National Gas
Transmission owns and operates the National Transmission System (NTS) in the UK
and is working to play a leading role in the transition to a clean energy
future.
National Gas
Transmission, through Project Union, intends to repurpose approximately 1,243
miles (2,000 km) or 25% of the UK’s gas transmission pipelines by the early
2030s, creating a hydrogen “backbone” for the UK that connects to the European
Hydrogen Backbone.
The NTS
consists of more than 4,722 miles (7,600 km) of pipelines with diameters
ranging from 4-inch to 48-inch (100 mm to 1,200 mm). Installation dates range
from the late 1960s to the present, with 45% of the total network by length
installed in the 1970s.
Pipelines Repurposing
To repurpose
existing natural gas assets to hydrogen service, operators must conduct
assessments to appraise their suitability and, once repurposed, implement
effective integrity management programs to ensure continued safe operation.
These processes require a robust understanding
of pipeline properties, risks, and susceptibility to integrity threats.
Hydrogen service also drives the need for new datasets to be established or
expanded, for example a particular focus on material performance in hydrogen
environments.
For many
pipelines, integrity management is currently based on secondary data, often no
longer supported by high-quality or traceable records.
National Gas
Transmission aims to re-establish high-quality data for such assets to ensure
that repurposing assessments and future integrity management programs are based
on accurate, complete and evidence-based data. The ambitious timescales planned
for hydrogen repurposing mean that there is an urgent need for the relevant
data to be established.
This article explores the approach
taken by National Gas Transmission, supported by ROSEN, to:
Efficient Data Processes
National Gas
Transmission has extensive records, including original documentation from
construction back to the 1960s and 70s. However, most of these records are
archived in paper copies or microfiche films. Identifying a certain document
for a specific asset from archived records is challenging, taking considerable
time and manual effort.
This project is
developing an efficient and reliable process centered around automated tools to
extract data from scanned records and use this data to populate a geodatabase
for pipelines and related assets. The result is a complete dataset with full
traceability evidenced by hyperlinks to supporting documentation.
This process
centres around three main solutions:
Value of GIS
Solutions
Geographic
Information Systems (GIS) provide a solution that combines a detailed database
model with mapping of assets. Pipelines and other assets can be represented by
both spatial and linear referencing and detailed data can be aligned to the
assets with full granularity.
For
pipelines, in-line inspection (ILI) provides direct mapping down to the level
of individual pipes, components and welds. Although ILI does not capture data
on above-ground installations (AGIs) a spatial representation of such assets can
be facilitated by overlaying detailed drawings and aligning reference points
with satellite imagery (Figure 2).
Wide-ranging
extensions to the default Utility Pipeline Data Model (UPDM) schema were made to
capture the datasets needed for hydrogen repurposing.
Each data
entry is also accompanied by a simple classification according to the confidence
level in the data and its suitability for use in repurposing assessments. The
schema also adds the capability to reference applicable documentation, via
direct hyperlinks, to evidence the sources of data.
Representing
the data in this manner is an effective way to appraise the full range of
relevant information for a specific asset, including information on the
pipeline route, material properties and integrity threats. The functionality to
easily query and summarise data is incorporated using Structured Query Language
(SQL) within ArcGIS.
The use of
dashboard views (Figure 3), provides an impactful overview of the data over
the full asset or a selected segment. In this example, the pipeline is represented
with open circles showing girth welds and coloured circles showing the
locations of metal loss and geometrical anomalies integrated from in-line
inspection (ILI) data.
Charts are also
used to provide a summary of the number of integrity threats, anomaly sizes,
and their distribution along the pipeline for the selected segment.
Automated
Data Extraction
A pipeline
segment with a length of, say, 30 miles (50 km) will contain several thousand
individual pipes, components and welds. Pipelines typically include multiple
different areas of construction, attributes, and properties, resulting from
design requirements and modifications that accumulate over time. This often
results in a significant task to align and quantify data with high confidence.
Numerous
types of records must be reviewed to achieve complete data suitable for the
detailed engineering and risk assessments required to evidence suitability for hydrogen
repurposing. This project is assessing data from a wide range of sources,
including:
Although
automated solutions are not always necessary, there are several cases where
automation offers a substantial saving in time and manual effort, as well as
reducing errors in data entry.
One of the
clearest examples is in matching construction records with the supporting
manufacturing documentation. The bar chart construction record extract (Figure
4) details the pipe grade and wall thickness for each pipe, as well as the “cast”
or “heat” numbers associated with each of the several thousand pipes used to
construct this pipeline segment. Optical character recognition (OCR) and
automated scripts have been developed to extract these records into a digitised
listing.
Manually
identifying the manufacturing records for these heat numbers from an
unstructured collection of thousands of scanned records is a significant task.
However,
automation leveraging optical character recognition (OCR) and automated scripts
can match the applicable records and populate hyperlinks to these against the
digitised listing of pipes and components from construction records.
An engineer
then checks the extracted data to ensure correctness and completeness. Once the
review is complete, the listing is directly published to ArcGIS, using scripts
to populate the database schema from the spreadsheet.
Advanced
Inspections
Despite
thorough records searches, there will inevitably be data gaps. Hydrogen service
also drives the need for new datasets to be established or expanded. In
particular, there is a focus on material properties in hydrogen gas
environments, as well as the increased risk posed by the possible presence of
cracks and crack-like defects.
To address
these data requirements, a comprehensive inspection campaign using advanced
in-line inspection (ILI) technologies has been completed for a 30-inch (750 mm),
22-mile (36-km) pipeline segment intended for hydrogen repurposing by National
Gas Transmission, with inspection of further pipeline segments intended over
the coming years as aligned with the overall hydrogen strategy.
The
inspection incorporated the following advanced ILI services:
The definition
of “populations” through the RoMat PGS service provides a clear breakdown of
the pipeline into groups of pipes with the same grade, manufactured to the same
process, and therefore possessing similar properties.
These
populations provide a foundation upon which the findings of the inspection
scope can be aligned in combination for this pipeline segment (Table 1).
Note that the reported anomalies, particularly the potential crack-like
anomalies and hardness anomalies, may require validation to confirm the nature
of the features and ILI performance.
The data
required to support the assessment of these identified integrity threats have
been gathered using the information extracted from records and stored within
the geodatabase in the process detailed earlier in this article. Where data
does not have a sufficient confidence level or is not available, the need for
further inspection and testing becomes clear.
In
particular, in cases where potential cracks or crack-like anomalies are
identified within specific populations, toughness data can be specifically
gathered from the affected population(s) to support engineering calculations.
Bringing It All Together
This project
has created efficient processes and tools to extract data from physical records
and existing registers using automated processes. To add to existing data, a
scope of advanced in-line inspection (ILI) was defined and completed on the
first pipeline segment intended by National Gas Transmission for hydrogen
repurposing.
These
combined data have been integrated within an extended geodatabase structure,
aligned with mapping of pipelines and related assets with full granularity down
to individual pipes, components, and welds. This brings together information on
the pipeline route, material properties, and integrity threats in a single
system, enabling efficient management and interrogation of data.
Following
these processes, future hydrogen repurposing assessments will benefit from
complete information supported by direct links to data sources to evidence
compliance.
The automated
tools developed will accelerate the processes to achieve robust datasets essential
to fully representative engineering and risk assessments, and the data will support
effective integrity management programs for the remaining life of the pipeline. P&GJ