Depthwise Spectral Subtraction for Wellbore Defect Signals
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Solution Overview
Problem
Unwanted noise in wellbore acoustic data interferes with the detection of critical signals indicative of wellbore defects, leading to inaccurate safety assessments.
Innovation Solution
A depth-wise spectral subtraction method is employed to identify and remove background noise from wellbore data, preserving signals of interest by analyzing spectral content and applying formulas to suppress background noise effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If spectral subtraction is applied to remove background noise, then noise reduction effectiveness is improved, but signal distortion risk increases
Solution Approach 1:
The patent applies depth-wise spectral subtraction that processes different depth intervals with individually estimated noise profiles. Each depth interval has its own noise characteristics estimated from noise-dominated acquisitions, allowing localized noise removal that adapts to spatial variations in noise sources while preserving depth-specific signal characteristics.
Solution Approach 2:
The patent performs preliminary classification of acquisitions to identify noise-dominated intervals before applying spectral subtraction. By pre-identifying which acquisitions are dominated by background noise versus those containing defect signals, the system prepares appropriate noise profiles for subtraction only where needed, preventing distortion of defect signals while removing background noise.
2Object-affected harmful factors
If noise removal processing is applied to all data, then background noise is reduced, but defect signal preservation becomes compromised
Solution Approach 1:
The patent applies spectral subtraction selectively rather than universally. By performing partial action on only those depth intervals classified as noise-dominated, the system removes background noise where present while leaving defect signals in signal-dominated intervals untouched. This partial application of noise removal prevents the excessive action that would otherwise distort or remove defect signals.
Solution Approach 2:
The patent segments the wellbore data into multiple depth intervals and classifies each as either noise-dominated or signal-dominated. This segmentation allows differential processing where spectral subtraction is applied to noise-dominated segments while preserving signal-dominated segments, thereby removing unwanted noise without compromising defect signal integrity.
Data Source
AI summary
An array of hydrophones may be deployed in a wellbore to collect sounds that may be used to identify whether a wellbore is safe to operate. This hydrophone array may include acoustic sensors that sense noises indicative of a defect that could lead to catastrophic failure of a wellbore and other noises that may be considered unwanted background noises. Techniques of the present disclosure may classify noises indicative of a defect as being “signals of interest.” The presence of “background noise” may interfere with the collection and/or evaluation of “signals of interest.” Because of this, evaluations performed on data that includes “background noise” and “signals of interest” may result in inaccurate determinations being made regarding the safety of a wellbore. As such, systems and methods of the present disclosure are directed to improving safety of a wellbore by removing “background noise” more effectively while increasing quality of “signals of interest.”