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Marine compressed air source array acoustic field characterization from at-sea measurements: Long-range propagationa)
Kun Li1, Natalia Sidorovskaia2
1John W. Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, Louisiana 70112, USA.
The Journal of the Acoustical Society of America
|September 26, 2024
Summary
Marine seismic surveys generate sound that travels long distances. This study measured acoustic propagation, finding levels can unexpectedly increase with range due to factors like receiver depth and seafloor conditions.
Area of Science:
- Oceanography
- Marine acoustics
- Seismic exploration
Background:
- Marine seismic surveys use compressed-air arrays, generating significant acoustic energy.
- Understanding long-range acoustic propagation is crucial for environmental impact assessments and geophysical surveys.
Purpose of the Study:
- To measure the three-dimensional acoustic field of a marine seismic source array.
- To analyze long-range acoustic propagation characteristics, including received sound pressure and sound exposure levels (SELs).
- To investigate the influence of receiver depth, array orientation, and propagation conditions on acoustic signals.
Main Methods:
- Conducted a comprehensive experiment in the northern Gulf of Mexico in 2007.
- Measured acoustic fields using a standard marine compressed-air source array.
- Collected data on received sound pressure levels and SELs at various ranges and depths.
Main Results:
- Received peak pressure levels and SELs exhibited non-monotonic (oscillatory) behavior with range, with up to a 10 dB increase at longer distances.
- Acoustic levels at the shallowest hydrophone exceeded those at deeper hydrophones by 3-10 dB beyond 20 km, indicating surface ducting effects.
- Range-independent bathymetry resulted in approximately 4 dB higher received acoustic levels compared to range-dependent conditions.
Conclusions:
- Long-range acoustic propagation from seismic arrays is complex and influenced by environmental factors.
- The experimental data provides a valuable dataset for validating acoustic source and propagation models.
- Accurate modeling is essential for predicting sound pressure and SEL in the far-field of seismic sources.
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