Page 389 - Intelligent Digital Oil And Gas Fields

328 Intelligent Digital Oil and Gas Fields

quality of data, calibration, etc. He goes on to say that we will see a lot of
changes and innovation, such as smart sensors with self-calibration, self-
diagnostics, and self-diagnostics on the connectivity with other sensors,
and edge devices with analytics and collaboration. An important question
is: how much intelligence to put into each edge device with more intelli-
gence which feeds the cloud? There will be a lot of innovation in intelli-
gence in the edge devices for what data are actually transmitted to cloud
for storage. Predictive analytics is also coming in a big way for equipment
failure, scheduled maintenance, production analysis, and empowering
O&G operations to move beyond reaction.
Fig. 9.3 shows a schematic of how the data will be acquired and displayed
everywhere. The concept of “data lake” is being introduced to the data eco-
system. Currently, O&G companies mostly have data warehouses and struc-
tured and relational data for their master data stores, which have developed
over several decades. Transactional industries are transitioning to new archi-
tectures for Big Data and IIoT. A data lake stores data, both structured and
unstructured, in a form close to its native state, along with metadata char-
acteristics. This approach enables a much more flexible system for data access
by the many applications, analytics, machine learning, visualization, integra-
tion, etc. that need to access it. Seamless data will be required for the inte-
grated reservoir management discussed later.
Abdalla went on to discuss how the new generation will use much more
intuitive technology (software), simple to learn, with no training courses,
that is mostly self-guiding workflows. New platforms have “self-protecting”
workflows that alert or prevent users from making mistakes. “Apps” will be
sources for users to build their own workflows or use existing ones with ana-
lytics, for example, predictive maintenance and artificial lift optimization.
Currently, there is a gap to define protocols and standards across vendors.
IIoT needs a more structured protocol so devices can communicate with
each other, rather than one way to the cloud or data storage. Open standard
across companies will enable sensors (with “smarts”) to communicate among
themselves.

9.3 NEXT-GENERATION ANALYTICS

Kunal Dutta-Roy and Senthil Arcot of Technical Toolboxes, Inc.
(a global provider of integrated and cloud-based pipeline software and con-
sulting) describe how they see the future of analytics for artificial lift. Pumps
and well equipment will be monitored like a car, informing their owner that