(MENAFN- Trend News Agency) BAKU, Azerbaijan, November 23. National Oilwell
Varco (NOV), a company specializing in equipment and components for
oil and gas drilling and production, has developed a single
standardized artificial intelligence (AI)-based platform for
drilling operations, NOV's business development manager,
completions and production solutions Torbjørn Hegdal said, Trend reports.
He spoke at the SPE Caspian Technical Conference in Baku.
"When you go from understanding algorithms to building a
platform, it takes a lot of effort. So, the first step is to
digitize and then collect data and systematize it. I would like to
go a little bit deeper into the macro picture and focus on some of
the things that we do in our company, specifically drilling
operations, process operations, both surface and subsea, and maybe
business development. We believe that at the heart of automation is
the automation of drilling operations," Hegdal noted.
"It's the use of technology to process data, look at it and
learn from it, and it's all an automated process. We see a lot of
benefits when it comes to energy efficiency, chemical use, etc. to
really reduce the impact of our operations. It promotes remote
working. It kind of gets people out of unsafe places, increases
economic efficiency, etc.," he said.
According to him, a lot of it has to do with condition
monitoring, predictive maintenance, specifically with early
detection and getting ahead of operations.
"Briefly explained, it's about platform development. There are a
huge number of possible applications within our business. That is
why we have developed a single standardized platform. There is a
lot of data collected from wells, production, operations, drilling
operations, and the platform was created precisely to systematize
this data and to be able to learn from it. One of the things we're
doing is analyzing the data on site, in real time, so that it's not
affected by communications and it doesn't go to the cloud. But it's
about the way we store the data and also use it remotely. But
again, this is an attempt to move to a more standardized platform,"
he noted.
Hegdal mentioned that the platform is designed and used
primarily for drilling operations, but technologically, the company
is looking to take the same approach.
"So it's about collecting data, systematizing it and moving it
into some kind of unified space and onto a unified platform. And
it's very much about creating and developing a digital twin to work
on. And then the use of different levels of artificial
intelligence, from machine learning to working deeper with the data
and making faster decisions in operations. So, in drilling, it's
very much about automating drilling and identifying that function,"
he added.
Torbjørn Hegdal added that there are two sides to this. One is
identifying any outliers, whether that's a risk or actually
optimizing performance. It's about achieving repeatable operations.
There are other applications, such as vessel condition monitoring.
It is used on more powerful vessels to truly control this part of
the operation as well.
According to Hegdal, many analyses are only performed on-site,
but operations can also be performed remotely.
"When it comes to workflow, it's about predictive maintenance to
minimize downtime and process issues. So, I am just going to dive
into a couple of examples because I think it's a good way to look
at a micro level of what's actually happening in algorithms and how
we can implement it in business," he emphasized.
Hegdal said that the example relates to a water treatment
process, whether it's produced water or seawater that is processed
for pumping purposes.
"It's a case study, but it's really to understand the
performance of membranes and try to be more proactive. If it is
done manually, just observing deviations, it's going to take time
and end up causing more downtime. But in this case, machine
learning allows to track patterns in equipment performance and
detect a typical problem - biofouling - at a much earlier stage,"
he said.
"Of course, this has a direct impact on uptime, but there are
other benefits, such as reduced chemical consumption, and overall
it's a more sustainable solution. I would take it one step further,
and that is to do with the underwater part. This is to visualize
what happens underwater when the work process is done above. It's
all about reliability, uptime and minimizing maintenance. So we're
going to take the same approach here as well to really understand
all the data that's coming in," Hegdal explained.
"So when we talk about water treatment, we use electrolysis, all
the chemicals on the seafloor, and we're continuously monitoring
that. We get a lot of data, but again, it's about understanding and
seeing that data and learning from it," he said.
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