Blended acquisition with dispersed source arrays

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. A19-A23 ◽  
Author(s):  
A. J. Berkhout
Keyword(s):  
High Frequency ◽  
Spatial Sampling ◽  
Acquisition Process ◽  
Air Gun ◽  
Seismic Acquisition ◽  
Sampling Intervals ◽  
Source Array

Blended source arrays are historically configured with equal source units, such as broadband vibrators (land) and broadband air-gun arrays (marine). I refer to this concept as homogeneous blending. I have proposed to extend the blending concept to inhomogeneous blending, meaning that a blended source array consists of different source units. More specifically, I proposed to replace in blended acquisition the traditional broadband sources by narrowband versions — imagine coded single air guns with different volumes or coded single narrowband vibrators with different central frequencies — together representing a dispersed source array (DSA). Similar to what we see in today’s audio systems, the DSA concept allows the design of dedicated narrowband source elements that do not suffer from the low versus high frequency compromise. In addition, the DSA concept opens the possibility to use source depths and spatial sampling intervals that are optimum for the low-, mid-, and high-frequency sources (multiscale shooting grids). DSAs are considered to be an important step in robotizing the seismic acquisition process.

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

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. P33-P46 ◽  
Author(s):  
Martin Landrø ◽  
Yuan Ni ◽  
Lasse Amundsen
Keyword(s):  
High Frequency ◽  
Separation Distance ◽  
Signal Model ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Array Configuration ◽  
Air Gun ◽  
Marine Air ◽  
Potential Signal ◽  
Source Array

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 air-gun 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.

Acquisition/Processing: Machine learning-based deblending: Dispersed source array data example

2021 ◽  
Vol 40 (10) ◽  
pp. 759-767
Author(s):  
Rolf H. Baardman ◽  
Rob F. Hegge
Keyword(s):  
Machine Learning ◽  
High Frequency ◽  
Low Frequency ◽  
Seismic Interpretation ◽  
Salt Dome ◽  
Training Data ◽  
Array Data ◽  
Seismic Processing ◽  
Processing Machine ◽  
Source Array

Machine learning (ML) has proven its value in the seismic industry with successful implementations in areas of seismic interpretation such as fault and salt dome detection and velocity picking. The field of seismic processing research also is shifting toward ML applications in areas such as tomography, demultiple, and interpolation. Here, a supervised ML deblending algorithm is illustrated on a dispersed source array (DSA) data example in which both high- and low-frequency vibrators were deployed simultaneously. Training data pairs of blended and corresponding unblended data were constructed from conventional (unblended) data from another survey. From this training data, the method can automatically learn a deblending operator that is used to deblend for both the low- and the high-frequency vibrators of the DSA data. The results obtained on the DSA data are encouraging and show that the ML deblending method can offer a good performing, less user-intensive alternative to existing deblending methods.

scholarly journals Detecting gas leakage using high-frequency signals generated by air-gun arrays

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. A7-A12 ◽  
Author(s):  
Martin Landrø ◽  
Fredrik Hansteen ◽  
Lasse Amundsen
Keyword(s):  
High Frequency ◽  
Field Experiments ◽  
Water Layer ◽  
Sampling Interval ◽  
Acoustic Energy ◽  
Storage Site ◽  
High Frequency Signal ◽  
Gas Leakage ◽  
Temporal Sampling ◽  
Air Gun

Recent field experiments have demonstrated that marine air-gun arrays create acoustic energy greater than 1 kHz. We have suggested to use the high-frequency signal as a source to look for gas leakage at, for instance, a producing hydrocarbon field, or a [Formula: see text] storage site in which the field is covered by permanent acoustic sensors at the seabed, often referred to as a permanent reservoir monitoring field. The only needed modification is that the temporal sampling interval for the receivers is decreased to 0.1 ms (in contrast to the normal sampling interval of 1 or 2 ms), to ensure that the system is capable of recording signals up to 5 kHz. We suggest using numerous fixed receivers at the seabed to detect a gas chimney by simple high-pass filtering and subsequent transmission type analysis of the recorded signals. We think this method might serve as an elegant, precise, and very cost-effective way to detect gas leakage into the water layer.

A 108km2 Compressive Sensing Processing Trial

2021 ◽  
Author(s):  
Dustin Blymyer ◽  
Klaas Koster ◽  
Graeme Warren
Keyword(s):  
Compressive Sensing ◽  
Surface Waves ◽  
Seismic Data ◽  
High Frequency ◽  
Quality Data ◽  
Low Velocity ◽  
Conventional Design ◽  
Seismic Acquisition ◽  
Similar Cost ◽  
Station Density

Abstract Summary Compressive sensing (CS) of seismic data is a new style of seismic acquisition whereby the data are recorded on a pseudorandom grid rather than along densely sampled lines in a conventional design. A CS design with a similar station density will generally yield better quality data at a similar cost compared to a conventional design, whereas a CS design with a lower station density will reduce costs while retaining quality. Previous authors (Mosher, 2014) have shown good results from CS surveys using proprietary methods for the design and processing. In this paper we show results obtained using commercially available services based on published algorithms (Lopez, 2016). This is a necessary requirement for adoption of CS by our industry. This report documents the results of a 108km2 CS acquisition and processing trial. The acquisition and processing were specifically designed to establish whether CS can be used for suppression of backscattered, low velocity, high frequency surface waves. We demonstrate that CS data can be reconstructed by a commercial contractor and that the suppression of backscattered surface waves is improved by using CS receiver gathers reconstructed to a dense shot grid. We also show that CS acquisition is a reliable alternative to conventional acquisition from which high-quality subsurface images can be formed.

Time-Lapse Monitoring of Daily Velocity Changes in Binchuan, Southwestern China, Using Large-Volume Air-Gun Source Array Data

2022 ◽  
Author(s):  
Yi Luan ◽  
Hongfeng Yang ◽  
Baoshan Wang ◽  
Wei Yang ◽  
Weitao Wang ◽  
...  
Keyword(s):  
Large Volume ◽  
Seismic Data ◽  
Temporal Changes ◽  
Air Pressure ◽  
Southwestern China ◽  
Long Period ◽  
Air Gun ◽  
Velocity Variations ◽  
Velocity Changes ◽  
Source Array

Abstract Temporal changes of seismic velocities in the Earth’s crust can be induced by stress perturbations or material damage from reasons such as strong ground motion, volcanic activities, and atmospheric effects. However, monitoring the temporal changes remains challenging, because most of them generally exist in small travel-time differences of seismic data. Here, we present an excellent case of daily variations of the subsurface structure detected using a large-volume air-gun source array of one-month experiment in Binchuan, Yunnan, southwestern China. The seismic data were recorded by 12 stations within ∼10 km away from the source and used to detect velocity change in the crust using the deconvolution method and sliding window cross-correlation method, which can eliminate the “intercept” error when cutting the air-gun signals and get the real subsurface variations. Furthermore, the multichannel singular spectral analysis method is used to separate the daily change (∼1 cycle per day) from the “long-period” change (<1 cycle per day) or noise. The result suggests that the daily velocity changes at the two nearest stations, 53277 (offset ∼700 m) and 53278 (offset ∼2.3 km), are well correlated with air temperature variation with a time lag of 5.0 ± 1.5 hr, which reflects that the velocity variations at the subsurface are likely attributed to thermoelastic strain. In contrast, both daily and long-period velocity changes at distant stations correlate better with the varying air pressure than the temperature, indicating that the velocity variations at deeper depth are dominated by the elastic loading of air pressure. Our results demonstrate that the air-gun source is a powerful tool to detect the velocity variation of the shallow crust media.

Attenuated high-frequency emission from a new design of air-gun

2014 ◽  
Author(s):  
Emmanuel Coste ◽  
David Gerez ◽  
Halvor Groenaas ◽  
Ola Pramm Larsen ◽  
Michel Wolfstirn ◽  
...  
Keyword(s):  
High Frequency ◽  
Air Gun ◽  
Frequency Emission

Introduction to this special section: Acquisition and sensing

2019 ◽  
Vol 38 (9) ◽  
pp. 670-670
Author(s):  
Margarita Corzo ◽  
Tim Brice ◽  
Ray Abma
Keyword(s):  
Special Section ◽  
Seismic Survey ◽  
Ocean Bottom ◽  
Total Cost ◽  
Small Boat ◽  
Air Gun ◽  
Seismic Acquisition ◽  
The Cost ◽  
Seismic Images

Seismic acquisition has undergone a revolution over the last few decades. The volume of data acquired has increased exponentially, and the quality of seismic images obtained has improved tremendously. While the total cost of acquiring a seismic survey has increased, the cost per trace has dropped precipitously. Land surveys have evolved from sparse 2D lines acquired with a few dozen receivers to densely sampled 3D multiazimuth surveys. Marine surveys that once may have consisted of a small boat pulling a single cable have evolved to large streamer vessels pulling multiple cables and air-gun arrays and to ocean-bottom detectors that require significant fleets to place the detectors, shoot the sources, and provide support. These surveys collect data that are wide azimuth and typically fairly well sampled.

scholarly journals High frequency ghost cavitation - a comparison of two seismic air-gun arrays using numerical modelling

2017 ◽  
Vol 125 ◽  
pp. 153-160 ◽  
Author(s):  
Babak Khodabandeloo ◽  
Martin Landrø
Keyword(s):  
Numerical Modelling ◽  
High Frequency ◽  
Air Gun

High-frequency signals from air-gun arrays

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. Q19-Q27 ◽  
Author(s):  
M. Landrø ◽  
L. Amundsen ◽  
D. Barker
Keyword(s):  
High Frequency ◽  
Experimental Testing ◽  
Seismic Sources ◽  
Frequency Noise ◽  
Suggested Model ◽  
Frequency Effects ◽  
High Frequency Noise ◽  
Air Gun ◽  
Marine Seismic ◽  
High Frequency Effects

We suggest two different mechanisms for generation of high-frequency signals from seismic sources: one type that we interpret as being caused by high-frequency effects close to and within each individual air gun and another type caused by an effect that we refer to as ghost cavitation. The former one is found to have a steep decreasing amplitude trend with frequency, while the latter has a close to 1/f attenuation for frequencies above 1 kHz. A thorough understanding of the effects is of significant importance to quantify and estimate any environmental impact of marine seismic air-gun arrays. The proposed ghost-cavitation mechanism needs further experimental testing. However, given that the suggested model is proven, we think it is possible to attenuate the high-frequency noise generated by compact air-gun arrays by increasing the areal extent of the gun array.

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