Downhole Pipe Defect Segmentation via Time-Frequency Spectrograms
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Solution Overview
Problem
Current methods for monitoring downhole oil pipe corrosion in wellbores with multiple concentric casings are inefficient, as they rely on manual judgment and lack automated tools for accurate defect detection and quantification, particularly from within the innermost pipe.
Innovation Solution
A downhole logging tool with transmitter and receiver coils generates time-frequency spectrograms, using geometric active contours and level set methods to automatically quantify pipe defect attributes like length and width, enabling precise defect detection and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual judgment methods are used for defect detection, then device complexity is reduced, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent replaces manual visual inspection with automated image processing and machine learning algorithms. The system uses spectrogram analysis, geometric active contours, and level set methods to automatically detect and quantify pipe defects, eliminating the need for human workers to manually interpret measurements and significantly improving detection accuracy and consistency.
2Measurement precision
If automated defect detection is implemented, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system performs self-analysis through automated image processing algorithms that independently detect, segment, and quantify defects without human intervention. The machine learning models automatically interpret the spectrogram data, calculate defect attributes, and generate results, making the complex system self-sufficient and reducing the need for manual operation.
Solution Approach 2:
The patent segments the defect detection process into distinct computational stages: spectrogram generation, image preprocessing, geometric active contour segmentation, level set method refinement, and attribute extraction. This modular segmentation of the automated system makes the complex process more manageable and implementable through coordinated software modules.
3Ease of operation
If workers perform manual defect analysis, then ease of operation is maintained, but productivity deteriorates
Solution Approach 1:
The patent replaces the manual inspection process with automated computational analysis. The system rapidly processes spectrogram data and generates defect assessments without human intervention, dramatically increasing inspection throughput and productivity while maintaining ease of use through automated result generation.
4Device complexity
If manual defect quantification is used, then device complexity is reduced, but loss of information increases
Solution Approach 1:
The patent replaces manual estimation of defect attributes with automated image analysis that precisely measures defect length, width, area, and other characteristics from the spectrogram. The geometric active contours and level set methods accurately quantify defect geometry, preserving all relevant information without human error or subjective judgment.
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 automated, accurate detection and quantification of pipe defects, improving the monitoring of downhole corrosion and enhancing the integrity of well operations by reducing manual error and enhancing the reliability of defect analysis.
Implementation Method 1
A downhole logging tool with transmitter and receiver coils generates time-frequency spectrograms
Data Source
AI summary
A method for taking measurements in a wellbore including lowering a downhole logging tool in the wellbore; obtaining, via the logging tool, a plurality measurements of a downhole element; processing the plurality of measurements to obtain a plurality of processed measurements; calculating a contour model based on the plurality of processed measurements; and determining a parameter of the downhole element based on the contour model.