Pipeline Constriction Detection via Fiber-Optic Temperature Anomalies
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Solution Overview
Problem
Detecting and locating constrictions in pipelines, such as those caused by solid deposition or mechanical damage, is challenging due to the reliance on conventional data collection and trial-and-error methods, which can lead to delayed detection and potential pipeline shutdowns.
Innovation Solution
A pipeline system equipped with a fiber-optic distributed sensor and a hydraulic flow model that compares measured temperatures along the pipeline to predicted temperatures, using pressure and flow rate inputs to detect temperature anomalies and identify constriction locations, enabling early detection and remediation of issues like hydrate formation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional data collection and trial-and-error methods are used to detect constrictions, then detection can be performed with simple equipment, but detection time is delayed and reliability is reduced
Solution Approach 1:
The patent replaces conventional mechanical inspection methods (intelligent pigs) and trial-and-error diagnostic approaches with a physics-based hydraulic flow model that uses temperature measurements from distributed fiber-optic sensors to detect and locate constrictions in real-time, significantly improving both detection reliability and speed
Solution Approach 2:
The patent introduces temperature as an intermediary parameter to detect constrictions. By measuring temperature anomalies along the pipeline using distributed fiber-optic sensors and comparing them against the hydraulic flow model predictions, the system can indirectly detect constrictions without direct mechanical inspection
2Measurement precision
If intelligent pigs with sensors are used to detect constrictions, then measurement precision can be improved, but device complexity and operational disruption increase
Solution Approach 1:
The patent makes the distributed fiber-optic temperature sensing system multi-functional by using it for both pipeline temperature monitoring and constriction detection. The same infrastructure serves dual purposes, eliminating the need for separate intelligent pig systems while maintaining detection precision
Solution Approach 2:
The patent replaces the complex mechanical intelligent pig system with a simpler distributed fiber-optic sensing system combined with a hydraulic flow model, achieving comparable or superior measurement precision without the operational disruption and complexity of mechanical inspection devices
3Productivity
If conventional data collection methods are used, then equipment simplicity is maintained, but productivity and early detection capability are reduced
Solution Approach 1:
The patent implements continuous monitoring of pipeline temperature using distributed fiber-optic sensors, allowing for real-time detection of constrictions and enabling continuous optimization of pipeline flow management, thereby improving productivity through uninterrupted surveillance
Solution Approach 2:
The patent establishes a feedback loop where temperature measurements from distributed fiber-optic sensors are continuously compared against predictions from the hydraulic flow model, allowing for real-time detection and response to constrictions, improving pipeline flow management efficiency
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for rapid and reliable detection of constrictions, reducing the risk of pipeline shutdowns and production losses by identifying temperature anomalies and triggering remedial actions, potentially preventing complete stoppages and minimizing chemical injection requirements.
Implementation Method 1
an optical fiber disposed along a length of the pipeline to sense temperature of the pipeline
Implementation Method 2
A control system has a hydraulic flow model to determine a predicted operating temperature at each of a plurality points along the pipeline, wherein inputs to the hydraulic flow model include pipeline hydraulic conditions comprising pressure and flow rate
Data Source
AI summary
The present techniques are directed to a pipeline transporting a production fluid including hydrocarbon. An optical fiber is disposed along a length of the pipeline. A control system determines a predicted operating temperature based on pressure and flow rate of the production fluid in the pipeline. The control system determines a measured temperature along the pipeline using the optical fiber. The control system detects and locates a temperature anomaly by comparing the measured temperature of the pipeline to the predicted operating temperature.