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The concept of the real-time enterprise is not new. Business success is driven by good

decisions, and timely access to high-quality data is critical to making the right calls at the
right time. Managing and sharing this data in the upstream industry is a relatively new
concept, and any companies are formulating or refining their strategies. This offers an
excellent opportunity to build from scratch rather than evolve incrementally through painful lessons. CERA has conducted an informal survey of the industry—both exploration and
production (E&P) firms and vendors—to gain an understanding of the various approaches
to real-time data management. This Special Report presents the findings of this survey,
identifying different approaches and delivering CERA’s perspectives on the key components
of successful solutions.

by Michael Wynne

InTRoDUCTIon

The concept of the real-time enterprise is not new. Business success is driven by good
decisions, and timely access to high-quality data is critical to making the right calls at the
right time. Managing and sharing this data in the upstream industry is a relatively new
concept, and any companies are formulating or refining their strategies. This offers an
excellent opportunity to build from scratch rather than evolve incrementally through painful lessons. CERA has conducted an informal survey of the industry—both exploration and
production (E&P) firms and vendors—to gain an understanding of the various approaches
to real-time data management. This Special Report presents the findings of this survey,
identifying different approaches and delivering CERA’s perspectives on the key components
of successful solutions.

Real-time data management is a key component of Digital Oil Field of the Future (DOFF)
implementation, providing the mechanism for capturing, storing, and distributing the data
that provide real-time asset awareness and support fast, accurate decision making. Initially
the focus is always on local asset–based use of the data for processes such as production
optimization. However, well-implemented real-time data management solutions enable
non–asset-based knowledge workers to access the data and create new or enhanced processes
(e.g., logistical planning, increased-frequency iterative reservoir simulations). For many E&P
firms right-time access to real-time data is a cornerstone to expanding and migrating their
organizational model to include expertise centralization, for example. The factors affecting
strategies for real-time data management include company size, asset distribution—according
to geography and age—resources, culture, and organization. The scope can be further
constrained by issues such as prohibited data transfer, whereby information may not leave
a country’s borders, which may force a particular strategy to be adopted.

In this report CERA reviews three key criteria for real-time data management strategies
identified during the research:

Architecture. • Design and selection of architecture involve variables such as legacy
hardware, infrastructure requirements, and primary data-consuming applications. This
demands partnership between the upstream business and upstream information technology
(IT) organization to create an effective supportable solution.

Ownership. • Real-time data management systems create a support burden. Research shows that it is important to decide at the outset who owns the solution and who
owns the data.

Standards. • CERA has found that extended discussions on standards frequently delay the initiative. Field-based equipment standardization is a frequent discussion topic that
CERA feels extends the scope of real-time data management solutions too far, since
attempting to dictate equipment standards to asset managers will in most cases be an
unpopular and unproductive initiative.

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