Slowness Filter for Downhole Sonic Data Noise Removal
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Solution Overview
Problem
Existing sonic data processing methods for downhole tools in the oil/gas industry face challenges in accurately measuring borehole flexural modes and other acoustic signals due to interference from collar arrivals and other coherent noise, which affects the accuracy of formation characterization.
Innovation Solution
A method and system that utilize a slowness filter to detect and remove coherent noise from sonic data by creating a new set of waveforms with a phase delay corresponding to the target slowness to be removed, and applying this filter to the original waveforms, allowing for the isolation of target signals and improved estimation of formation parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sonic data processing methods are used, then the measurement process is simple, but the measurement precision is reduced due to interference from collar arrivals and coherent noise
Solution Approach 1:
The patent extracts and removes coherent noise components (collar arrivals, tool mode arrivals, leaky modes) from the sonic data by identifying their specific slowness characteristics and applying targeted filtering. This separation isolates the desired borehole flexural mode signals from the interfering coherent noise, directly improving measurement precision without requiring complex hardware modifications
Solution Approach 2:
The patent transforms the raw sonic data into the slowness domain through Fourier transformation and applies slowness-based filtering. By changing the parameter domain from time-space to slowness-frequency, the method enables selective removal of coherent noise components based on their distinct slowness values, achieving high-precision signal separation
2Measurement precision
If a slowness filter is applied to remove coherent noise, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent introduces an intermediary processing stage that transforms the data into the slowness domain using Fourier transformation. This intermediary representation serves as a bridge between the raw time-domain data and the final filtered output, enabling selective noise removal through slowness-based filtering while maintaining a systematic and manageable processing architecture
Solution Approach 2:
The patent replaces complex mechanical or hardware-based noise filtering systems with signal processing algorithms operating in the slowness domain. Instead of using physical filters or complex sensor arrangements, the method uses mathematical transformations and digital signal processing to achieve noise removal, simplifying the overall system while improving precision
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
The slowness filtering technique effectively removes coherent noise, enhancing the accuracy of borehole flexural mode measurements and other formation parameter estimations, leading to more precise characterization of geological formations.
Implementation Method 1
creating a new set of waveforms which have a phase delay corresponding to a target slowness to be removed
Implementation Method 2
subtracting the above new set of waveforms from the original waveforms
Implementation Method 3
sensing acoustic waves generated by one or more acoustic sources and having propagated through a geological formation
Implementation Method 4
obtaining slowness-frequency components of the plurality of waveforms
Data Source
AI summary
A method for processing sonic data acquired with a downhole sonic tool is provided. The method comprises detecting coherent noise based on a plurality of waveforms obtained from one or more receivers issued by one or more transmitters. The plurality of waveforms correspond to propagating acoustic waves in a formation. In addition, the method comprises building a slowness filter for removing the coherent noise, and applying the slowness filter to the plurality of waveforms.