services for
niche applications.
For example, many companies monitor
motor vibrations on large gas compressors.
In the same way an experienced mechanic
can hear the grinding sound of a bad
bearing in a car wheel, the best of these
algorithms can identify and even predict
machine maintenance issues before they
cause downtime. Other companies are
taking streams of pressure data from
flowlines and are identifying leaks reliably
as soon as they appear.
The influence of AI in the oil field is
growing rapidly and warrants the excitement it is generating. However, until
now, AI has been confined to large oil
companies only. To start, training AI
models requires large amounts of cen-

tralized data, which traditionally depends
on teams of people managing sensors
and servers. In addition, companies need
highly skilled data scientists to run the
algorithms and interpret the results for
each application. Even when the AI
comes from a third party, the tasks of
transferring data and delivering results
to people in the field remain too complex
for all but the largest companies.
The second wave of IIoT sensors will
democratize access to AI as IIoT companies that aggregate data from many
operators develop cloud-based AI solutions. Since these companies already
will have sensor data managed centrally,
they can avoid the data flow complexities
that slow AI efforts. Furthermore, these
companies will be able to integrate the
AI insights into their dashboards and
apps, making them easy to see and respond to.
By offering AI as a service, IIoT companies will make AI accessible to smaller
operators and affordable for even lowmargin fields. These operators finally
will start to employ the full range of surveillance technology that today is available
only to large companies.
These second-wave sensors represent
a groundbreaking advancement that delivers on the promises of IIoT today and
unlocks a new world of artificial intelligence applications. Low-cost, flexible
and widespread monitoring is decreasing
downtime and optimizing production,
and will continue to do so as the technology is adopted.
r

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Stephen Crowe is the technology
manager at Sensorfield LLC, where
he leads the development of the company's platform and wireless monitoring sensors for oil and gas production
operations. Prior to joining Sensorfield, Crowe worked in testing automation at Schlumberger. He holds
B.S., B.A. and mechanical engineering degrees from Rice University.

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FEBRUARY 2019 79

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American Oil and Gas Reporter - February 2019

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