Automatic source localization of diffracted seismic noise in shallow water

We evaluated an automatic source localization approach for diffracted seismic noise (DSN) attenuation based on apex recognition. The potential DSNs in each shot gather were first detected by identifying their apexes. Then, the positions of these detected apexes were used to calculate the source locations of their corresponding DSNs. After that, according to the distribution of the source locations obtained in all shot gathers in one seismic line, we removed some false detected DSNs and further improved the source location estimates of the remaining ones. By assuming that the source location of one DSN is fixed or slowly changed during the seismic data acquisition, for a truly existing DSN, its multiple source location estimates, which are obtained from different streamers in multiple shot gathers, should focus. Therefore, a clustering algorithm was applied to obtain the source location estimates of the final selected DSNs and remove the false recognized DSNs at the same time. To verify the source localization results obtained, we suppressed these DSNs by flattening them along their trajectories and extracting them by multichannel filters, similar to other existing methodologies. A real 3D marine data example demonstrated that the proposed method obtains some promising results for attenuation of the DSNs.

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Nonstretch normal moveout through iterative partial correction and deconvolution

Geophysics ◽

10.1190/geo2013-0392.1 ◽

2014 ◽

Vol 79 (4) ◽

pp. V131-V141 ◽

Cited By ~ 8

Author(s):

Ettore Biondi ◽

Eusebio Stucchi ◽

Alfredo Mazzotti

Keyword(s):

Seismic Data ◽

Singular Value ◽

Long Offset ◽

Nmo Correction ◽

Seismic Data Acquisition ◽

Marine Data ◽

Value Decomposition ◽

Nmo Stretch ◽

Space Variant ◽

Partial Correction

Source to receiver distances used in seismic data acquisition have been steadily increasing and it is now common to work with data acquired with more than 10 km of offset. Subbasalt exploration and seismic undershooting are just two applications in which long-offset reflections are sought. However, such reflections are often subjected to muting to suppress normal moveout (NMO) stretch artifacts, thus causing a loss of valuable information. To retrieve these portions of the recorded wavefield, we developed a nonstretch NMO correction based on wavelet estimation and on an iterative procedure of partial NMO correction and deconvolution. We evaluated this methodology using fourth-order traveltime curve approximations to increase the offset of usable reflections, but it can be adapted to traveltime curves of any order. Time- and space-variant wavelets, estimated by means of singular value decomposition along the sought traveltimes, were used to build the desired output for the deconvolution that aims at retrieving the original shape of the partially stretched wavelets. We tested our method on a synthetic gather presenting time and offset varying wavelets, on a real-marine line simulating an undershooting pattern and on true undershooting land-marine data. These examples demonstrated that our new algorithm effectively limits the stretching associated with the NMO correction and enables the recovery of those portions of the stacked sections that are typically lost from muting in the standard NMO correction.

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Multicomponent OBC (4C) Seismic Data Acquisition Challenges And Solution-Design, Operation, And Field Quality Control: Case Study OBC Bekapai

10.29118/ipa.0.13.g.112 ◽

2018 ◽

Author(s):

Pian Nopiana

Keyword(s):

Quality Control ◽

Data Acquisition ◽

Seismic Data ◽

Control Case ◽

Field Quality ◽

Solution Design ◽

Seismic Data Acquisition

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APPLICATION OF THE EMPIRICAL MODE DECOMPOSITION METHOD TO GROUND-ROLL NOISE ATTENUATION IN SEISMIC DATA

Brazilian Journal of Geophysics ◽

10.22564/rbgf.v31i4.342 ◽

2013 ◽

Vol 31 (4) ◽

pp. 619 ◽

Cited By ~ 1

Author(s):

Luiz Eduardo Soares Ferreira ◽

Milton José Porsani ◽

Michelângelo G. Da Silva ◽

Giovani Lopes Vasconcelos

Keyword(s):

Empirical Mode Decomposition ◽

Seismic Data ◽

Low Frequency ◽

High Amplitude ◽

Seismic Line ◽

Seismic Processing ◽

Mode Decomposition ◽

Ground Roll ◽

Fortran 90 ◽

Emd Method

ABSTRACT. Seismic processing aims to provide an adequate image of the subsurface geology. During seismic processing, the filtering of signals considered noise is of utmost importance. Among these signals is the surface rolling noise, better known as ground-roll. Ground-roll occurs mainly in land seismic data, masking reflections, and this roll has the following main features: high amplitude, low frequency and low speed. The attenuation of this noise is generally performed through so-called conventional methods using 1-D or 2-D frequency filters in the fk domain. This study uses the empirical mode decomposition (EMD) method for ground-roll attenuation. The EMD method was implemented in the programming language FORTRAN 90 and applied in the time and frequency domains. The application of this method to the processing of land seismic line 204-RL-247 in Tacutu Basin resulted in stacked seismic sections that were of similar or sometimes better quality compared with those obtained using the fk and high-pass filtering methods.Keywords: seismic processing, empirical mode decomposition, seismic data filtering, ground-roll. RESUMO. O processamento sísmico tem como principal objetivo fornecer uma imagem adequada da geologia da subsuperfície. Nas etapas do processamento sísmico a filtragem de sinais considerados como ruídos é de fundamental importância. Dentre esses ruídos encontramos o ruído de rolamento superficial, mais conhecido como ground-roll . O ground-roll ocorre principalmente em dados sísmicos terrestres, mascarando as reflexões e possui como principais características: alta amplitude, baixa frequência e baixa velocidade. A atenuação desse ruído é geralmente realizada através de métodos de filtragem ditos convencionais, que utilizam filtros de frequência 1D ou filtro 2D no domínio fk. Este trabalho utiliza o método de Decomposição em Modos Empíricos (DME) para a atenuação do ground-roll. O método DME foi implementado em linguagem de programação FORTRAN 90, e foi aplicado no domínio do tempo e da frequência. Sua aplicação no processamento da linha sísmica terrestre 204-RL-247 da Bacia do Tacutu gerou como resultados, seções sísmicas empilhadas de qualidade semelhante e por vezes melhor, quando comparadas as obtidas com os métodos de filtragem fk e passa-alta.Palavras-chave: processamento sísmico, decomposição em modos empíricos, filtragem dados sísmicos, atenuação do ground-roll.

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Restricted model domain time Radon transforms

Geophysics ◽

10.1190/geo2016-0270.1 ◽

2016 ◽

Vol 81 (6) ◽

pp. A17-A21 ◽

Cited By ~ 7

Author(s):

Juan I. Sabbione ◽

Mauricio D. Sacchi

Keyword(s):

Inverse Problem ◽

Seismic Data ◽

Computational Cost ◽

Synthetic Data ◽

Model Space ◽

Radon Transforms ◽

Iterative Solver ◽

Hard Thresholding ◽

Restricted Model ◽

Marine Data

The coefficients that synthesize seismic data via the hyperbolic Radon transform (HRT) are estimated by solving a linear-inverse problem. In the classical HRT, the computational cost of the inverse problem is proportional to the size of the data and the number of Radon coefficients. We have developed a strategy that significantly speeds up the implementation of time-domain HRTs. For this purpose, we have defined a restricted model space of coefficients applying hard thresholding to an initial low-resolution Radon gather. Then, an iterative solver that operated on the restricted model space was used to estimate the group of coefficients that synthesized the data. The method is illustrated with synthetic data and tested with a marine data example.

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