Virtual Sensor Network for Fail-Safe Oilfield Control
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Solution Overview
Problem
Existing oil and gas exploration and production systems face challenges in achieving holistic oversight and management due to separate applications and data sets, lack of interoperability, unreliable physical sensors, and actuator failures leading to system inoperability.
Innovation Solution
Implementing a virtual sensor network with integrated virtual sensors and actuators, utilizing a uniform interface and deep learning for signal processing, and a hierarchical architecture of intelligent gateways, edge appliances, and corporate cloud for seamless data integration and fail-safe control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate oilfield applications are used for each activity, then each application can be specialized for its specific purpose, but interoperability and holistic system management are frustrated
Solution Approach 1:
The patent introduces a common data model and standardized interface framework as an intermediary layer between separate oilfield applications. This mediator enables data exchange and communication between specialized applications without requiring them to be merged, thus maintaining both specialization capability and system interoperability. The common data model acts as a universal language that translates between different application-specific data formats.
2Measurement precision
If physical sensors are used to measure and monitor physical phenomena, then direct measurements can be obtained, but the system becomes costly and unreliable due to sensor failure
Solution Approach 1:
The patent creates virtual copies of physical sensors through mathematical models and simulations. These virtual sensors replicate the measurement functionality of physical sensors but without the associated reliability issues and costs. The virtual sensors use data from multiple sources and computational algorithms to generate measurements that mirror what physical sensors would provide, thereby maintaining measurement precision while eliminating sensor failure risks.
3Ease of operation
If physical sensors and actuators are relied upon for control systems, then direct control can be achieved, but system inoperability occurs when sensors or actuators fail
Solution Approach 1:
The patent implements fail-safe mechanisms and redundancy planning before failures occur. Virtual sensors and actuators are prepared in advance as backup systems, and the control architecture is designed with fault tolerance. When physical sensors or actuators fail, the system can switch to virtual counterparts or alternative control pathways, preventing complete system inoperability. This prior cushioning ensures continuous operation despite component failures.
4Adaptability or versatility
If data replication is performed for each stakeholder group, then each group receives its own version of the data model, but data integrity and reconciliation issues cannot be controlled systematically
Solution Approach 1:
The patent establishes a feedback mechanism where changes to data models are tracked, communicated, and reconciled across all stakeholder groups. The system monitors data model versions and automatically notifies affected stakeholders of changes. This feedback loop ensures that all groups work with consistent, up-to-date data while still allowing for stakeholder-specific customizations, thereby maintaining data integrity alongside adaptability.
Data Source
AI summary
A method of managing oilfield activity with a control system is provided having a plurality of virtual sensors and integrating the virtual sensors into a virtual sensor network. The method includes determining interdependencies among the virtual sensors, obtaining operational information from the virtual sensors, and providing virtual sensor output to the control system based on the determined interdependencies and the operational information.