Beamforming Refinement for Downhole Acoustic Source Separation
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Solution Overview
Problem
Existing beamformers, such as Maximum SNR beamformers, are difficult to implement effectively in acoustic logging devices due to limited knowledge of signal and interference spectral variances, hindering the separation of acoustic vibrations from different sources in a wellbore environment.
Innovation Solution
Utilizing an initial guess of source spectra from a different type of beamformer to estimate signal and interference variances, followed by a refinement loop with a Maximum SNR beamformer to iteratively improve the spectral separation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a Maximum SNR beamformer is used for acoustic source separation, then the spectral separation capability is improved, but the implementation difficulty increases due to limited knowledge of signal and interference spectral variances
Solution Approach 1:
The patent applies a preliminary beamformer (such as a delay-and-sum beamformer) before the Maximum SNR beamformer to obtain initial spectral estimates. These preliminary estimates serve as the basis for calculating signal and interference spectral variances, enabling the Maximum SNR beamformer to function effectively without requiring prior knowledge of these parameters.
Solution Approach 2:
The patent introduces an intermediate processing step where a preliminary beamformer acts as a mediator between the raw acoustic data and the Maximum SNR beamformer. This intermediary generates initial spectral estimates that facilitate the subsequent variance calculation, bridging the gap between available data and the requirements of the Maximum SNR beamformer.
2Loss of information
If acoustic data from multiple sources is collected in a wellbore, then the characterization capability of the downhole environment is improved, but the difficulty of analyzing and separating the acoustic vibrations increases
Solution Approach 1:
The patent segments the combined acoustic signal into contributions from individual acoustic sources through beamforming techniques. By applying spatial filtering and spectral separation, the system divides the mixed acoustic data into distinct source components, enabling separate analysis of each source's characteristics.
Solution Approach 2:
The patent replaces manual or simple filtering methods with advanced signal processing techniques including beamforming, spectral estimation, and iterative refinement algorithms. This substitution of mechanical/simple analysis with computational methods enables effective separation and analysis of multiple overlapping acoustic sources.
Data Source
AI summary
Aspects of the subject technology relate to systems, methods, and computer readable media for estimating acoustic spectra. Acoustic data can be received at a hydrophone array from a first acoustic source and a second acoustic source in a downhole environment. An initial noise spatial correlation matrix estimation can be generated based on the acoustic data. The initial noise spatial correlation matrix estimation can be applied to a beamformer to generate a first source spectra estimation for the first acoustic source and the second acoustic source. A revised noise spatial correlation matrix estimation can be generated based on the first source spectra estimation. The revised noise spatial correlation matrix estimation can be applied to the beamformer to generate a second source spectra estimation for the first acoustic source and the second acoustic source in the downhole environment based on the first source spectra estimation.