Real-time System Control via Digital Twin for SAGD Well Fault Prevention
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Solution Overview
Problem
Existing system control methods are ineffective in preventing faults and reducing output in complex systems like oil production for steam assisted gravity drainage (SAGD) wells, as they rely on historical data and operator experience, leading to economic losses and equipment damage due to delayed fault detection and remediation.
Innovation Solution
A real-time engineering analysis based system control apparatus that uses digital models to continuously monitor and predict potential faults, applying self-calibration and self-learning algorithms to adjust operations and prevent output reduction by analyzing real-time data and simulating hypothetical scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring and prediction systems are implemented, then fault detection capability and system reliability are improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent creates a digital twin (virtual model) that copies the physical SAGD well system, allowing real-time monitoring and fault prediction without adding physical sensors or equipment to the actual system. The digital twin replicates system behavior through mathematical models, enabling complex analysis while keeping the physical system simple.
Solution Approach 2:
The patent replaces physical monitoring equipment and manual analysis with computational models and algorithms. Instead of using additional physical sensors and mechanical monitoring devices, the system uses software-based digital twins, machine learning algorithms, and computational fluid dynamics to perform monitoring and fault detection.
2Loss of time
If historical data and operator experience are used for control decisions, then system operation is simple, but fault response is delayed causing economic losses
Solution Approach 1:
The patent performs preliminary actions by continuously running digital twins that predict future system states and potential faults before they occur. The system proactively identifies anomalies and recommends corrective actions in advance, allowing operators to prevent faults rather than react to them after detection.
Solution Approach 2:
The patent implements continuous feedback loops where real-time well data is fed into digital twin models, which then provide feedback on system health, predicted faults, and optimal control recommendations. This closed-loop feedback system enables rapid response to changing conditions without requiring high levels of operator expertise.
3Productivity
If digital twins and real-time simulations are used, then operational optimization is improved, but computational energy and processing requirements increase
Solution Approach 1:
The patent applies partial action by running digital twin simulations at different levels of detail and frequency based on system needs. Critical parameters are simulated in real-time with high fidelity, while less critical parameters use coarser models or historical data, reducing overall computational burden while maintaining optimization benefits.
Solution Approach 2:
The patent uses periodic action by updating digital twin simulations at strategically determined intervals rather than continuously. The system monitors when updates are most valuable and schedules computational resources accordingly, performing intensive simulations only when needed for decision-making while using lighter monitoring between updates.
Data Source
AI summary
According to examples, system control may include accessing a plurality of procedures to control an operation of a system to prevent an occurrence of a fault in the system and/or a reduction of an output of the system. A highest ranked procedure may be learned from the plurality of procedures to control the operation of the system to prevent the occurrence of the fault in the system and/or the reduction of the output of the system. Real-time data associated with the system may be accessed. Further, the operation of the system may be controlled by applying the highest ranked procedure to prevent the occurrence of the fault in the system and/or the reduction of the output of the system.