Hydrocarbon Processing - October 2022 - 63

Digital Technologies
With proactive monitoring and diagnostics
in place, Ithaca Energy improved
reliability and uptime, avoiding losses of
up to $2 MM/d. Additionally, these diagnostic
insights provided a clearer understanding
of the root causes for diminished
or degraded performance, enabling
maintenance personnel to proactively
service equipment prior to failure, and to
also save time and money. By using the
proprietary ML application'sa
asset swapping
capability, Ithaca Energy was also
able to scale the application to monitor
similar assets throughout the enterprise.
Promoting data-driven operational
decisions. Manufacturing campaigns for
a high-value-but difficult to produce-
product at allnex (an industrial coating
resins and additives producer) can last
from weeks to months. Because of the inherent
process complexity and its detrimental
impact on processing equipment,
each campaign will ultimately end due
to the cumulative impact of this harsh
process. Extending a campaign can be
achieved by lessening the daily harsh conditions
that confront equipment-and
extending campaigns by even 1 d-2 d can
provide significant financial upside.
By implementing the proprietary ML
, allnex incorporated timely
applicationa
assessments and insights into product
development campaigns, promoting data-driven
discussions and interventions
to increase success rates. FIG. 3 shows an
instance in which the ML application
identified a factor that was increasing
the likelihood of campaign failure. By adjusting
this process parameter, the team
prevented an early failure, resulting in
significant savings.
This early warning preceding failure,
along with insight into other key contributing
factors, empowered operations
personnel to act early and get the campaign
back on track.
ML improves efficiency. Industrial ML
implementations require process expertise,
data, context and collaboration to
initialize, but no-code options alleviate
the need for extensive ML or statistics
understanding.
With the right connectivity and feedback
loops, advanced analytics applications
are empowering process manufacturers
in the use of ML to achieve target
key performance indicators, and to preemptively
alert operations and maintenance
staff when anomalies are detected.
These measures provide increased operational
efficiency, enable optimal and
timely maintenance, and improve enterprise
safety and the bottom line.
NOTE
a Seeq's QSearch
ASHWIN VENKAT is the Senior
Principal Scientist and Team Lead
for the Advanced Analytics/
Machine Learning group at Seeq.
He has more than 20 yr of
experience developing,
implementing and commercializing
new analytics and ML technology. Prior to joining
Seeq, he served as an application architect for a
predictive analytics/ML startup. Dr. Venkat has also
served in roles at Shell and Chevron, both focused
on developing and implementing technology for
improving the performance of manufacturing assets.
Dr. Venkat earned a PhD in chemical engineering
from the University of Wisconsin, Madison.
SEPIDE ZAKERI is a Senior Applied
ML Scientist (Applications) at Seeq,
where she leads the development,
implementation and
commercialization of new analytics
and ML technology for the process
industries. Dr. Zakeri earned a
PhD in petroleum engineering from the University
of Tulsa in Oklahoma.
JOSEPH DISANTIS is a Senior
Applied ML Scientist at Seeq. He
has more than 15 yr of experience
working in research and
development with energy
companies to solve high-value
business problems by leveraging
time series data. Prior to joining Seeq, he developed
patented technologies at Marathon Oil Company
related to synthetic fuel production and drilling rig
control systems. DiSantis also has experience building
successful data science teams focused on applied
ML across the upstream domain.
ALEX JOHNSTONE is a Process
Engineer with 15 yr of experience
in the oil and gas industry. He has
worked in upstream operations in
California and the UK North Sea,
focusing on optimization and
continuous improvement. In his
current role, Johnstone is responsible for the
decarbonization of supply, positioning Ithaca
Energy as a leading low-carbon producer.
JIM MARTIN heads the Operational
Excellence Group at allnex. The
group assists allnex's plants in
decreasing energy consumption,
reducing waste generation,
improving asset reliability, increasing
non-capital production capacity,
and expanding into the world of digitalization.
He has worked for more than 25 yr in both direct
manufacturing roles and manufacturing support
roles. Martin earned a Bch degree in chemical
engineering from Rensselaer Polytechnic Institute,
and an MBA degree from Carnegie Mellon University.
Hydrocarbon Processing | OCTOBER 2022 63
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Hydrocarbon Processing - October 2022

Table of Contents for the Digital Edition of Hydrocarbon Processing - October 2022

Contents
Hydrocarbon Processing - October 2022 - Cover1
Hydrocarbon Processing - October 2022 - Cover2
Hydrocarbon Processing - October 2022 - Contents
Hydrocarbon Processing - October 2022 - 4
Hydrocarbon Processing - October 2022 - 5
Hydrocarbon Processing - October 2022 - 6
Hydrocarbon Processing - October 2022 - 7
Hydrocarbon Processing - October 2022 - 8
Hydrocarbon Processing - October 2022 - 9
Hydrocarbon Processing - October 2022 - 10
Hydrocarbon Processing - October 2022 - 10A
Hydrocarbon Processing - October 2022 - 10B
Hydrocarbon Processing - October 2022 - 10C
Hydrocarbon Processing - October 2022 - 10D
Hydrocarbon Processing - October 2022 - 11
Hydrocarbon Processing - October 2022 - 12
Hydrocarbon Processing - October 2022 - 13
Hydrocarbon Processing - October 2022 - 14
Hydrocarbon Processing - October 2022 - 15
Hydrocarbon Processing - October 2022 - 16
Hydrocarbon Processing - October 2022 - 17
Hydrocarbon Processing - October 2022 - 18
Hydrocarbon Processing - October 2022 - 19
Hydrocarbon Processing - October 2022 - 20
Hydrocarbon Processing - October 2022 - 21
Hydrocarbon Processing - October 2022 - 22
Hydrocarbon Processing - October 2022 - 23
Hydrocarbon Processing - October 2022 - 24
Hydrocarbon Processing - October 2022 - 25
Hydrocarbon Processing - October 2022 - 26
Hydrocarbon Processing - October 2022 - 27
Hydrocarbon Processing - October 2022 - 28
Hydrocarbon Processing - October 2022 - 29
Hydrocarbon Processing - October 2022 - 30
Hydrocarbon Processing - October 2022 - 31
Hydrocarbon Processing - October 2022 - 32
Hydrocarbon Processing - October 2022 - 33
Hydrocarbon Processing - October 2022 - 34
Hydrocarbon Processing - October 2022 - 35
Hydrocarbon Processing - October 2022 - 36
Hydrocarbon Processing - October 2022 - 37
Hydrocarbon Processing - October 2022 - 38
Hydrocarbon Processing - October 2022 - 39
Hydrocarbon Processing - October 2022 - 40
Hydrocarbon Processing - October 2022 - 41
Hydrocarbon Processing - October 2022 - 42
Hydrocarbon Processing - October 2022 - 43
Hydrocarbon Processing - October 2022 - 44
Hydrocarbon Processing - October 2022 - 45
Hydrocarbon Processing - October 2022 - 46
Hydrocarbon Processing - October 2022 - 47
Hydrocarbon Processing - October 2022 - 48
Hydrocarbon Processing - October 2022 - 49
Hydrocarbon Processing - October 2022 - 50
Hydrocarbon Processing - October 2022 - 51
Hydrocarbon Processing - October 2022 - 52
Hydrocarbon Processing - October 2022 - 53
Hydrocarbon Processing - October 2022 - 54
Hydrocarbon Processing - October 2022 - 55
Hydrocarbon Processing - October 2022 - 56
Hydrocarbon Processing - October 2022 - 56A
Hydrocarbon Processing - October 2022 - 56B
Hydrocarbon Processing - October 2022 - 56C
Hydrocarbon Processing - October 2022 - 56D
Hydrocarbon Processing - October 2022 - 56E
Hydrocarbon Processing - October 2022 - 56F
Hydrocarbon Processing - October 2022 - 56G
Hydrocarbon Processing - October 2022 - 56H
Hydrocarbon Processing - October 2022 - 57
Hydrocarbon Processing - October 2022 - 58
Hydrocarbon Processing - October 2022 - 59
Hydrocarbon Processing - October 2022 - 60
Hydrocarbon Processing - October 2022 - 60A
Hydrocarbon Processing - October 2022 - 60B
Hydrocarbon Processing - October 2022 - 60C
Hydrocarbon Processing - October 2022 - 60D
Hydrocarbon Processing - October 2022 - 60E
Hydrocarbon Processing - October 2022 - 60F
Hydrocarbon Processing - October 2022 - 61
Hydrocarbon Processing - October 2022 - 62
Hydrocarbon Processing - October 2022 - 63
Hydrocarbon Processing - October 2022 - 64
Hydrocarbon Processing - October 2022 - 64A
Hydrocarbon Processing - October 2022 - 64B
Hydrocarbon Processing - October 2022 - 65
Hydrocarbon Processing - October 2022 - 66
Hydrocarbon Processing - October 2022 - Cover3
Hydrocarbon Processing - October 2022 - Cover4
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https://www.nxtbook.com/nxtbooks/gulfpub/petrochemical_2018_v2
https://www.nxtbook.com/nxtbooks/gulfpub/petrochemical_2018
https://www.nxtbook.com/nxtbooks/gulfpub/hp_201812
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