Flow Meter Prover Anomaly Detection via Multi-Path Volume Segmentation
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Solution Overview
Problem
Existing flow meter proving systems face inaccuracies due to variations in fluid characteristics and operational conditions, leading to potential malfunctions and errors in meter factor calculations, which can result in significant errors in hydrocarbon measurements.
Innovation Solution
A system utilizing four detectors and a data acquisition and monitoring system to measure volumes between different detector pairs, calculate uncertainty ranges, and identify anomalies by comparing measured volumes with true volumes, initiating recalibration when anomalies are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional two-detector proving systems are used, then device complexity is reduced, but measurement precision deteriorates due to inability to detect anomalies
Solution Approach 1:
The proving system is segmented into multiple measurement paths by adding detectors D2 and D4, creating four volume measurements (Va, Vb, Vc, Vd) instead of one. This segmentation allows cross-validation of measurements and anomaly detection, improving measurement precision while adding manageable system complexity
Solution Approach 2:
The additional detectors D2 and D4 act as intermediaries that provide alternative measurement paths. By introducing these intermediary sensing points, the system can compare multiple measurements of the same physical quantity (prover volume) and identify anomalies through discrepancy analysis
2Reliability
If four detectors are used to measure multiple volumes, then measurement precision improves through anomaly detection, but device complexity increases
Solution Approach 1:
The system implements feedback by calculating the relationship Va+Vb-Vc-Vd and comparing it against expected values. This feedback mechanism allows the system to self-diagnose anomalies and trigger alerts or recalibration, improving reliability while keeping the complexity manageable through automated decision-making
Solution Approach 2:
The proving system performs self-validation by using its own multiple measurements to detect anomalies. The system automatically identifies when measurements are inconsistent and can trigger self-correction procedures, reducing the need for external monitoring and improving reliability
3Measurement precision
If uncertainty calculations are performed, then measurement precision is maintained within acceptable ranges, but loss of time increases due to additional calculations
Solution Approach 1:
Uncertainty calculations and anomaly detection are performed automatically as part of the standard proving process rather than as separate post-processing steps. By integrating these calculations into the real-time data acquisition flow, the system maintains measurement precision without significant time penalty
Data Source
AI summary
A system for identifying an anomaly in flow meter proving equipment includes four detectors D1, D2, D3, and D4. A data acquisition and monitoring system is configured to signals from D1, D2, D3, and D4 to measure flow volumes between D1 and D3 as a measured volume Va, between D2 and D4 as a measured volume Vb, between D2 and D3 as a measured volume Vc, and between D1 and D4 as a measured volume Vd. The data acquisition and monitoring system calculates Va+Vb−Vc−Vd plus a max uncertainty as an upper range value and Va+Vb−Vc−Vd minus the max uncertainty as a lower range value. The data acquisition and monitoring system identifies an anomaly in response to the upper range value being less than zero or the lower range value being greater than zero and initiates recalibration of the prover in response to the identifying of the anomaly.