Real-time Dynamic Data Validation for Intelligent Wells
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Solution Overview
Problem
The oil and gas industry faces challenges with unreliable, invalid, and incomplete field data from intelligent field components, which can lead to suboptimal well performance and reservoir management decisions.
Innovation Solution
Implementing real-time dynamic data validation methods that combine multiple engineering logics to validate data from well instruments, detect anomalies, and trigger alerts for immediate action, while also estimating fluid production rates and recommending equipment calibrations to ensure reliable data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time dynamic data validation with multiple engineering logics is implemented, then data reliability is improved, but device complexity increases
Solution Approach 1:
The validation system is segmented into multiple independent engineering logic modules, each responsible for validating specific data parameters (pressure, temperature, flow rates, etc.). This modular approach allows the system to achieve comprehensive validation without creating a monolithic complex system, as each module can be developed, maintained, and adjusted independently.
Solution Approach 2:
The validation apparatus is designed to handle multiple types of field data from various intelligent field components (multiphase flow meters, permanent downhole monitoring systems, wellhead pressure and temperature devices, etc.) through a unified validation framework. This multi-functional design improves data reliability across different data sources while avoiding the need for separate validation systems for each component type.
2Productivity
If real-time dynamic data validation is implemented, then well performance optimization is improved, but loss of time in data processing increases
Solution Approach 1:
The system performs preliminary validation checks on incoming field data using pre-defined engineering logic rules and thresholds before the data is fully processed. This preliminary action identifies obviously invalid data early in the processing pipeline, allowing the system to quickly flag issues without requiring complete analysis of all data parameters, thus reducing overall processing time while maintaining optimization effectiveness.
Solution Approach 2:
The validation system provides real-time feedback on data quality and well performance metrics, enabling rapid decision-making and corrective actions. This feedback mechanism allows the system to continuously optimize well performance based on validated data without significant delays, as the feedback loop is integrated into the real-time data processing workflow.
3Measurement precision
If multiple engineering logics are combined for data validation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Multiple engineering logic validation rules are segmented into distinct, well-defined modules that each validate specific aspects of the field data (e.g., pressure range validation, temperature rate-of-change validation, flow rate consistency validation). This segmentation allows the system to achieve high measurement precision through comprehensive validation while managing complexity through modular organization and clear separation of validation responsibilities.
Data Source
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AI summary
Apparatus (30), computer readable media, and methods for managing an intelligent field, are provided. An exemplary method can include receiving real-time dynamic field data, analyzing validity of the dynamic field data, validating values of the field data, validating a state/condition of a well, and flagging well components, well conditions, and/or well state validation issues. An exemplary apparatus (30) can include hydrocarbon well instruments (40), a SCADA system, a process integration server and/or dynamic fieid data analyzing computer (31), and memory/computer readable media (35) storing a dynamic field data analyzing computer program (51). The computer program (51) can include instructions that when executed cause the dynamic field data analyzing computer (31) to perform yarious operations to include receiving real-time dynamic field, data, analyzing validity of the dynamic field data, validating values of the field data, validating a state/condition of a well, and flagging well components, well conditions, and/or well state validation issues.