Hydrocarbon Processing - April 2021 - GP-36

DIGITALIZATION

FIG. 6. An integrated, intelligent gas gathering and processing super system, combining smart
gas plants with digital pipelines.1

FIG. 7. A smart gas plant configuration from digital twin asset template building blocks.

Real-time operational data infrastructure. The real-time operational

infrastructurea is an agnostic, open, scalable and reliable technology specifically
designed for critical operations. It enables
several key functionalities:
* Secure integration of time-series
operational data from DCS,
supervisory control and data
acquisition (SCADA) and Industrial
Internet of Things (IIoT) systems
* Abstraction of diverse tag
and asset names into a
standard company lexicon
* Integration of metadata, including
engineering data and the
maintenance management system
* Normalization of units of measure,
time zones and descriptions
* Configuration of traditional
operational applications,
such as energy management,
environmental compliance
and KPI-driven dashboards
36

MARCH/APRIL 2021 | GasProcessingNews.com

* Use of a " layers of analytics "
framework and strategy providing
the analytics foundation via
descriptive, diagnostic and simple
predictive analytics.
No-code digital twins. A digital twin is

a replica of a physical asset, such as a heat
exchanger, a pump or a compressor comprising attributes, calculations, KPIs, empirical correlations and models of varying
complexity. Contrary to the present hype,
digital twins have been around since the
1960s. However, today's operationally focused digital twins are dramatically more
robust and sophisticated in their ease of
use, approach and capability to develop,
evolve and leverage in a smart gas plant.
Most digital twins require information technology (IT), data scientists,
machine learning, model integration and
coding. They also have a limited ability to
deal with data volume, velocity, variability and anomalies. They are difficult to

scale and struggle to address the anomalies of physical assets that have variability in vintage, make, model and level of
instrumentation. Furthermore, real-time
operational data and asset metadata (i.e.,
static information like equipment model
and location) typically reside as tags in
control systems, as well as in other databases and platforms, with accessibility
issues and lack of naming standards limiting access to critical data that could potentially be leveraged to gain insight.
However, one operations-focused
digital twin technologyb has access to
this required data with the ability for the
SMEs to configure replicas of their gas
plant components, such as columns, heat
exchangers, pumps, compressors and
air coolers in an agile, evolutionary way.
These no-code digital twins rely on digital
asset templates and can be combined like
LEGO blocks to form a comprehensive
digital representation of physical gas plant
and gathering and processing system, using drag-and-drop capabilities (FIG. 7).
The digital operational infrastructure can enable asset anomaly detection
by empowering the SME to create or
modify anomaly expressions and then
test the expressions by backcasting-i.e.,
running the expression back into the operational history. Once satisfied with the
expression, the SME can then forwardcast this modified expression or event
detection algorithm to other assets that
utilize the same digital twin template.
This powerful capability enables continuous improvement of calculations, expressions and event analytics over time,
as well as comparison of similar expression results, KPIs or events as part of the
diagnostic process.
To be able to address the variances in
equipment type, make and vintage, the
digital twin templates must contain subtemplates or derived templates to capture
these deviations from the base template.
In the digital twin templates, the attributes
are placeholders for the actual, asset-specific values that are mapped once when
the template is applied to an actual asset.
A real-world data infrastructurea with
no-code digital twin technologyb now
operates across DCP Midstream, one of
the largest midstream operators in North
America. DCP Midstream has numerous
gas plants, fractionation units and other
midstream assets, including thousands
of associated heat exchangers, pumps,

http://www.GasProcessingNews.com

Hydrocarbon Processing - April 2021

Table of Contents for the Digital Edition of Hydrocarbon Processing - April 2021