Multilateral Well Digital Twin for Virtual Zonal Production Profiling
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Solution Overview
Problem
Multilateral wells with electric submersible pumps and integrated completions are notoriously difficult to optimize or operate due to challenging flow characteristics, requiring extensive testing and frequent reconfiguration of inflow control valves (ICVs) in response to changing production conditions, which is time-consuming and often impractical for human operators.
Innovation Solution
A production digital twin system is employed to generate a model of a multilateral well, calibrated using historical data, which updates with real-time measurements to provide virtual zonal production profiles, enabling an optimizer to adjust valve settings and pump operations for optimal production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If extensive testing and frequent reconfiguration of inflow control valves is performed to optimize production, then production optimization is achieved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary calibration using historical data to establish the relationship between valve settings and production profiles before actual optimization is needed. This pre-established model enables rapid prediction and adjustment without requiring extensive real-time testing, thus achieving production optimization while minimizing time consumption.
Solution Approach 2:
The system creates a virtual copy (digital twin) of the wellbore production system that replicates the physical system's behavior. This virtual model allows for simulation and optimization experiments to be conducted in the digital domain, eliminating the need for time-consuming physical testing and reconfiguration of actual valves while still achieving production optimization goals.
2Ease of operation
If manual monitoring and adjustment of production conditions is performed, then operational control is maintained, but responsiveness to changing conditions deteriorates
Solution Approach 1:
The system implements continuous feedback loops where production data is automatically collected, analyzed, and used to adjust valve settings in real-time. This automated feedback mechanism maintains operational control while dramatically improving responsiveness to changing production conditions compared to manual monitoring and adjustment processes.
Solution Approach 2:
The optimization system performs self-adjustment by automatically analyzing production data and modifying valve configurations without human intervention. This self-service capability enables the system to respond immediately to changing conditions while maintaining operational control, eliminating the delays inherent in manual processes.
3Measurement precision
If frequent retests are conducted to verify production optimization, then accuracy is improved, but operational efficiency deteriorates
Solution Approach 1:
The system uses the virtual digital twin model to perform virtual verification and validation of optimization results before implementing changes in the physical system. This digital verification process provides accurate assessment of optimization effectiveness without requiring frequent physical retests, thus maintaining measurement precision while preserving operational efficiency.
Solution Approach 2:
The system performs preliminary virtual testing and validation in the digital model to ensure optimization accuracy before actual implementation. This pre-verification approach reduces the need for frequent post-implementation retests in the physical system, maintaining accuracy while improving operational efficiency by minimizing disruption to production operations.
Data Source
AI summary
A production digital twin system may generate a model of a wellbore. A production digital twin system may use historical data, calibrating the model. A production digital twin system may receive an updated total production profile from one or more sensors located at a surface of the wellbore. A production digital twin system may update the model with the updated total production profile. A production digital twin system may generate, using the model, a virtual zonal production profile for each of the plurality of lateral production zones, the virtual zonal production profile based on a total production profile.