American Oil and Gas Reporter - July 2021 - 64

SpecialReport: Cloud Computing
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Laredo is monitoring tank batteries for leaks and overflow conditions. For leaks, the
company monitors the inflow to the tank and accounts for tank pump patterns and/or
truck hall patterns. For unknown rate change patterns, Laredo notifies the appropriate
field personnel. Shown here is an example of a leak within a battery and the point at
which field staff would have been alerted.
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with AWS to implement a machine
learning service to build, train, and deploy
machine learning models into our
pipelines. Proactive monitoring also was
applied to tanks and corridor lines to
detect leaks, which reduced the risk of
unexpected on-premises issues.
We used machine learning tools to
quickly identify and remediate issues
that could result in flaring or venting of
natural gas. We set up proactive monitoring
of field equipment as well as tank
pressure, product compositions such as
the mount of oxygen, hydrogen sulfide,
and other mixed produced gas streams,
and physical pressure release points such
as Enardo valves. By leveraging computer
vision and the corresponding pressure
measurements, we were able to identify
events and notify field personnel to investigate
future issues. We also were
able to help with root-cause analysis of
likely leading indicators of why a controllable
event occurred.
The first step was to install IoT devices
to generate high-velocity data that would
enable us to interrogate the negative
venting events in a new way and get a
view into the issue that we did not have
with our legacy systems. The improved
data initially led us to a suspect conclusion
that the events were not occurring nearly
as often as the measured volume suggested,
so we added another device: a
thermal camera.
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After training our computer vision
models, and re-evaluating the historical
footage with the new algorithm, we were
able to reach a correct conclusion that
negative events were occurring that we
did not even know about. We were also
able to determine that these events could
be remedied with simple equipment configuration
changes. As a result of the
data-driven discovery and remedy, Laredo
now has one of the lowest flaring and
venting rates in the entire Permian Basin.
Exhilarating Timeline
The timeline on this project has been
Laredo's cloud-based digital strategy includes deploying an algorithm that monitors
plunger effectiveness and determines when Laredo should economically replace
plungers in its wells.
64 THE AMERICAN OIL & GAS REPORTER
exhilarating. In late March 2021, we escalated
addressing controllable venting as a
priority. By the end of March, we installed
our first IoT devices to explore the phenomenon
in depth. By mid-April after the
initial dataset had been collected, we were
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American Oil and Gas Reporter - July 2021

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