Page 392 - Intelligent Digital Oil And Gas Fields

330 Intelligent Digital Oil and Gas Fields

oil change or service is needed. There will be no reason for a middleman to
make assessments and decisions. Different devices are connected to run a
field operation; today, devices have to communicate “up” to a central device
or dashboard, but in the future there will be an ecosystem of different end
devices communicating with each other by common standards for an open
environment. Reaching this vision has some challenges: production opera-
tions have not kept up with standards and security might be an issue. The
first to market with standards may drive the competition to join in. Main-
tenance will be recorded in real time and also will guide additional actions.
All data will be captured in a knowledge system.
Drones and nanosensors will be used to monitor system leaks.
Nanosensors are available now for leak detection; and like all newer tech-
nology, prices are declining quickly, nearly 100 times less than a few years
ago. Sensors will provide the basis for analytical, data-driven, and modeling
solutions. Sensors make modeling (machine learning) more reliable, and will
eventually be used in multiple system end points to build models.
Use of a single data lake (as described above) means one integrated data
source for an operating asset, which will finally drive movement away from
the domain silos that have plagued the industry for decades. Humans will
interact and make decisions at a more integrated level. Solutions will be built
as services—data as service, analysis as service, visualization as service, alerts
as service. In the future, analysis provides guidance and communication to
operators to act. Brain power and software are on contract.
There is and will be ubiquitous video at well pads and well sites with
remote and automated operations, that pan, zoom, time, recognize abnor-
malities, record acoustics and then store, analyze, and alert for abnormal
issues. Visual diagnostics enable virtual site inspection and will be auto-
mated (see Pixel Velocity, 2017) with recording of events and pattern
recognition.
Here is an interesting comment from Jim Crompton, Managing Director
at Reflections Data Consulting, “Technology vendors are so far advanced
versus the current maturity of the upstream O&G operator that the two
are struggling to have a constructive conversation …Digitization of the
oilfield (at least many of them) is happening, but that does not mean that
effective analytics will naturally follow.” The paradigm of the “digital
twin,” a digital representation of the physical system, is that every asset
and its components “learn” using physics plus data analytics from other assets
as to best procedures and processes. The knowledge repository is in the
“digital twin.”