The signature of an air gun array: Computation from near‐field measurements including interactions—Practical considerations

Parkes, Gregg; Ziolkowski, A. A.; Hatton, Les; Haugland, T.

doi:10.1190/1.1441640

Cited by 56 publications

(13 citation statements)

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“…The layout of the survey is shown in Figure 9. The source wavefield was measured according to the method in Ziolkowski et al (1982) and Parkes et al (1984), and the seismic reflection data were processed to zero phase according to our method, described above. Wells 12/22-2 and 12/22-3 are connected by a seismic line, as shown in Figure 9, and lie in the area where the top of the J1 megasequences truncated ( Figure 7) and hence where the Mid-Cimmerian Unconformity might best be resolved.…”

Section: Results Of the New Well-tie Methodologymentioning

confidence: 99%

“…The source wavefield of the air-gun array was measured for each shot using near-field hydrophones. Using the method of Ziolkowski et al (1982) and Parkes et al (1984), the measurements were used to decompose the wavefield into the individual spherical waves generated by the oscillating bubbles emitted by the air guns. The spherical waves were then superposed in the frequency domain, taking into account the geometry of the array and the free surface, to compute a far-field signature at 20 • to the vertical.…”

Section: The Waveletmentioning

confidence: 99%

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Wavelets, well ties, and the search for subtle stratigraphic traps

Ziolkowski¹,

Underhill²,

Johnston

1998

GEOPHYSICS

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We examine the conventional methodology for tying wells to processed seismic data and show why this methodology fails to allow for reliable interpretation of the seismic data for stratigraphy. We demonstrate an alternative methodology that makes the tie without the use of synthetic seismograms, but at the price of measuring the seismic source signature, the cost of such measurements being about 1% of data acquisition costs. The essence of the well tie is (1) to identify geological and seismic interfaces from the logs and core, (2) to measure the one‐way traveltime to these interfaces using downhole geophones, and (3) to use the polarity information from (1) and the timing information from (2) to identify the horizons on the zero‐phase processed seismic data. Conventional processing of seismic data usually causes the wavelet to vary from trace to trace, and conventional wavelet extraction at a well using the normal‐incidence reflection coefficients relies on a convolutional relationship between these coefficients and the processed data that has no basis in the physics of the problem. Each new well introduces a new wavelet and poses a new problem—how should the zero‐phasing filter be derived between wells? Our methodology consists of three steps: (1) determination of the wavelet consisting of all known convolutional effects before any processing using measurements of the source time function made during data acquisition, (2) compression of this wavelet to the shortest zero‐phase wavelet within the bandwidth available, and (3) elimination of uncontrolled distortions to the wavelet in subsequent processing. This method is illustrated with data from the prospective Jurassic succession in the Moray Firth rift arm of the North Sea in which we have identified, for the first time on seismic data, a major regional unconconformity that cuts out more than 20 Ma of geological time. This method offers two major benefits over the conventional approach. First, all lateral variations in the processed seismic data are caused by the geology. Second, events on the processed seismic data may be identified from well logs simply by their polarity and timing. It follows that events can then be followed on the seismic data from one well to another with confidence, the seismic data can be interpreted for stratigraphy, and subtle stratigraphic traps may be identified.

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Section: Results Of the New Well-tie Methodologymentioning

confidence: 99%

Section: The Waveletmentioning

confidence: 99%

Wavelets, well ties, and the search for subtle stratigraphic traps

Ziolkowski¹,

Underhill²,

Johnston

1998

GEOPHYSICS

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“…The use of near-field measurements measuring the acoustic signal at a distance of approximately 1 m from each air gun in a marine air-gun array is proposed and demonstrated by Ziolkowski et al (1982), and it is later improved by Parkes et al (1984). Landrø et al (1991) test the method on compact air-gun arrays and find that the near-to far-field method produces instable results in this case.…”

Section: Introductionmentioning

confidence: 99%

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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“…The method is suitable for deep water surveys and has been applied to a survey offshore Gabon. Ziolkowski (1982) and Parkes (1984) described an equation relating the signal recorded in near-field hydrophones, mounted on the source array, as a function of notional sources, by:…”

Section: Introductionmentioning

confidence: 99%

Far-field Source Signature Reconstruction Using Direct Arrival Data

Davison

Poole

2015

Proceedings

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For accurate source designature it is fundamental to have precise knowledge of the seismic far-field source signature. While near-field hydrophone data can often be used to provide good quality signatures, such recordings are not always available. This paper describes a technique to extract the far-field signature from the inversion of direct arrivals present in the seismic streamer data. The method has been applied to a deep water survey offshore Gabon, and has been found to produce comparable results to those using data recorded from near-field hydrophones mounted above the air guns on the seismic source array. The method presents advantages for the reprocessing of legacy surveys to achieve a more broadband seismic result.

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The signature of an air gun array: Computation from near‐field measurements including interactions—Practical considerations

Cited by 56 publications

References 0 publications

Wavelets, well ties, and the search for subtle stratigraphic traps

Wavelets, well ties, and the search for subtle stratigraphic traps

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

Far-field Source Signature Reconstruction Using Direct Arrival Data

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