Oil and gas production handbook An introduction to oil ... - ABB Group
Oil and gas production handbook An introduction to oil ... - ABB Group
Oil and gas production handbook An introduction to oil ... - ABB Group
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• Flowline control <strong>to</strong> stabilize multiphase flow in gathering systems,<br />
risers <strong>and</strong> flow lines.<br />
• Well control that will stabilize <strong>and</strong> optimize <strong>gas</strong> lift <strong>and</strong> naturally<br />
flowing wells. This application should prevent flow <strong>and</strong> pressure<br />
surges while maintaining minimal backpressure <strong>and</strong> maintain<br />
maximum <strong>production</strong> as well as continuing <strong>production</strong> at the<br />
optimum lift <strong>gas</strong> rate.<br />
• Gas-lift optimization is provided <strong>to</strong> ensure the best possible<br />
distribution of lift-<strong>gas</strong> between <strong>gas</strong> lifted wells.<br />
• Slug management helps mitigate variations in inflow impact. The<br />
separation <strong>and</strong> hydrocarbon processing during startup, upset <strong>and</strong><br />
normal operation.<br />
• Well moni<strong>to</strong>ring systems (WMS) are used <strong>to</strong> estimate the flow rates<br />
of <strong>oil</strong>, <strong>gas</strong> <strong>and</strong> water from all the individual wells in an <strong>oil</strong> field. The<br />
real-time evaluation is based on data from available sensors in the<br />
wells <strong>and</strong> flow lines.<br />
• Hydrate prediction <strong>to</strong>ols help <strong>to</strong> avoid hydrate formation, which may<br />
occur if a subsea gathering system is allowed <strong>to</strong> cool down <strong>to</strong>o much<br />
before the necessary hydrate preventive actions are performed.<br />
• Optimal operation is defined by a set of constraints in the wells <strong>and</strong><br />
<strong>production</strong> facilities. A constraint moni<strong>to</strong>ring <strong>to</strong>ol moni<strong>to</strong>rs the<br />
closeness <strong>to</strong> all constraints. This provides decision support for<br />
corrective actions needed <strong>to</strong> move current operation closer <strong>to</strong> its true<br />
potential.<br />
• Advanced control <strong>and</strong> optimization solutions <strong>to</strong> improve the<br />
performance of product quality control, while adhering <strong>to</strong> operating<br />
constraints. This is typically done with two technologies: model<br />
predictive control <strong>to</strong> drive the process closer <strong>to</strong> operating targets,<br />
<strong>and</strong> inferential measurement <strong>to</strong> increase the frequency of product<br />
quality feedback information.<br />
• Tuning <strong>to</strong>ols are designed <strong>to</strong> optimize <strong>and</strong> properly maintain the<br />
optimal setting of control loops in the process au<strong>to</strong>mation system.<br />
8.2.3 Asset optimization <strong>and</strong> maintenance support<br />
<strong>An</strong> asset optimization (AO) system reduces costly <strong>production</strong> disruptions by<br />
enabling predictive maintenance. It records the maintenance his<strong>to</strong>ry of an<br />
asset <strong>and</strong> identifies potential problems <strong>to</strong> avert unscheduled shutdowns,<br />
maximize up-time <strong>and</strong> operate closer <strong>to</strong> plant <strong>production</strong> prognoses. This<br />
functionality supports maintenance workflow as the AO system<br />
communicates with a maintenance system, often denoted as a computerized<br />
maintenance management system (CMMS).<br />
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