Real-Time Adaptive Control of Demulsifier Injection Using Self-Learning Artificial Intelligence Models
AssigneeSaudi Arabian Oil Company
InventorsAriffen Bin Adnan, Yuk San Man, Othman Taha
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Abstract
A computer-implemented method for real-time adaptive control of demulsifier injection using self-learning AI models is described. The method includes obtaining sensor data in a gas-oil separator plant and calculating demulsifier input parameters. The method also includes predicting process variables comprising at least water content and determining an injection rate in real time based on the predicted process variables.
Claims20
A computer-implemented method for real-time adaptive control of demulsifier injection using self-learning AI models, the method comprising:
- obtaining, with one or more hardware processors, sensor data in a gas-oil separator plant (GOSP);
- calculating, with the one or more hardware processors, demulsifier input parameters;
- predicting, with the one or more hardware processors, process variables comprising at least water content;
- and
- determining, with the one or more hardware processors, an injection rate in real time based on the predicted process variables.
An apparatus comprising a non-transitory, computer readable, storage medium that stores instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
- obtaining sensor data in a gas-oil separator plant;
- calculating demulsifier input parameters;
- predicting process variables comprising at least water content;
- and
- determining an injection rate in real time based on the predicted process variables.
A system, comprising:
- one or more memory modules;
- one or more hardware processors communicably coupled to the one or more memory modules, the one or more hardware processors configured to execute instructions stored on the one or more memory models to perform operations comprising:
- obtaining sensor data in a gas-oil separator plant;
- calculating demulsifier input parameters;
- predicting process variables comprising at least water content;
- and
- determining an injection rate in real time based on the predicted process variables.
Dependencies are inferred from the claim text.