Oil and gas
companies have hundreds of thousands of miles of pipelines and infrastructure
in remote areas that they must survey, to ensure their infrastructure and
operations are secure.
A
technology known as geospatial analytics has been instrumental in helping these
companies locate events across these vast geographies in a timely manner,
ranging from potential leaks to encroachment from buildings and vegetation to
spotting chemicals on land and in water.
Geospatial
analytics is an efficient and cost-effective technology for oil and gas
companies, which allows for multispectral and hyperspectral imagery, gathered
from satellites, UAVs, planes and fixed cameras, to be analyzed in a process
that ultimately can provide both alerts and qualitative results for oil and gas
companies.
Geospatial
analytics allows customers to constantly monitor their infrastructure and then
render images of results into interactive displays, alerts and visualizations
that provide critical information quickly after data capture, facilitating
customer action.
Over
the past few years, the use of artificial intelligence (A.I.) and specific
algorithms have moved the technology of geospatial analytics to new heights — helping
organizations keep their infrastructure, the surrounding communities and the
environment safe.
As
the technology advances, so do its use cases.
Pressure
to eliminate methane emissions will increase in 2024. Today’s oil and gas and
energy companies need more sound data to locate small leaks that could
escalate.
Energy and oil
and gas companies are facing increased pressure to limit their methane
emissions, and, as such, these organizations are responding to demands from
investors who prioritize environmental responsibility alongside profit.
Additionally,
insurance and investment organizations face increased pressure from
shareholders to hold energy companies — such as those in oil and gas —
accountable for the perceived lack of performance on environmental issues.
While
many energy companies are working to shore up their infrastructure, to prevent
such events as methane leaks that can harm the environment and the communities
where their customers reside, newer approaches are required to locate smaller
and harder-to-detect issues.
In
2024, organizations must ensure their infrastructure is sound, which means
finding harder-to-detect issues. However, with infrastructure spread over
thousands of miles — often in remote locations — the ability to pinpoint an
issue or leak before it becomes a major event is extremely challenging.
A.I.-powered
geospatial analytics allows for the analysis of terabytes of data, producing
actionable alerts that help a company pinpoint potential issues and allowing
the company to limit negative consequences. A.I. offers the ability to analyze
data quickly, learn from misidentified threats and provide accurate early
warnings for energy companies.
For
example, methane measurement algorithms detect and measure plume concentrations
and flow rates, in addition to indicating the leak’s source, all with accuracy.
Early
detection and alerts — with specifics about location and severity — minimize
risk, ease environmental impacts, avoid escalating costs, and lessen the toll
of public exposure. Today’s technology can direct a company to the source of
the problem with specificity, saving time and money and directing valuable
resources to where their expertise is critical to resolution.
‘Forever
Chemicals’
“Forever chemicals,” including perfluoroalkyl and polyfluoroalkyl
substances (PFAS), and their effects on human and fauna health will be reported
with increasing frequency as more is learned about how widespread they are in
our environment and their specific negative effects on humans and other organisms.
Consumers
can find trace amounts of these chemicals in drinking water, beauty and home
products and more, including the linings of fast-food boxes, non-stick cookware
and fire-fighting foams.
The
persistence of forever chemicals in the environment and their prevalence
countrywide makes them a unique water quality concern. High concentrations of
PFAS may lead to adverse health risks in people, according to the U.S. Environmental Protection Agency (EPA).
A recent U.S.
Geological Survey found at least 45% of the nation’s tap water is estimated to
have one or more types of PFAS. As a result, the EPA released its proposed rule
seeking to set the first enforceable national drinking water standards for
PFAS.
In 2024, the
onus falls on the industries and organizations that have released these
chemicals to the environment to have better tools to detect the presence of
forever chemicals.
Organizations
need to be able to survey waterways and land for the presence of forever
chemicals. While an environmental scientist can go out and survey parts of a
waterway for these forever chemicals with a handful of test tubes, science
teams are not getting the whole picture, as these tests will not fully
determine the concentration of PFAS, its extent or its fate and transport in
the water or on soil.
Only recently
have A.I.-powered algorithms been developed to analyze satellite imagery and
accurately pinpoint traces of PFAS in soil and water. When organizations have
thousands of miles of waterways or land to test, a geospatial analytics approach
with A.I. is necessary.
Negative
Attention
Another major pipeline leak will again bring negative attention to an
already-constrained pipeline industry, resulting in increased federal and state
regulatory oversight. A.I.-powered geospatial analytics can stem the tide.
Given
the prevalence of oil and pipeline leaks in the past two years — wreaking havoc
on the environment and communities and costing the companies operating these
assets hundreds of millions of dollars — 2024 promises more pressure than ever
from regulatory agencies on oil and gas and utility companies.
The
Keystone pipeline, which spans 2,600 miles, leaked an estimated 14,000 barrels
of oil — more than half a million gallons — into a creek in Washington County,
Kansas, on Dec. 7, 2022. Many pipeline leaks start small. The Keystone oil
pipeline leak was found to be primarily due to a progressive fatigue crack that
originated during the construction of the pipeline.
One
of the major issues is that organizations have pipelines spread across remote areas
spanning hundreds and thousands of miles, making it difficult to regularly
monitor the infrastructure with traditional leak detection technologies, such
as SCADA systems, as these technologies are not optimized to identify smaller
leaks.
Unfortunately,
pipeline leaks are sometimes detected first by people working on the land. This
aspect adds to the negative press and public opinion toward these midstream
companies, making it increasingly difficult for them to accomplish the job of
energy transportation for our nation.
Today’s
satellite technology and geospatial analytics, powered by A.I., can be used for
the early detection, location and quantification of operational issues within a
company’s infrastructure.
Therefore,
it is time for pipeline operators to look to technology to help offset the
considerable challenges of having vast infrastructure that cannot always be
watched with the human eye. Oil and gas and utility companies need to utilize
these technologies to understand the state of their pipelines better.
The
upshot is that finding any event, such as a leak, in its infancy and locating
the source and extent of the risks is critical in minimizing costly
consequences. With A.I., geospatial analytics offers the ability to analyze
petabytes of data, comprising thousands of individual aerial or satellite
images, to detect events such as potential leaks.
Early
detection and alerts, with specifics about location and severity, minimize
risk, avoid escalating costs and impacts on the environment and lessen the toll
of public exposure. P&GJ