Whirl Detection via Ellipse Fitting of Drill String Motions
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Solution Overview
Problem
Existing methods for determining drill string whirl attributes, such as magnitude, orientation, and velocity, are limited by their reliance on frequency domain computations, which are prone to noise and inaccuracies, failing to provide robust results for detecting and mitigating whirl-induced failures in hydrocarbon drilling operations.
Innovation Solution
A system and method that transforms tri-axial acceleration data into drill string motions, fitting these motions to a revolution ellipse to derive whirl attributes like magnitude, orientation, and velocity without requiring frequency determination, using numerical optimization and coordinate frame transformations to correct for noise and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency domain computations are used to determine whirl attributes, then whirl frequency can be identified, but measurement precision deteriorates due to noise introducing additional peaks in the frequency spectrum
Solution Approach 1:
The patent replaces frequency domain analysis with time domain analysis. Instead of transforming acceleration data into the frequency domain where noise creates spurious peaks, the system performs numerical integration and ellipse fitting directly on time-domain data. This substitution eliminates the harmful effect of noise while maintaining the ability to accurately determine whirl attributes such as magnitude, orientation, and velocity.
Solution Approach 2:
The patent introduces an intermediary transformation process that converts tri-axial acceleration data into drill string motion parameters through numerical integration and coordinate frame transformations. This intermediary step allows the system to work with time-domain data directly, avoiding the need for frequency domain transformation and its associated noise problems, while still achieving accurate whirl characterization.
2Reliability
If frequency domain computations are used, then whirl frequency can be estimated, but reliability deteriorates due to inability to robustly handle noise and provide accurate determinations
Solution Approach 1:
The system substitutes frequency domain computations with time domain-based numerical integration and ellipse fitting. This replacement provides robust handling of noise by working directly with time-domain signals, eliminating the spurious peaks that compromise reliability in frequency domain methods. The time domain approach maintains measurement precision for whirl attributes while significantly improving robustness to noise.
Solution Approach 2:
The patent employs iterative ellipse fitting processes that continuously adjust and refine the whirl parameter estimates based on the acceleration data. This feedback mechanism allows the system to converge on accurate whirl attributes even in the presence of noise, improving both reliability and precision. The iterative nature of the fitting process enables the system to compensate for noise and provide robust, accurate determinations.
3Measurement precision
If time domain analysis is used to avoid noise, then measurement precision improves, but device complexity increases due to numerical optimization and coordinate frame transformations
Solution Approach 1:
The patent segments the complex data processing into distinct, manageable steps: (1) numerical integration of acceleration data to obtain velocity and position, (2) coordinate frame transformations to align with drill string rotation, and (3) ellipse fitting to extract whirl attributes. This segmentation reduces the perceived complexity by breaking down the overall process into sequential operations, each with clear input and output, while maintaining high measurement precision.
Solution Approach 2:
The system changes the parameter representation from frequency-domain spectral components to time-domain motion parameters (position, velocity, orientation). This parameter transformation simplifies the analysis by eliminating the need for complex spectral processing and noise filtering, while achieving accurate whirl attribute determination. The parameter change approach reduces processing complexity by working with more intuitive and directly measurable quantities.
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 reliable and proactive detection of whirl attributes, reducing the risk of tool failures by providing real-time, accurate measurements of whirl magnitude, orientation, and velocity, allowing for timely mitigation efforts in drilling operations.
Implementation Method 1
Tri-axial accelerometers used in the drilling industry measure three orthogonal accelerations related to shock and vibration during drilling operations
Implementation Method 2
A system and method that transforms tri-axial acceleration data into drill string motions, fitting these motions to a revolution ellipse to derive whirl attributes
Data Source
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AI summary
Methods and systems output at least one drill string whirl attribute, such as magnitude, orientation, velocity and type, without requiring determination of whirl frequency. Transforming acceleration data into drill string motions provides a path of one point along the drill string. Fitting these motions throughout one complete revolution of the drill string to a revolution ellipse, for example, provides revolution ellipse centers defining centers of rotation for each revolution fitted. A whirl ellipse, for example, derives from another fitting using a plurality of the revolution ellipse centers. Coefficients from the whirl ellipse and/or vector direction of the centers provide at least one whirl attribute for output.