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Oilfield Technology
January
2016
Clearly, being able to predict when they are going to crash (and
being able to swap them out beforehand), is valuable information.
Apache Corporation operates thousands of ESPs in
North America and around the world. Thanks to real time
monitoring, the Texas-based company has collected a huge
volume of ESP performance data, along with completions,
subsurface characteristics and geological information.
The company knew that they potentially held the key to
extending operational life of their ESPs. They contracted with GE’s
oil and gas division to analyse the hybrid data in order to pick the
right pump for the right well, then to help pumps last longer, and
finally, to predict when they might fail. In the end, the process
helped Apache avoid significant losses of production.
The company’s success came from leveraging a hardware
and software process that is generically referred to as asset
performance management (APM). Real time monitors transmit
a spectrum of data to central facilities where they are processed
with software that uses big data analytics to search out patterns
invisible to the human eye.
Various terms are used to describe parts of the process,
including artificial intelligence, machine learning, and machine
intelligence. At its most generic, software developed around
specialised algorithms takes a wide array of space and time data
(not only quantitative data, such as temperatures and pressures,
but language, images, speech and metadata), and makes common
sense of it all.
According to GE, APM can reduce maintenance costs by 30%,
cut scheduled repairs by 12% and reduce breakdowns by up
to 70%. “The work we do with customers shows that big data
analytics can make a difference,” says Orvil Smith, the Canadian
general manager of GE Oil and Gas Measurement and Control.
“When an ESP fails, it can take a long time to get the well back up.
If you can anticipate a problem before failure, know when to turn
it down and order new replacement parts, then it can avoid a lot
of down-days.”
APM is just one facet of a revolution underway in all sectors
of the economy. Smart devices, ranging from electric meters to
pipeline substations, are gathering data and transmitting it via
the internet. According to Cisco, there are currently 25 billion
smart devices connected to the internet. By 2020, that number is
expected to double to 50 billion.
Already, the oil and gas sector is creating immense volumes
of data with smart devices. Operators calculate that monitors
on a 3000 km gas pipeline generate 30 terabytes of data every
month, which is triple the amount of information stored in the
Library of Congress.
Companies are looking at a range of ways to integrate APM
and its offshoots into the oil and gas industry. Bit Stew Systems
is a San-Francisco based firm. It specialises in supplying software
to connect and control monitors and gauges, and develops APM
applications for the collected data. Recently, they conducted a
downtime proof-of-concept case study for drill-ships. “The most
common cause of downtime is when an asset fails and there is an
inefficiency of response,” says Franco Castaldini, vice president
of Bit Stew Systems. “The replacement part is not in inventory
so there is lost time while the OEM supplies a part or the
operator searches for a replacement on another ship.” Bit Stew’s
algorithms allow the driller to analyse their level of risk through
condition-based maintenance based on actual performance
details. “It gives you a visibility to parts inventory that allows a
faster response.”
Bit Stew’s first oil and gas sector APM-related application is
designed to maintain pipeline integrity. “The pipeline integrity
application looks at the flow, pressure, vibrations, and valves and
geospatially visualises everything in one place,” says Castaldini.
“You can then integrate weather, fire and seismic events so that
you can understand the risk to assets and take action.” Not only
does the system improve the efficiency of response to events, it
also allows greater functionality and less downtime.
Ayata Prescriptive Analytics, based in Houston, is one of the
pioneers of incorporating a wide variety of information – from
gauge data to videos, images, text and sound – into analytics. The
company breaks analytics down into three categories: descriptive
analytics (what is happening, and why); predictive analytics (what
will happen); and prescriptive analytics (what can be done to
improve what will happen in the future).
According to CEO Atanu Basu, the company is working with
Chevron, Apache and other oil and gas firms to help make the
development of unconventional resources more efficient and
safer. Ayata’s application analyses 3D seismic data, real time
drilling logs, frack pressures, water use, casing information and
production statistics. By combining all the available data sets with
prescriptive analytics, the company claims that operators can
devise better decisions that look much further ahead (as opposed
to the current practice of reviewing data and making incremental
improvements on the next well). Equipment lasts longer, performs
more reliably, and, in the end, results in greater field production
and recovery.
Operators do not necessarily need to invest in expensive
gauges and monitors to benefit. Atlas RFID supplies the Jovix
system (which consists of radio frequency identification, or RFID
tags, and related equipment and software), to the construction
industry. The tags contain electronically-stored information that
allows them to be identified and tracked. When a tag passes within
range of an RFID reader, the tag automatically transmits electronic
information to the reader, where it can then be recorded on
tabulation software. The tags have proven to be very useful on
large oil and gas construction sites, where billions of dollars’
worth of equipment and materials need to be tracked and located.
Currently, Atlas is working with Bechtel and other engineering
firms to augment their system. Many pieces of equipment
awaiting installation in the laydown yard require periodic and/or
preventative maintenance to maintain functionality. Special
applications can both locate and diarise maintenance activities.
“Jovix is a state of the art software solution that can radically alter
the work processes associated with material management in an
innovative manner,” says Ed Koch, Software Product Manager for
Bechtel Global Corporation.
Using APM to monitor equipment, scheduling maintenance
and enhancing safety is merely scratching the surface. GE has
been offering such services to oil and gas clients for several years,
and is now engaged in stretching the boundaries. “GE is working
with our customers in oil and gas to evolve big data analytics to
go beyond equipment management and to optimise the entire
production process,” says Darren Massey, programme leader,
Customer Innovation Centre, at GE Canada Global Growth and
Operations, “Any knowledgeable person in the oil and gas sector
knows that when they see a pump gauge pass the red line, the
pump is going to burn out. What big data analytics does is look
at a wider range of available data to find patterns that are not as
obvious to extend the life of that pump but also optimise the way
it operates to get the most production out of it.”
