Drilling data often isn’t saved. It is simply discarded, foreclosing any opportunity to look for patterns that could
enable earlier problem detection and point the way toward better practices.
what data is required to realize that value,
and which analytics tools are best suited
to your goals? Only when those questions
have satisfactory answers can an enterprise move forward with confidence.
Many E&P companies have already
embraced business intelligence and other
analytics tools in their back offices, particularly for financial management and enterprise resource planning. But they are
significantly further behind in operations
technology. Many are using only rudimentary IT in the operations that define their
industry: exploring for oil and gas, developing reserves and managing production
for maximum lifetime value.
Drilling data, for example, is routinely
gathered in real time so that the rig can be
shut down if key measurements such as
torque on the drill pipe and bit, or pressure
in the mud circulation system, move outside of established limits. But this drilling
data often isn’t saved. It is simply discarded, foreclosing any opportunity to look for
patterns that could enable earlier problem
detection and point the way toward better
practices. So the starting point must be to
identify gaps in data capture and plug as
many of them as possible.
The next challenge is to minimize,
or at least significantly reduce, data
fragmentation. Typically, exploration, development and production departments
have maintained separate data repositories, each with its own data types. These
repositories may be further fragmented
geographically, for example, if companies
organize and store data on the basis of
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