Interferometric Data Access via Parameter Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Processing and visualizing large volumes of interferometric data from pipelines is challenging due to remote locations with limited network connectivity, making it difficult to transfer and analyze massive data sets from fiber optic sensors effectively.
Innovation Solution
A computer-implemented method and system for accessing and updating interferometric system data using a data repository with a structured format, allowing users to query and extract specific data parameters like timestamps and channel numbers, and pre-processing data for efficient transmission and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all interferometric system data is transferred from remote field locations to pipeline company offices for analysis, then complete data analysis can be performed, but network bandwidth requirements become prohibitively high and transfer time increases significantly
Solution Approach 1:
The system extracts only the necessary interferometric data parameters (such as strain measurements, temperature readings, or event detections) from the complete dataset and transfers only these extracted elements to remote devices. This allows local analysis without requiring transfer of all raw data, significantly reducing network bandwidth consumption while maintaining analysis completeness for the required parameters.
Solution Approach 2:
Data processing and parameter extraction are performed in advance at the data repository before transfer to remote devices. By pre-processing the interferometric data to identify and extract relevant parameters, the system eliminates the need to transfer and process large volumes of raw data at remote locations, reducing both bandwidth requirements and transfer time.
2Measurement precision
If all interferometric system data is transferred to pipeline company offices, then comprehensive data analysis can be performed, but the time required for data transfer and initial processing increases significantly
Solution Approach 1:
The system extracts only the necessary interferometric data parameters (such as strain measurements, temperature readings, or event detections) from the complete dataset and transfers only these extracted elements to remote devices. This allows local analysis without requiring transfer of all raw data, significantly reducing network bandwidth consumption while maintaining analysis completeness for the required parameters.
Solution Approach 2:
Data processing and parameter extraction are performed in advance at the data repository before transfer to remote devices. By pre-processing the interferometric data to identify and extract relevant parameters, the system eliminates the need to transfer and process large volumes of raw data at remote locations, reducing both bandwidth requirements and transfer time.
3Ease of operation
If raw interferometric data is transferred to remote devices, then full data processing capability is available locally, but the data volume creates excessive bandwidth and storage requirements
Solution Approach 1:
The system extracts only the necessary interferometric data parameters (such as strain measurements, temperature readings, or event detections) from the complete dataset and transfers only these extracted elements to remote devices. This allows local analysis without requiring transfer of all raw data, significantly reducing network bandwidth consumption while maintaining analysis completeness for the required parameters.
Solution Approach 2:
The system provides different data quality levels to different remote devices based on their specific needs and capabilities. Each device receives only the data parameters required for its local analysis tasks, rather than receiving complete raw datasets. This enables local processing capability while optimizing bandwidth consumption according to each device's specific requirements.
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
Enables efficient access and processing of interferometric system data, reducing data transfer burdens and allowing for localized analysis of sensor and event data from pipelines and wellbores, even in remote locations with limited connectivity.
Implementation Method 1
Pressure changes, due to sound waves for example, in the space immediately surrounding an optical fiber and that encounter the optical fiber, cause dynamic strain in the optical fiber.
Implementation Method 2
The fiber Bragg gratings partially reflect the pulses back towards an optical receiver at which an interference pattern is observed.
Implementation Method 3
Optical interferometry is a technique in which two separate light pulses, a sensing pulse and a reference pulse, are generated and interfere with each other.
Data Source
AI summary
A computer-implemented method of providing access to interferometric system data stored in a data repository. A query that includes a data parameter identifier is received. The data repository is accessed and the interferometric system data is stored in the data repository using a data structure that has one or more data parameter arrays and one or more corresponding data group members. Each data group member includes one or more data arrays each associated with a data parameter in the corresponding data parameter array. Using the data parameter identifier, one or more target data parameters are determined from among the one or more data parameter arrays. One or more target data arrays that correspond to the one or more target data parameters are determined from among the one or more data arrays. The interferometric system data, which is in the one or more target data arrays, is extracted.