The data processing system for a prover skid
The data processing system for a metering skid constitutes an integrated, automated, and intelligent measurement and control framework. At its core, it utilizes a closed-loop process-encompassing "Sensing – Computation – Control – Transmission – Management"-to achieve precise metering, real-time monitoring, and safety interlocking for fluid media such as natural gas and petroleum. Its complete operational logic is detailed as follows:
I. System Architecture: A Three-Tiered Collaborative Structure
Modern metering skid data systems typically adopt a "three-tier architecture" design:
Sensing Layer (Field Instrumentation): The system's "senses," responsible for raw data acquisition.
Control Layer (Core Controller): The system's "brain," responsible for data computation and logic control.
Application Layer (Monitoring Platform): The system's "hub," responsible for data visualization, remote management, and analysis.
II. Detailed Breakdown of the Complete Operational Process
1. Data Acquisition (Sensing Layer)
Core Task: To acquire real-time physical parameters of the fluid and the operational status of equipment.
Acquisition Devices:
Flowmeters: Turbine, ultrasonic, Coriolis mass flowmeters, etc., measuring instantaneous and cumulative flow rates.
Transmitters: Pressure and temperature sensors, acquiring pipeline pressure and media temperature data.
Auxiliary Instruments: Gas analyzers (measuring composition and calorific value), densitometers, water content analyzers, and valve status switches.
Signal Output: Converting physical quantities into standard electrical signals (4-20mA analog) or digital signals (RS485, HART, Modbus).
2. Signal Preprocessing and Transmission
Signal Conditioning: The controller (PLC/RTU) amplifies, filters, and isolates the acquired weak signals to eliminate interference.
Data Reading: Periodically polling and reading data from all instruments via a built-in protocol library (e.g., Modbus-RTU).
Local Caching: Temporarily storing data in the controller's internal memory or SD card to prevent data loss in the event of communication interruptions.
3. Core Computation and Compensation (Control Layer)
This constitutes the critical stage for ensuring metering accuracy:
Temperature and Pressure Compensation Calculation
Since gas volume is highly susceptible to variations in temperature and pressure, the system automatically converts the actual volumetric flow rate (at operating conditions) into a volumetric flow rate at standard conditions (20°C/0°C, 101.325 kPa), utilizing either the ideal gas state equation or the compressibility factor (Z). Formula: Qn = Q × (P/Pn) × (Tn/T) × Z
Mass / Energy Conversion
Incorporating gas composition data (e.g., methane content), calculates mass flow rate and energy flow rate (calorific value).
Accumulation and Statistics
Real-time calculation of daily, monthly, and annual accumulated flow volumes; records minimum, maximum, and average flow values.
4. Logic Control and Safety Interlocks
Automatic Control: Built-in PID algorithm adjusts the opening of the control valve based on setpoints to stabilize outlet pressure and flow rate.
Safety Protection (Anomaly Handling):
Overpressure / Underpressure: If pressure exceeds defined thresholds, the safety shut-off valve is immediately actuated.
Flow Anomalies: Sudden flow fluctuations, excessive flow velocity, or zero flow trigger an alarm and initiate a shut-down sequence.
Leaks / Instrument Faults: Detection of sensor failures or communication interruptions triggers audible and visual alarms, along with remote notifications.
5. Remote Data Transmission (Communication Layer)
Local Communication: The controller connects to an on-site HMI (touchscreen) via an RS485 bus for local data display and operation.
Remote Communication:
Wired: Ethernet (TCP/IP) connection to the plant's SCADA/DCS system.
Wireless: GPRS/4G/NB-IoT connectivity for uploading data to cloud servers or a central dispatch center.
Communication Protocols: Utilizes industry-standard protocols (Modbus-TCP, IEC 60870-104, MQTT).
6. Data Storage, Visualization, and Management (Application Layer)
Data Storage: A central server database (MySQL/PostgreSQL) provides long-term storage (≥1 year) for historical data.
Monitoring Interface (SCADA):
Real-time process flow diagrams, trend curves, and data reports.
Remote parameter adjustment, valve control, and equipment start/stop operations.
Reporting and Auditing: Automatically generates shift, daily, and monthly reports; supports data traceability and reconciliation.
Mobile Application: Management personnel can monitor system status and receive real-time alerts via a dedicated mobile app.
III. Typical Operational Sequence (Example: Natural Gas)
0 ms: Fluid flows through the flow meter; sensors generate pulse or electrical signals.
100 ms: The PLC acquires temperature, pressure, and flow signals, performing Analog-to-Digital (A/D) conversion. 200ms: Executes temperature and pressure compensation algorithms to calculate standard-condition flow rates.
500ms: Updates the local HMI display and checks for parameter limit violations.
1s: Transmits data packets to the cloud via the network.
Continuous: Accumulates flow totals, logs events, and responds to remote commands.
IV. Key Features
High Precision: Through algorithmic compensation, metering errors are typically maintained within a range of ±0.5% to ±1.0%.
High Reliability: Features unattended operation, autonomous execution, power-loss protection, and data redundancy.
High Safety: Incorporates multi-level alarms, interlocking safeguards, and an explosion-proof design (Exd II CT4).
Intelligence: Supports remote diagnostics, OTA updates, and big data analytics.
Summary
The data processing system of a metering skid functions, in essence, as an edge computing node. Operating autonomously at the industrial field site, it executes a fully automated workflow encompassing "data acquisition - precision computation - closed-loop control - safety protection - information uploading. It serves as a core piece of equipment for the energy sector-including oil & gas and natural gas industries-enabling the realization of digitalized, intelligent, and unmanned management.
