Introduction
The rate at which the field of Data Science and Analytics is
booming, business in every industry has developed data-led strategies for
overcoming problems and solving challenges. The oil and gas industries are no
different. With the global energy industry facing an onslaught of new
challenges, oil and gas companies no longer rely on techniques and technologies
of the past.
Analytics can optimize the activities associated with exploration
and production, including oilfield production forecasting, predictive asset
maintenance, reservoir characterization and analytics for unconventional
resource recovery.
One of the leading provider of Energy, Royal Dutch Shell, uses
big data to improve its operations and to increase oil and gas output of their
wells. Since a couple of years they have started lowering optical fiber cables
within their wells. These cables are supplied with sensors that measure everything
within the wells. With this data, Shell analysed how the wells are doing and
how much oil or gas is still left.
Shell is credited with producing about 2300 barrels of oil
every minute and transport fuel to 10 million retail customer daily. So far, it
has generated 46 Petabytes of data through its seismic sensors that are used to
discover new oil wells. Shell felt that they have a lot of data but very less
decision making ability. With this in mind, there was a recognition in the IT
function that Shell needs to adapt to predictive modelling and data forecasting
techniques. Shell is currently working with IBM and DreamWorks Hollywood to
achieve the data visualization. Although the analyses are done in the cloud
(AWS), the visualizations are immediately available to the crew working at the
local factory.
With the advent of Analytics in Shell, they have been able
to achieve an upliftment of 6%-8% in the production in terms of money (in Billions)
Data-Driven Oil
Fields
The search for new hydrocarbon deposits demands a huge
amount of materials, manpower and logistics. With drilling a deepwater oil
well often costing over $100 million, no one wants to be looking in the wrong
place.
Surveying of potential sites involves monitoring the low
frequency seismic waves that move through the earth below us due to tectonic
activity. Probes are put into the earth at the spot being surveyed, which will
register if the pattern of the waves is distorted as they pass through oil or
gas. Shell uses fibre optic cables (created in a special partnership with
Hewlett-Packard) for these sensors, and data is transferred to its private
servers (maintained by Amazon Web Services). This gives a far more accurate
image of what lies beneath. Data from any prospective oil field can then be
compared alongside that from thousands of others around the world, to enable
geologists to make more accurate recommendations about where to drill.
Asset Preventative
maintenance optimization
Various sources and forms of data, including basic
historical maintenance records and other information, can help operators detect
and diagnose the root causes of poor performance and limit unplanned downtime
of their machinery. By minimizing disruptions to production, or eliminating
them before they happen, operators can maximize maintenance resources and keep
production on schedule to meet financial goals
On some days, Shell assets generate no cash due to
unexpected events and turnarounds overruns resulting in maintenance cost
increase over the last few years. Old equipment that’s been in the field a long
time can break down and ruin the best plans for maximized recovery.
Shell uses predictive analysis to identify the most
effective set of maintenance activities and to create a means to decide which
activities can be safely re prioritised. Machinery used in drilling has to
operate in harsh conditions for prolonged periods of time so is prone to wear
and damage. To counteract this, the machinery is fitted with sensors collecting
data about its performance and comparing it with aggregated data, meaning parts
can be replaced in an efficient manner and downtime minimized, further reducing
overheads.
These are the few examples of what has been achieved, but there are speculations that there is so much more yet to be discovered with the help of this data. The possibilities are endless..!
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