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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 />

113

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