3D prediction of surface-related and interbed multiples

Geophysics ◽  
2006 ◽  
Vol 71 (1) ◽  
pp. V1-V6 ◽  
Author(s):  
Moshe Reshef ◽  
Shahar Arad ◽  
Evgeny Landa
Keyword(s):  
Data Processing ◽  
Time Domain ◽  
Final Section ◽  
Real Data ◽  
Computational Procedure ◽  
Detailed Knowledge ◽  
Geological Model ◽  
Multiple Attenuation ◽  
The Time Domain ◽  
Kinematic Properties

Multiple attenuation during data processing does not guarantee a multiple-free final section. Multiple identification plays an important role in seismic interpretation. A target-oriented method for predicting 3D multiples on stacked or migrated cubes in the time domain is presented. The method does not require detailed knowledge of the subsurface geological model or access to prestack data and is valid for both surface-related and interbed multiples. The computational procedure is based on kinematic properties of the data and uses Fermat's principle to define the multiples. Since no prestack data are required, the method can calculate 3D multiples even when only multi-2D survey data are available. The accuracy and possible use of the method are demonstrated on synthetic and real data examples.

Migration velocity analysis based on focusing diffractions generated using the CRS wavefront attributes: Application to real land data

Geophysics ◽  
2021 ◽  
pp. 1-50
Author(s):  
German Garabito ◽  
José Silas dos Santos Silva ◽  
Williams Lima
Keyword(s):  
Time Domain ◽  
Real Data ◽  
Normal Incidence ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Analysis ◽  
Velocity Models ◽  
Time Migration ◽  
Migration Velocity Analysis ◽  
The Time Domain

In land seismic data processing, the prestack time migration (PSTM) image remains the standard imaging output, but a reliable migrated image of the subsurface depends on the accuracy of the migration velocity model. We have adopted two new algorithms for time-domain migration velocity analysis based on wavefield attributes of the common-reflection-surface (CRS) stack method. These attributes, extracted from multicoverage data, were successfully applied to build the velocity model in the depth domain through tomographic inversion of the normal-incidence-point (NIP) wave. However, there is no practical and reliable method for determining an accurate and geologically consistent time-migration velocity model from these CRS attributes. We introduce an interactive method to determine the migration velocity model in the time domain based on the application of NIP wave attributes and the CRS stacking operator for diffractions, to generate synthetic diffractions on the reflection events of the zero-offset (ZO) CRS stacked section. In the ZO data with diffractions, the poststack time migration (post-STM) is applied with a set of constant velocities, and the migration velocities are then selected through a focusing analysis of the simulated diffractions. We also introduce an algorithm to automatically calculate the migration velocity model from the CRS attributes picked for the main reflection events in the ZO data. We determine the precision of our diffraction focusing velocity analysis and the automatic velocity calculation algorithms using two synthetic models. We also applied them to real 2D land data with low quality and low fold to estimate the time-domain migration velocity model. The velocity models obtained through our methods were validated by applying them in the Kirchhoff PSTM of real data, in which the velocity model from the diffraction focusing analysis provided significant improvements in the quality of the migrated image compared to the legacy image and to the migrated image obtained using the automatically calculated velocity model.

Dip moveout in the Radon domain

Geophysics ◽  
1999 ◽  
Vol 64 (1) ◽  
pp. 278-288
Author(s):  
Chengshu Wang
Keyword(s):  
Time Domain ◽  
Three Dimensional ◽  
Fourier Method ◽  
Real Data ◽  
Processing Technique ◽  
The Common ◽  
The Time Domain

I consider a new dip‐moveout (DMO) processing technique in the Radon domain called Radon DMO. The Radon DMO operator directly maps data from the NMO-corrected time domain to the DMO wavefield in the Radon domain. The method is built upon a process that transforms a single NMO-corrected trace into multiple traces spread along hyperbolas in the Radon domain. These hyperbolas are a linear Radon map of the DMO ellipses in the time domain. In this paper, I introduce the amplitude‐preserving Radon DMO and compare some examples of Radon DMO and Fourier DMO for both synthetic and real data. I also show the better frequency preservation properties of the Radon DMO method. Three‐dimensional data are often irregularly sampled with respect to fold, azimuth, and offset. Population deficiencies are exaggerated in the common‐offset domain. Radon DMO does not require that input traces belong to one common‐offset bin as does the Fourier method. Input traces can be organized from multiple offset bins grouping to perform Radon DMO, which is well used in 3-D surveys. Some synthetic and real data examples show these properties.

Measurements of Shielding Effectiveness of Textile Materials Containing Metal by the Free-Space Transmission Technique with Data Processing in the Time Domain

2013 ◽  
Vol 20 (2) ◽  
pp. 217-228 ◽  
Author(s):  
Nadezhda Dvurechenskaya ◽  
Pawe R. Bajurko ◽  
Ryszard J. Zieliński ◽  
Yevhen Yashchyshyn
Keyword(s):  
Data Processing ◽  
Time Domain ◽  
Free Space ◽  
Coaxial Line ◽  
Shielding Effectiveness ◽  
Experimental Data Processing ◽  
Textile Materials ◽  
Transmission Technique ◽  
Set Up ◽  
The Time Domain

Abstract The results of shielding effectiveness (SE) measurements of textile materials containing metal by the free-space transmission technique (FSTT) in the 1-26.5 GHz frequency range are presented in the paper. It is shown that experimental data processing using time-domain gating (TDG) makes it possible to effectively remove diffracted and reflected components from the desired signal. The comparison with the results obtained by other techniques, namely modified FSTT with TDG and coaxial line probe technique (ASTM D4935-99) is given. The comparison shows that the proposed technique gives more reasonable results while the measurement set-up is simpler in realization.

A non-linear model for elastic hysteresis in the time domain: Computational procedure

2020 ◽  
pp. 095440622098202
Author(s):  
MMS Dwaikat ◽  
C Spitas ◽  
V Spitas
Keyword(s):  
Time Domain ◽  
Mechanical Energy ◽  
Numerical Procedure ◽  
Time History ◽  
Computational Procedure ◽  
Continuous Systems ◽  
Full Time ◽  
Proposed Model ◽  
History Of ◽  
The Time Domain

Hysteretic damping of a material or structure loaded within its elastic region is the dissipation of mechanical energy at a rate independent of the frequency of vibration while at the same time directly proportional to the square of the displacement. Generally, reproducing this frequency-independent damping can be computationally complex and requires prior knowledge of the system’s natural frequencies or the full time history of the system’s response. In this paper, a new model and numerical procedure are proposed whereby hysteretic material damping is achieved in the time domain. The proposed procedure is developed based on modifying the viscous model through a correction factor calculated exclusively using the local response. The superiority of the proposed approach lies in its ability to capture material hysteresis without any knowledge of the eigen- or modal frequencies of the system and without knowledge of the past time history of the system’s response or the characteristics of any excitation forces. A numerical procedure is also presented for implementing the proposed model in vibration analysis. The simplicity of the approach enables its generalisation to continuous systems and to systems of multi-degrees of freedom as demonstrated herein. The proposed model is presented as a correction to the viscous damping model which makes it attractive to implement into commercial finite element package using user-defined element subroutines as demonstrated in this study.

Time- and offset-domain internal multiple prediction with nonstationary parameters

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. V105-V116 ◽  
Author(s):  
Kristopher A. Innanen
Keyword(s):  
Plane Wave ◽  
Inverse Scattering ◽  
Time Domain ◽  
Quantitative Interpretation ◽  
Seismic Processing ◽  
Priority Area ◽  
Multiple Attenuation ◽  
Multiple Prediction ◽  
The Time Domain ◽  
Prediction Parameters

Practical internal multiple prediction and removal is a high-priority area of research in seismic processing technology. Its significance increases in plays in which data are complex and sophisticated quantitative interpretation methods are apt to be applied. When the medium is unknown and/or complex, and moveout-based primary/multiple discrimination is not possible, inverse scattering-based internal multiple attenuation is the method of choice. However, challenges remain for its application in certain environments. For instance, when generators are widely distributed and are separated in space by a range of distances, optimum prediction parameters such as [Formula: see text] (which limits the proximity of events combined in the prediction) are difficult to determine. In some cases, we find that no stationary value of [Formula: see text] can optimally predict all multiples without introducing damaging artifacts. A reformulation and implementation in the time domain permits time nonstationarity to be enforced on [Formula: see text], after which a range of possible data- and geology-driven criteria for selecting an [Formula: see text] schedule can be analyzed. The 1D and 1.5D versions of the time-nonstationary algorithm are easily derived and can be shown to add a new element of precision to prediction in challenging environments. Merging these ideas with multidimensional plane-wave domain versions of the algorithm provides 2D/3D extensions.

An accelerated sparse time-invariant Radon transform in the mixed frequency-time domain based on iterative 2D model shrinkage

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. V147-V155 ◽  
Author(s):  
Wenkai Lu
Keyword(s):  
Least Squares ◽  
Frequency Domain ◽  
Time Domain ◽  
Radon Transform ◽  
Real Data ◽  
Mixed Frequency ◽  
The Time Domain ◽  
Domain I ◽  
Time Invariant ◽  
2D Model

I have developed an accelerated sparse time-invariant Radon transform (RT) in the mixed frequency-time domain based on iterative 2D model shrinkage in the time domain. I denote it as SRTIS. In the traditional sparse time-invariant RT in the mixed frequency-time domain, the sparse RT is modeled as a sparse inverse problem that is solved by the iteratively reweighted least-squares (IRLS) algorithm in the time domain, and the forward and inverse RTs are implemented in the frequency domain. In this method, IRLS is replaced by iterative 2D model shrinkage, i.e., the sparsity of the Radon model is promoted by some simple 2D model shrinkage operations in the time domain. Synthetic and real data demultiple examples using the parabolic RTs are given to demonstrate the better performance of the SRTIS when compared with the least-squares-based RT, the frequency domain sparse RT, and the traditional time-domain sparse RT in the mixed frequency-time domain.

HIGH-SPEED SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY SIGNAL PROCESSING WITH TIME-DOMAIN INTERPOLATION USING GRAPHICS PROCESSING UNIT

2011 ◽  
Vol 04 (03) ◽  
pp. 325-335 ◽  
Author(s):  
XIQI LI ◽  
GUOHUA SHI ◽  
LING WEI ◽  
ZHIHUA DING ◽  
YUDONG ZHANG
Keyword(s):  
Data Processing ◽  
Time Domain ◽  
Processing Speed ◽  
Graphics Processing Unit ◽  
Interpolation Method ◽  
Processing Unit ◽  
Zero Padding ◽  
The Time Domain ◽  
Graphics Processing ◽  
Sd Oct

Sensitivity and data processing speed are important in spectral domain Optical Coherence Tomography (SD-OCT) system. To get a higher sensitivity, zero-padding interpolation together with linear interpolation is commonly used to re-sample the interference data in SD-OCT, which limits the data processing speed. Recently, a time-domain interpolation for SD-OCT was proposed. By eliminating the huge Fast Fourier Transform Algorithm (FFT) operations, the operation number of the time-domain interpolation is much less than that of the zero-padding interpolation. In this paper, a numerical simulation is performed to evaluate the computational complexity and the interpolation accuracy. More than six times acceleration is obtained. At the same time, the normalized mean square error (NMSE) results show that the time-domain interpolation method with cut-off length L = 21 and L = 31 can improve about 1.7 dB and 2.1 dB when the distance mismatch is 2.4 mm than that of zero-padding interpolation method with padding times M = 4, respectively. Furthermore, this method can be applied the parallel arithmetic processing because only the data in the cut-off window is processed. By using Graphics Processing Unit (GPU) with compute unified device architecture (CUDA) program model, a frame (400 A-lines × 2048 pixels × 12 bits) data can be processed in 6 ms and the processing capability can be achieved 164,000 line/s for 1024-OCT and 71,000 line/s for 2048-OCT when the cut-off length is 21. Thus, a high-sensitivity and ultra-high data processing SD-OCT is realized.

scholarly journals PRE STACK DEPTH MIGRATION UNTUK KOREKSI EFEK PULL UP DENGAN MENGGUNAKAN METODE HORIZON BASED DEPTH TOMOGRAPHY PADA LAPANGAN ‘A1 DAN A2’

2020 ◽  
Vol 4 (1) ◽  
pp. 64-77
Author(s):  
Attikah Azzahra ◽  
Bagus Sapto Mulyatno ◽  
Bambang Mujihardi
Keyword(s):  
Data Processing ◽  
Time Domain ◽  
Depth Migration ◽  
Velocity Transformation ◽  
Velocity Modeling ◽  
Interval Velocity ◽  
Time Migration ◽  
And Migration ◽  
Tomography Method ◽  
The Time Domain

In the case of seismic data processing with sandstone lithology such as shale and carbonate often get the result of data processing which have pull up effect especially on the time domain migration result. Pre stack depth migration is a processing based on focusing the amplitude according to the actual depth by using the input interval velocity. Migration is performed using kirchhoff pre stack depth migration algorithm. Pre stack depth migration is done with modeling of horizontal based depth tomography method. This method uses residual moveout correction applied along the horizon-picking line. This research uses two field data that is A1 and A2 Field. A1field has characteristics of carbonate rock that produce pull up shaped similar to carbonate layer. A2 field has a pull-up effect that is not very clear but has build up because of the layer above it. Stages performed starting from the processing of pre stack time migration in the form of velocity picking, generate rms velocity and migration time domain. The pre stack depth migration process begins with a velocity transformation with the dix transformation equation to generate interval velocity, migrate Pre stack depth migration, perform horizon interpretations and perform velocity modeling using the horizon based depth tomography method. The iteration is done 4 times and resulted in the final section of pre stack depth migration which has been corrected by pull up effect.

Modeling of attenuation and dispersion

Geophysics ◽  
1993 ◽  
Vol 58 (8) ◽  
pp. 1167-1173 ◽  
Author(s):  
Carlos Lopo Varela ◽  
Andre L. R. Rosa ◽  
Tadeusz J. Ulrych
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Low Cost ◽  
Real Data ◽  
Dispersion Modeling ◽  
Minimum Phase ◽  
The Time Domain ◽  
Wavefield Extrapolation ◽  
Attenuation And Dispersion ◽  
Proper Solutions

At the present time, proper solutions for absorption modeling are based on wavefield extrapolation techniques which, in some instances, may be considered expensive. Two alternative, low cost, but incomplete solutions exist in the literature. The first models dispersion in the frequency domain in accordance with the Futterman dispersive relations but does not consider attenuation. The second models both attenuation and dispersion in the time domain but assumes a digital minimum‐phase formulation that results in an inadequate treatment of the dispersion. We show that this second solution can be adapted to perform attenuation and/or dispersion modeling in agreement with the Futterman attenuation‐dispersion relationships thus obviating the shortcoming mentioned above. Synthetic and real data examples are shown to illustrate the performance of the proposed algorithm.

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