Remote Field Eddy Current Pipe Defect Detection
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Solution Overview
Problem
Corrosion management in multiple downhole casing strings is complex due to the challenges in accurately detecting defects and estimating overall thickness using electromagnetic logging tools, especially in multi-pipe configurations, where noise robustness and resolution are compromised.
Innovation Solution
The implementation of remote-field eddy current (RFEC) techniques with multiple receivers and frequencies for defect detection, utilizing differential phase analysis to distinguish defected pipes and estimate overall thickness, providing a more robust and accurate characterization of pipe conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electromagnetic logging tools are used for corrosion detection in multiple casing strings, then corrosion monitoring capability is provided, but measurement precision and noise robustness are compromised
Solution Approach 1:
The patent divides the measurement system into multiple independent receivers (first receiver and second receiver) positioned at different locations within the casing string. Each receiver independently measures electromagnetic signals from different pipes, allowing the system to segment the complex multi-pipe measurement problem into manageable individual measurements that can be processed separately for improved precision
Solution Approach 2:
The patent introduces the frequency dimension by measuring electromagnetic signals at multiple frequencies (first frequency and second frequency). This dimensional expansion allows the system to differentiate between signals from different pipes and distinguish corrosion-related signal variations from background noise, thereby improving measurement precision in multi-pipe configurations
2Adaptability or versatility
If electromagnetic logging tools operate in multi-pipe configurations, then comprehensive pipe coverage is achieved, but data interpretation complexity increases
Solution Approach 1:
The patent segments the data interpretation process by assigning specific receivers to measure specific pipes (first receiver for first pipe, second receiver for second pipe). This segmentation creates a direct mapping between receivers and target pipes, significantly simplifying the interpretation of which measurements correspond to which pipes in multi-pipe configurations
Solution Approach 2:
The patent employs feedback mechanisms where measured electromagnetic signals are compared against reference signals or threshold values to automatically identify corrosion defects. This feedback-based automated interpretation reduces the complexity of manual data analysis while maintaining comprehensive multi-pipe monitoring capability
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 enables precise detection of defected pipes and accurate overall thickness estimation, improving the robustness against noise and reducing the complexity of data interpretation, leading to enhanced corrosion management and production processes in oil and gas operations.
Implementation Method 1
a transmitter operable to generate an electromagnetic signal
Implementation Method 2
remote-field eddy current (RFEC) techniques
Implementation Method 3
the EM log data may be interpreted to correlate a level of flux leakage or EM induction with corrosion
Data Source
AI summary
Methods for detection of pipe characteristics, such as defect detection of downhole tubulars and overall thickness estimation of downhole tubulars, utilizing remote-field eddy current technique. A defect detection method may further include disposing a defect detection tool in a wellbore, wherein the defect detection tool comprises a transmitter and a plurality of receivers, recording measurements for a plurality of channels, utilizing pre-calculated estimation curves corresponding to the plurality of channels at a plurality of defected candidates to obtain thicknesses corresponding to the plurality of channels at each defected candidate; and evaluating variations for the thicknesses by computing standard deviations between the thicknesses obtained for the plurality of channels at each defected candidates utilizing a minimum variation, and computing an overall thickness change using overall thickness estimations for the plurality of defected candidates.