Acoustic Node Network Localization for Towed Seismic Streamers
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Solution Overview
Problem
Current seismic data acquisition techniques face challenges in accurately localizing seismic streamers due to environmental factors like sound speed profiles and bathymetry, leading to inaccurate acoustic performance and localization precision, as they do not account for varying environmental conditions such as temperature, pressure, and salinity, which affect sound propagation paths.
Innovation Solution
A method to manage acoustic performances of acoustic nodes by estimating propagation properties using sound speed profiles, bathymetric characteristics, and sub-bottom properties, allowing for the adjustment of node layouts and parameters to optimize signal transmission and reception, thereby improving localization precision and acoustic performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If acoustic nodes are distributed along long seismic streamers to increase coverage area, then the number of acoustic nodes increases, but the localization precision deteriorates due to accumulated errors in inter-node distance estimation
Solution Approach 1:
The system continuously monitors acoustic signal propagation characteristics and uses this feedback to dynamically adjust the acoustic network configuration. By comparing actual signal propagation with predicted models and correcting node positions accordingly, the system maintains localization precision despite the extended coverage area and number of nodes.
Solution Approach 2:
The invention changes the parameters of acoustic signal propagation by accounting for environmental factors such as sound speed variations, temperature gradients, and bathymetry. By incorporating these environmental parameters into the distance estimation model, the system reduces localization errors that would otherwise accumulate over long streamer lengths.
2Area of stationary object
If acoustic signals are transmitted over long distances along streamers, then the coverage area increases, but the signal quality deteriorates due to propagation errors and environmental factors
Solution Approach 1:
The system introduces environmental parameter models as intermediaries between the acoustic nodes and the distance estimation process. These models mediate the relationship by providing corrections for sound speed variations, temperature effects, and bathymetric influences, thereby maintaining signal quality over long transmission distances.
Solution Approach 2:
The invention replaces simple geometric distance calculation with a physics-based acoustic propagation model that accounts for environmental factors. This substitution of the distance estimation mechanism improves signal quality by correcting for propagation errors that would otherwise degrade reliability over long distances.
3Device complexity
If the acoustic network is configured with fixed node positions, then the device complexity is reduced, but the adaptability deteriorates when environmental conditions vary
Solution Approach 1:
The system transitions from a static, fixed node configuration to a dynamic network that automatically adapts to environmental conditions. By continuously updating node positions and propagation parameters based on real-time environmental data, the system maintains adaptability without significantly increasing operational complexity.
Solution Approach 2:
The acoustic network performs self-adjustment by automatically monitoring environmental conditions and modifying its own configuration accordingly. The system serves itself by using environmental sensors and propagation models to autonomously optimize node positions and signal parameters, eliminating the need for manual reconfiguration.
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 enhances the accuracy of seismic data acquisition by optimizing acoustic performances before and during surveys, reducing errors in inter-node distance estimation and improving signal quality, leading to more precise localization of seismic streamers and better imaging of the seafloor.
Implementation Method 1
These transducers are transmitters and receivers of acoustic signals, which can be used to estimate an inter-node distance separating two acoustic nodes (acting as sender node and receiver node respectively) situated on two different streamers (which may be adjacent or not) as a function of an acoustic signal propagation duration measured between these two nodes
Implementation Method 2
it is important to precisely locate the streamers, in particular for: monitoring the position of the hydrophones (distributed along the seismic streamers) in order to obtain a satisfactory precision of the image of the sea bed in the exploration zone
Implementation Method 3
environmental factors like sound speed profiles and bathymetry, leading to inaccurate acoustic performance and localization precision, as they do not account for varying environmental conditions such as temperature, pressure, and salinity, which affect sound propagation paths
Data Source
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AI summary
It is proposed a method for managing the acoustic performances of a network of acoustic nodes arranged along towed acoustic linear antennas, the network of acoustic nodes being adapted to determine inter-node distances allowing to locate the acoustic linear antennas. The method comprises steps of: obtaining (91) a determined layout of the network of acoustic nodes; obtaining (92) at least one marine environment property relating to an area of performance of a survey with the network of acoustic nodes; and quantifying (94) the acoustic performances of the network of acoustic nodes, using a sound propagation model, the at least one marine environment property and the determined layout.