Acoustic Noise Source Localization via Hydrophone Cross-Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Localizing fluid flows in wellbore annuli is challenging due to pressure buildup and leakages, which current acoustic logging tools struggle to accurately detect and manage.
Innovation Solution
The use of an acoustic logging tool equipped with hydrophones that perform cross-correlation functions to determine noise source distributions, allowing for the identification of fluid flow locations and distributions within the wellbore.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional acoustic logging tools are used to detect fluid flows, then the tools can capture acoustic signals, but they struggle to accurately localize noise sources and identify flow locations
Solution Approach 1:
The patent divides the wellbore annulus into multiple radial zones and uses multiple hydrophones arranged at different radial positions to segment the acoustic field analysis. This segmentation allows the system to resolve noise sources in specific radial zones, improving localization accuracy by analyzing acoustic signals from discrete spatial segments rather than treating the entire annulus as a single region.
Solution Approach 2:
The patent introduces cross-correlation functions as an intermediary mathematical tool to process acoustic signals from multiple hydrophones. By computing cross-correlations between signals from different hydrophones, the system creates a transformed domain that enhances the visibility of noise source locations, acting as a mediator that converts raw acoustic data into localized flow information.
2Measurement precision
If multiple hydrophones are used to improve localization, then the system can better identify noise sources, but the device complexity increases
Solution Approach 1:
The patent designs the hydrophone array to serve multiple functions simultaneously: the same set of hydrophones used for capturing acoustic signals are also used for computing cross-correlation functions, determining noise source locations, and identifying flow characteristics. This multi-functionality reduces device complexity by eliminating the need for separate measurement and processing systems.
Solution Approach 2:
The patent creates virtual hydrophones through mathematical processing of signals from physical hydrophones. By computing cross-correlation functions and inverting the resulting matrix, the system generates synthetic acoustic field information that represents additional measurement points without requiring additional physical sensors, effectively copying the measurement capability through computational means.
3Measurement precision
If acoustic signals are processed to locate noise sources, then flow locations can be identified, but the processing time and computational cost increase
Solution Approach 1:
The patent performs preliminary signal processing by computing cross-correlation functions between hydrophone signals before attempting noise source localization. This preliminary action pre-processes the acoustic data into a transformed domain that highlights temporal and spatial relationships, reducing the computational burden of subsequent inversion operations and accelerating the overall localization process.
Solution Approach 2:
The patent transforms the acoustic signal parameters by computing cross-correlation functions that convert time-domain signals into a domain that emphasizes spatial relationships. This parameter transformation changes the mathematical characteristics of the data, making noise source identification more efficient and reducing processing time by working with transformed parameters rather than raw signals.
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 localization of noise sources, improving remedial and production management operations by accurately identifying leakages and fluid flows, thereby enhancing wellbore integrity and production efficiency.
Implementation Method 1
Acoustic noise source localization based on cross-correlation functions across a hydrophone array
Implementation Method 2
performing a cross-correlation function between pairs of hydrophones using the acoustic data set
Data Source
AI summary
A method for acoustic noise source detection. The method may comprise disposing an acoustic logging tool into a wellbore, performing an acoustic logging operations in the wellbore with the acoustic logging tool, forming a data set form the acoustic logging operation, and performing a cross-correlation function between pairs of hydrophones using the data set. The method may further comprise construction a cost function using at least in part the cross-correlation function to find a noise source distribution and identifying a location of the acoustic noise source by inverting the noise source distribution.