Page 208 - Intelligent Digital Oil And Gas Fields

162 +Gains A B Manual System. Offline process. High level of
Intelligent Digital Oil and Gas Fields

Production performance with and without DOF −Loses Sustained gains C Automated but nonoptimized system. Online
downtime production. Human Intervention. 24
hours delays in response
process. Human intervention for controls.
Automated and optimized system. Online process.
Human intervention for controls
D
Automated and optimized system with smart
control process connected to loT. Online process.
Automated control with human supervision.

Time in months
Fig. 5.7 Comparison of different levels of automated workflows in DOF. The production
benefit of DOF implementation over manual process (A) is observed. There are DOF with
automated workflows but nonoptimized (B), automated workflows with optimized sys-
tem (C) but controlled by engineers and an automated-optimized system and self-
controlled by smart operation (D).

5.2.6 The Ten Essential Steps to Build the Back End
of an Automated Workflow
In software architecture the back end is defined as a task incorporated as
algorithm in a programming script or language which is able to automate
the entire workflow process, that is, from A to Z. The back end process
also is focused on data transmission, data transformation, data security and
accessibility, and backup system. Fig. 5.8 describes the 10 most important
steps to design the back end of an automated workflow using a web user
interface (UI).
Step 1: Understand the current manual process. Ideally, existing manual pro-
cesses will be documented. But if not, then it is critical to first document
them because it will be very difficult to automate a process until under-
standing how engineers execute current state process. It is very important
to specify the purpose, inputs, outputs/results, dependencies, decisions,
and process flow. The most useful way to document a process is a flow
chart, which shows objects and actions, and an organigram, which shows