A Method for Calculating the Output Pressure Waveform from an Air Gun

Ziolkowski, Anton

doi:10.1111/j.1365-246x.1970.tb01773.x

Cited by 141 publications

(92 citation statements)

References 3 publications

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“…Furthermore, we also observe that there is a time delay of approximately 1 ms between the 6.5 and 8 m separation distances. To investigate this issue in more detail, we performed a simple source modeling study using the method described in Ziolkowski (1970). The modeling example (not identical to the experiment, but very similar, so it is used for the purpose of illustrating the effect) in Figure 5 confirms these observations: The time window for when cavity production is possible is shifted and reduced in length as the separation distance is increased.…”

Section: Ghost Cavitation Versus Source Separation Distancementioning

confidence: 59%

“…A more realistic modeling for the actual configuration used in the field experiment is presented in Figure 6, where we observe a 3D version of the "cavity cloud" surrounding the gun array. In this figure, we have used conventional air-gun modeling (Ziolkowski, 1970) to estimate volumes in the water column, in which the modeled pressure is below a certain threshold. There are also source modeling approaches for generator injector guns (Landrø, 1992) and water guns (Landrø et al, 1993) Figure 2.…”

Section: Ghost Cavitation Versus Source Separation Distancementioning

confidence: 99%

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Reducing high-frequency ghost cavitation signals from marine air-gun arrays

Landrø

Amundsen

2016

GEOPHYSICS

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Ghost cavitation, which is a term describing that cavitation bubbles are generated acoustically, has been hypothesized to occur when the ghost reflected signals from many individual air guns beneath the sea surface produce a pressure that is close to zero in the water above the source array. Ghost cavitation is typically observed some milliseconds after the ghost reflection, and it may last for 5-15 ms, depending on the configuration of the source array. The cavitation process subsequently generates a weak high-frequency signal. To investigate this potential signal model and mechanism, we have performed a dedicated source experiment. We found that the distance between the source strings in a source array is a major factor that influences the amount and strength of the high-frequency signal. By increasing the separation distance from 6.5 to 8 m, we have observed a significant decrease in the high-frequency signal. Further, the amount of ghost cavitation can be reduced by increasing the distance between the guns. Also single sub-arrays may create ghost cavitation sound, of course weaker in signal strength compared with full arrays, in agreement with the model. Conventional air-gun modeling can be used to predict where ghost cavitation can occur. Therefore, in principle, a workflow could be developed to quantify grossly if and how much high-frequency signals could be generated by this mechanism, given the source array configuration, and further change the configuration to reduce to a very minimum the high-frequency signals, if deemed necessary. For an airgun array consisting of two subarrays separated by 6 m and fired at 9 m depth, we found that the high-frequency signals emitted between 1 and 10 kHz were of similar strength to the noise from conventional cargo ships, depending on their size and the vessels' speed.

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Section: Ghost Cavitation Versus Source Separation Distancementioning

confidence: 59%

Section: Ghost Cavitation Versus Source Separation Distancementioning

confidence: 99%

Reducing high-frequency ghost cavitation signals from marine air-gun arrays

Landrø

Amundsen

2016

GEOPHYSICS

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“…An airgun array usually contains airgun elements with different volumes, which produce sound pulses with different amplitudes, damping rates and bubble pulse periods (Ziolkowski, 1970). This variability makes airgun array signature modeling complex and difficult.…”

Section: Alrgun Array Beampattern Modelmentioning

confidence: 99%

“…Using this model, we calculated the acoustic pressure at a certain radius from the array and normalized it to obtain an estimate of the source beampattern. The airgun elements in this model were treated as monopole sources with a single impulse, while real airgun pulses include a series of bubble pulses (Ziolkowski, 1970). However, the model could still predict the locations of spatial and frequency notches in the airgun array beampattern, since notch locations are mainly determined by the geometric configuration of the array (Parkes and Hatton 1986, Tipler and Llewellyn 2003).…”

Section: Alrgun Array Beampattern Modelmentioning

confidence: 99%

Echolocation-based foraging by harbor porpoises and sperm whales, including effects of noise and acoustic propagation

DeRuiter¹

2008

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In this thesis, I provide quantitative descriptions of toothed whale echolocation and foraging behavior, including assessment of the effects of noise on foraging behavior and the potential influence of ocean acoustic propagation conditions on biosonar detection ranges and whale noise exposure. In addition to presenting some novel basic science findings, the case studies presented in this thesis have implications for future work and for management.In Chapter 2, I describe the application of a modified version of the Dtag to studies of harbor porpoise echolocation behavior. The study results indicate how porpoises vary the rate and level of their echolocation clicks during prey capture events; detail the differences in echolocation behavior between different animals and in response to differences in prey fish; and show that, unlike bats, porpoises continue their echolocation buzz after the moment of prey capture.Chapters 3-4 provide case studies that emphasize the importance of applying realistic models of ocean acoustic propagation in marine mammal studies. These chapters illustrate that, although using geometric spreading approximations to predict communication/target detection ranges or noise exposure levels is appropriate in some cases, it can result in large errors in other cases, particularly in situations where refraction in the water column or multi-path acoustic propagation are significant.Finally, in Chapter 5, I describe two methods for statistical analysis of whale behavior data, the rotation test and a semi-Markov chain model. I apply those methods to test for changes in sperm whale foraging behavior in response to airgun noise exposure. Test results indicate that, despite the low-level exposures experienced by the whales in the study, some (but not all) of them reduced their buzz production rates and altered other foraging behavior parameters in response to the airgun exposure. Sincere thanks also to the many other people who have helped with data collection and analysis over the course of my graduate work, and also to everyone who offered comments on drafts of this thesis. More detailed acknowledgments can be found at the end of each chapter, but here I would especially like to thank the following. Thesis Objectives and Chapter 1 OverviewThe goal of my thesis research has been to provide quantitative descriptions of toothed whale echolocation and foraging behavior (Chapters 2 and 5), including assessment of the effects of noise on foraging behavior (Chapter 5) and the potential influence of ocean acoustic propagation conditions on biosonar detection ranges (Chapter 3) and whale noise exposure (Chapter 4). I have focused on two study species, the harbor porpoise (Phocoena phocoena, Chapters 2-3) and the sperm whale (Physeter macrocephalus, Chapters 4-5).The following sections present background information relevant to the research presented in the rest of the thesis, beginning with a review of previous research on the use of echolocation by foraging animals. This review is followed by b...

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“…The empirical relations between these factors and the characteristics of airgun signatures (e.g., the amplitude of primary pulse, the period of bubble pulse and the primary-to-bubble amplitude ratio) have already been drawn. On the theoretical side, the seismic signatures from ocean used airguns and airgun arrays can be calculated numerically based on the free bubble oscillation theory (Ziolkowski 1970;Schulze-Gattermann 1972;Safar 1976;Cox et al 2004;Li et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Influencing factors of seismic signals generated by un-tuned large volume airgun array in a land reservoir

et al. 2014

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Un-tuned large volume airgun array in a water reservoir is recently proposed as a new way to generate seismic waves on land. It can be used to explore the earth velocity structure and its temporal variations as well. However, the characteristics of seismic signals (especially far-field signals) from an airgun array in a reservoir and its affecting factors (firing pressure, airgun towing depth, water level of the reservoir, etc.) has not been adequately studied. We analyzed the seismic data collected from field experiments at Binchuan Transmitting Seismic Station in 2011 and 2013 and found that (1) The similarity of seismic signals decrease with distance, which is most likely induced by the decay of signal amplitude and signal to noise ratio (SNR); (2) The amplitudes of far-field airgun signals are almost linearly proportional to the firing pressure; (3) The towing depth of airgun has less effects on the far-field signals; (4) The amplitudes of far-field airgun signals are proportional to the water level of the reservoir.

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A Method for Calculating the Output Pressure Waveform from an Air Gun

Cited by 141 publications

References 3 publications

Reducing high-frequency ghost cavitation signals from marine air-gun arrays

Reducing high-frequency ghost cavitation signals from marine air-gun arrays

Echolocation-based foraging by harbor porpoises and sperm whales, including effects of noise and acoustic propagation

Influencing factors of seismic signals generated by un-tuned large volume airgun array in a land reservoir

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