Page 397 - Intelligent Digital Oil And Gas Fields

The Future Digital Oil Field 335

9.5 KNOWLEDGE EVERYWHERE: KNOWLEDGE CAPTURE
AND PEOPLE RESOURCES
9.5.1 Capturing Knowledge in New Ways
DOF systems require new ways of working and are leading to new careers.
In the past 5 years, a career as a data scientist (with titles such as chief data
scientist, chief computational scientist) has become mainstream in both large
and small O&G companies and in the service industry. This relatively new
role that began in the IT Department a decade ago in many organizations has
moved into the operations and business units. Engineers in operations are
being tasked with learning and performing data analytics and statistics,
“data-driven production optimization,” and are increasingly coming from
that background and training. This role is necessary because of the use of
ubiquitous data as described above and the use of new technology to analyze
and use the data. The increasing trend of data science is likely to grow as
other conventional roles in the field decline.

9.5.2 Delivering DOF to the Business
Introduction of DOF systems is also bringing innovations to the delivery
model. Terms such as data acquisition as a service, analytics as a service, data
management as a service, communication as a service, and intervention as a
service are entering the industry lexicon. This delivery of services as needed
might be called the “Uberization” of many inputs to the decision chain for
which DOF is a complex integration of services. Edge sensors (with internal
analytics) are being installed and interconnected (IIoT) by service providers
on a unit cost basis. Operating companies will not “own,” that is, capitalize,
the sensors, communications, Big Data storage, etc. Even analytics will
become a service, for example, Microsoft’s Azure model.

9.6 INTEGRATED RESERVOIR DECISIONS
9.6.1 Big Data and Big Models

To improve production forecast accuracy and better decisions to enhance
O&G recovery, Big Data should be integrated in the future into large reser-
voir models. There is no official definition for big reservoir models, but we
can understand big models as those high definition/resolution 3D gridded
models that preserve the geological heterogeneity and fluid properties in cells
with fine resolution. Today, technology is available to manage massive data,
more than 100 TB, and soft-computing hardware and high-performance