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306 Intelligent Digital Oil and Gas Fields

led to a risk of surface events and well failures. The management of the sys-
tem required real-time production/injection pressure and temperature data
analytics for each well and analysis of surface tilt meter surveys. A key chal-
lenge was that much of this analysis was done manually: each morning
(7days per week), a production engineer was tasked with analyzing pdf
and spreadsheet reports and comparing it with the production and injection
data used to issue daily instructions on wells to direct field personnel.
The solution was an integrated system that displayed all the tilt meter,
fracture diagnostics, production, and injection data in one dashboard
(Eldred et al., 2015, Fig. 8.8). All stakeholders could then see all the data
in a unified environment. Production engineers, reservoir engineers, super-
visors, and field personnel collaborated on decisions on cycles; the decisions
were not dependent on a single engineer’s view at 6a.m., but benefited from
collaborative decisions from the stakeholders using real-time data through-
out the day (see next section). As in the other example, field personnel could
focus on the wells that required attention and do it more frequently (each
half-day). The asset reduced risk of well failure and maintained production
more consistently.

8.3 MANAGEMENT OF CHANGE
8.3.1 Collaboration in Practice: “A Day in the Life”
of a DOF Operation
Section 1.5 of Chapter 1 discussed how traditionally, disciplines involved in
the reservoir management value chain worked in discipline silos, with mul-
tiple manual data handoffs, use of different systems, and inefficient commu-
nication. Fig. 1.10 shows how a traditional organization of discipline silos
can be transformed into collaborative teams. Al-Jasmi et al. (2013) describe
how a work team in a CWE makes a decision in real time to change a well
operation (artificial lift pump settings) to increase oil rate.
With DOF, data is produced continuously and in real time. DOF systems
deliver continuous automated analytics of data and a continuous need for all
the asset team members, production, and operations, to collaborate and inter-
act on decisions that drive value. For example, consider an operation with
more than 1000 wells on artificial lift with treatment facilities for gas, oil,
and water that must be produced with minimum downtime, maximum
hydrocarbon production, and zero HSE incidents. Fig. 8.9 shows an example
of activity that continued on an operation throughout a 24-h period.