Real-Time Stream Composition Prediction for Refinery Optimization
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Solution Overview
Problem
Current refinery operations rely on static feed reference characterizations for downstream process units, leading to sub-optimal solutions and non-robust behavior due to the lack of dynamically updated feed characterizations, which is particularly problematic for meeting stricter environmental regulations and optimizing petroleum product production.
Innovation Solution
The Rigorous On-Line Composition (ROC) method and system dynamically predict the detailed chemical composition of streams in real-time by using a database of current crude diets, RTO information, and analyzer inputs, allowing for accurate and detailed property calculations and updates, enabling more precise optimization of refinery operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static feed reference characterizations are used for downstream process units, then device complexity is reduced, but manufacturing precision and optimization accuracy deteriorate
Solution Approach 1:
The system transitions from static feed reference characterizations to dynamic, real-time feed characterizations by continuously updating the feed composition data as new crude oil arrives at the refinery. This dynamic approach allows the downstream process units to use current, accurate feed information rather than relying on outdated static references, thereby improving optimization accuracy without significantly increasing system complexity.
Solution Approach 2:
The system implements a feedback mechanism where actual feed composition data from upstream crude distillation is continuously measured and fed back to downstream process units. This feedback loop enables real-time adjustment of process parameters based on actual feed characteristics, improving manufacturing precision while maintaining manageable system complexity through automated data flow.
2Measurement precision
If detailed chemical composition analysis is performed in real-time, then measurement precision improves, but loss of time increases due to complex analysis requirements
Solution Approach 1:
The system performs preliminary action by maintaining a continuously updated database of feed characterizations from upstream crude distillation before downstream processing begins. This pre-computed compositional data is readily available when needed, eliminating the need for time-consuming real-time analysis while providing accurate measurement data for optimization decisions.
Solution Approach 2:
The system creates and maintains a digital copy of the feed composition data through virtual characterization models that replicate the physical crude oil properties. This virtual copy can be analyzed and distributed instantly without requiring physical sampling and laboratory analysis, thereby achieving high measurement precision without time loss.
3Adaptability or versatility
If static feed reference characterizations are used, then adaptability to changing crude compositions deteriorates, but device complexity remains low
Solution Approach 1:
The system implements dynamic adaptability by continuously updating feed characterization data as new crude oil compositions arrive at the refinery. This dynamic approach allows downstream process units to automatically adapt to changing crude compositions without requiring complex manual reconfiguration, achieving high versatility while keeping system complexity manageable through automated data flow.
Solution Approach 2:
The system uses feedback mechanisms to detect changes in crude composition and automatically adjust downstream processing parameters. The continuous flow of compositional data from upstream to downstream units creates a self-adjusting system that adapts to changing conditions without requiring complex control logic or manual intervention.
Data Source
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AI summary
The invention provides a method and means of predicting, in near real-time, the detailed chemical composition of major streams in a refinery, including those downstream from the crude distillation column (310) The dynamically updated feed characterizations can be derived in near real time from an assay database (ASSAY dB) of current crude diet, RTO information about upstream refinery units and various analyzer (431-434) inputs The chemical compositions of each stream are stored and updated in a plant wide database (210) A broad range of property calculations (220) can be ascertained, either automatically or on demand, from the compositional information An application permits users, such as operations, planning and engineering personnel (205A), to access the database directly or indirectly (e g, on line) This information is then used by each user to further optimize the operation of a given refinery unit and/or the plant as a whole.