Multi‐Level airgun array: A simple and effective way to enhance the low frequency content of marine seismic data

2009 ◽  
Author(s):  
Guillaume Cambois ◽  
Andrew Long ◽  
Gregg Parkes ◽  
Terje Lundsten ◽  
Anders Mattsson ◽  
...  
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Frequency Content ◽  
Multi Level ◽  
Marine Seismic

Laplace-domain full-waveform inversion of seismic data lacking low-frequency information

Geophysics ◽  
2012 ◽  
Vol 77 (5) ◽  
pp. R199-R206 ◽  
Author(s):  
Wansoo Ha ◽  
Changsoo Shin
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Single Frequency ◽  
Frequency Content ◽  
Laplace Domain ◽  
Frequency Information ◽  
Velocity Models ◽  
Gaussian Source

The lack of the low-frequency information in field data prohibits the time- or frequency-domain waveform inversions from recovering large-scale background velocity models. On the other hand, Laplace-domain waveform inversion is less sensitive to the lack of the low frequencies than conventional inversions. In theory, frequency filtering of the seismic signal in the time domain is equivalent to a constant multiplication of the wavefield in the Laplace domain. Because the constant can be retrieved using the source estimation process, the frequency content of the seismic data does not affect the gradient direction of the Laplace-domain waveform inversion. We obtained inversion results of the frequency-filtered field data acquired in the Gulf of Mexico and two synthetic data sets obtained using a first-derivative Gaussian source wavelet and a single-frequency causal sine function. They demonstrated that Laplace-domain inversion yielded consistent results regardless of the frequency content within the seismic data.

Broadband seismic over/under sources and their designature-deghosting

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. P61-P73 ◽  
Author(s):  
Lasse Amundsen ◽  
Ørjan Pedersen ◽  
Are Osen ◽  
Johan O. A. Robertsson ◽  
Martin Landrø
Keyword(s):  
Seismic Data ◽  
High Frequency ◽  
Low Frequency ◽  
Point Sources ◽  
High Frequency Side ◽  
Frequency Content ◽  
Source Depth ◽  
Deep Sources ◽  
The Cost ◽  
High Frequency Content

The source depth influences the frequency band of seismic data. Due to the source ghost effect, it is advantageous to deploy sources deep to enhance the low-frequency content of seismic data. But, for a given source volume, the bubble period decreases with the source depth, thereby degrading the low-frequency content. At the same time, deep sources reduce the seismic bandwidth. Deploying sources at shallower depths has the opposite effects. A shallow source provides improved high-frequency content at the cost of degraded low-frequency content due to the ghosting effect, whereas the bubble period increases with a lesser source depth, thereby slightly improving the low-frequency content. A solution to the challenge of extending the bandwidth on the low- and high-frequency side is to deploy over/under sources, in which sources are towed at two depths. We have developed a mathematical ghost model for over/under point sources fired in sequential and simultaneous modes, and we have found an inverse model, which on common receiver gathers can jointly perform designature and deghosting of the over/under source measurements. We relate the model for simultaneous mode shooting to recent work on general multidepth level array sources, with previous known solutions. Two numerical examples related to over/under sequential shooting develop the main principles and the viability of the method.

scholarly journals Deep learning for low-frequency extrapolation from multioffset seismic data

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. R989-R1001 ◽  
Author(s):  
Oleg Ovcharenko ◽  
Vladimir Kazei ◽  
Mahesh Kalita ◽  
Daniel Peter ◽  
Tariq Alkhalifah
Keyword(s):  
Deep Learning ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Low Frequencies ◽  
Seismic Surveys ◽  
Full Waveform ◽  
Frequency Components ◽  
Marine Seismic

Low-frequency seismic data are crucial for convergence of full-waveform inversion (FWI) to reliable subsurface properties. However, it is challenging to acquire field data with an appropriate signal-to-noise ratio in the low-frequency part of the spectrum. We have extrapolated low-frequency data from the respective higher frequency components of the seismic wavefield by using deep learning. Through wavenumber analysis, we find that extrapolation per shot gather has broader applicability than per-trace extrapolation. We numerically simulate marine seismic surveys for random subsurface models and train a deep convolutional neural network to derive a mapping between high and low frequencies. The trained network is then tested on sections from the BP and SEAM Phase I benchmark models. Our results indicate that we are able to recover 0.25 Hz data from the 2 to 4.5 Hz frequencies. We also determine that the extrapolated data are accurate enough for FWI application.

Local‐trace zeroing and spike zeroing: Two short automated noise‐rejection routines to remove noise and spikes on seismic traces

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 188-196 ◽  
Author(s):  
Giuseppe Stanghellini ◽  
Claudia Bonazzi
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
User Interaction ◽  
Weather Conditions ◽  
Processing Parameters ◽  
Noise Rejection ◽  
Bad Weather ◽  
Marine Seismic ◽  
Spurious Signals ◽  
Incoherent Noise

The acquisition of marine seismic data is often affected by noise that introduces spurious signals. Due to the length of the receiver streamer, bad weather conditions can produce low‐frequency, high‐intensity incoherent noise and/or spikes that can be difficult to remove by means of conventional mathematical filters. In this paper we present two Fortran routines suitable to locate and remove the noise in the low and very low frequency ranges and to locate and suppress spikes. These two routines are designed to run without user interaction once the processing parameters are selected. Both routines are simple and compact, and can be included in any processing software.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

Delaying the source ghost to improve the ultralow-frequency response of a marine air-gun source

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. P45-P51
Author(s):  
Honglei Shen ◽  
Thomas Elboth ◽  
Chunhui Tao ◽  
Gang Tian ◽  
Hanchuang Wang ◽  
...  
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Ultralow Frequency ◽  
Full Waveform ◽  
Air Gun ◽  
Marine Source ◽  
Frequency Output ◽  
Marine Seismic ◽  
Marine Air

The competing effect between the fundamental bubble and its source-ghost response results in a strong attenuation of the lowest frequencies (below 7 Hz). This loss cannot be compensated easily by adjusting the source depth. Consequently, the low-frequency content in marine seismic data is not optimal, degrading the performance of low-frequency dependent processing approaches, such as full-waveform inversion. To overcome this, we have developed an additional source to counteract the ghost from the main source. In this situation, the fundamental bubble is characterized by the depth of the main source, whereas the ghost response is characterized by the summed depth of the main and additional sources. This source setup mitigates the competing effect and reduces the suppression of ultralow frequencies. Compared with a conventional horizontal source, our source design will reduce the mid- to high-frequency output, which may be beneficial in situations in which environmental constraints limit the maximum allowed output of a marine source.

The music of marine seismic: A marine vibrator system based on folded surfaces

2020 ◽  
Vol 39 (4) ◽  
pp. 254-263
Author(s):  
Okwudili C. Orji ◽  
Mattias Oscarsson-Nagel ◽  
Walter Söllner ◽  
Endrias G. Asgedom ◽  
Øystein Trætten ◽  
...  
Keyword(s):  
Seismic Data ◽  
Frequency Tuning ◽  
Synthetic Data ◽  
Harmonic Distortion ◽  
Low Frequency ◽  
Source Control ◽  
Environmental Friendliness ◽  
Air Gun ◽  
Frequency Module ◽  
Marine Seismic

Marine vibrators have bespoke geophysical benefits that are yet to be harnessed because of robustness and efficiency issues. We have developed a new marine vibrator source technology that is efficient and stable. The source technology overcomes the historical problems of inefficiency and robustness by using folded surface technology and resonance frequency tuning. We show measured output examples that demonstrate that the folded surface concept combined with small displacements can provide the required output levels. Our source system consists of a low-frequency module covering 1–10 Hz and a high-frequency module covering 10–125 Hz. The source control system has shown high stability and precision and can handle harmonic distortion. With the aid of synthetic data examples, we demonstrate that seismic data acquired using marine vibrators in either intermittent or continuous mode can be processed. Finally, we demonstrate the environmental friendliness of the source in comparison to air gun-based sources.

scholarly journals A low-frequency deghosting method: Analysis and numerical tests

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. V285-V296 ◽  
Author(s):  
Ying Wang ◽  
Adriana Citlali Ramirez ◽  
Are Osen
Keyword(s):  
Seismic Data ◽  
Fast Track ◽  
Low Frequency ◽  
Frequency Component ◽  
Data Sets ◽  
Numerical Tests ◽  
The Earth ◽  
Enhanced Resolution ◽  
Marine Seismic ◽  
Method Analysis

The low-frequency component of seismic data can be beneficial for several reasons: improved signal penetration into the earth, enhanced resolution, and better constrained inversion results. We have developed a detailed analysis of a deghosting solution for the low-frequency spectrum of marine seismic pressure data. The advantages of this low-frequency deghosting method are: (1) it can be applied in the spatial domain, (2) it is applicable for horizontal streamers and for streamers with a mild depth variation, and (3) it is a fast-track solution that can be used flexibly as a preprocessing, or premigration step. The disadvantages of this method are: (1) it is an approximation to the full-deghosting operator and cannot infill the ghost notches of the spectrum, except near 0 Hz, and (2) it has decreasing effectiveness with a larger source/receiver depth. Numerical tests on the synthetic and field data sets indicate that this method is promising in deghosting data, up to at least half the frequency of the first nonzero ghost notch.

Formation geological depth image according to refraction and reflection marine seismic data

2017 ◽  
Vol 39 (6) ◽  
pp. 106-121
Author(s):  
A. O. Verpahovskaya ◽  
V. N. Pilipenko ◽  
Е. V. Pylypenko
Keyword(s):  
Seismic Data ◽  
Depth Image ◽  
Marine Seismic
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