scholarly journals Attenuation of specular and diffracted 2D multiples in image space

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. V97-V109 ◽  
Author(s):  
Gabriel Alvarez ◽  
Biondo Biondi ◽  
Antoine Guitton
Keyword(s):  
Radon Transform ◽  
3D Model ◽  
Model Space ◽  
Image Space ◽  
Attractive Alternative ◽  
Seismic Line ◽  
Data Space ◽  
Zero Curvature ◽  
Multiple Elimination ◽  
Water Bottom

In complex areas, the attenuation of specular and diffracted multiples in image space is an attractive alternative to surface-related multiple elimination (SRME) and to data space Radon filtering. We present the equations that map, via wave-equation migration, 2D diffracted and specular water-bottom multiples from data space to image space. We show the equations for both subsurface-offset-domain common-image-gathers (SODCIGs) and angle-domain common-image-gathers (ADCIGs). We demonstrate that when migrated with sediment velocities, the over-migrated multiples map to predictable regions in both SODCIGs and ADCIGs. Specular multiples focus similarly to primaries, whereas diffracted multiples do not. In particular, the apex of the residual moveout curve of diffracted multiples in ADCIGs is not located at the zero aperture angle. We use our equation of the residual moveout of the multiples in ADCIGs to design an apex-shifted Radon transform that maps the 2D ADCIGs into a 3D model space cube whose dimensions are depth, curvature, and apex-shift distance. Well-corrected primaries map to or near the zero-curvature plane and specularly reflected multiples map to or near the zero apex-shift plane. Diffracted multiples map elsewhere in the cube according to their curvature and apex-shift distance. Thus, specularly reflected as well as diffracted multiples can be attenuated simultaneously. We show the application of our apex-shifted Radon transform to a 2D seismic line from the Gulf of Mexico. Diffracted multiples originate at the edges of the salt body and we show that we can successfully attenuate them, along with the specular multiples, in the image Radon domain.

Multiple attenuation in the image space

Geophysics ◽  
2005 ◽  
Vol 70 (1) ◽  
pp. V10-V20 ◽  
Author(s):  
Paul Sava ◽  
Antoine Guitton
Keyword(s):  
Real Data ◽  
Velocity Model ◽  
Image Space ◽  
Radon Transforms ◽  
Data Space ◽  
Multiple Attenuation ◽  
3D Data ◽  
Propagation Effects ◽  
Wavefield Extrapolation ◽  
Multiple Elimination

Multiples can be suppressed in the angle-domain image space after migration. For a given velocity model, primaries and multiples have different angle-domain moveout and, therefore, can be separated using techniques similar to the ones employed in the data space prior to migration. We use Radon transforms in the image space to discriminate between primaries and multiples and employ accurate functions describing angle-domain moveouts. Since every individual angle-domain common-image gather incorporates complex 3D propagation effects, our method has the advantage of working with 3D data and complicated geology. Therefore, our method offers an alternative to the more expensive surface-related multiple-elimination (SRME) approach operating in the data space. Radon transforms are cheap but not necessarily ideal for separating primaries and multiples, particularly at small angles where the moveout discrepancy between the two kinds of events are not large. Better techniques involving signal/noise separation using prediction-error filters can be employed as well, although such approaches fall outside the scope of this paper. We demonstrate, using synthetic and real data examples, the power of our method in discriminating between primaries and multiples after migration by wavefield extrapolation, followed by transformation to the angle domain.

scholarly journals Image-space surface-related multiple prediction

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. S113-S122 ◽  
Author(s):  
Brad Artman ◽  
Gabriel Alvarez ◽  
Ken Matson
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
Image Space ◽  
Depth Level ◽  
Image Domain ◽  
Data Space ◽  
The Earth ◽  
Multiple Prediction ◽  
The Cost ◽  
Multiple Elimination

A very important aspect of removing multiples from seismic data is accurate prediction of their kinematics. We cast the multiple prediction problem as an operation in the image space parallel to the conventional surface-related multiple-prediction methodology. Though developed in the image domain, the technique shares the data-driven strengths of data-domain surface-related multiple elimination (SRME) by being independent of the earth (velocity) model. Also, the data are used to predict the multiples exactly so that a Radon transform need not be designed to separate the two types of events. The cost of the prediction is approximately the same as that of data-space methods, though it can be computed during the course of migration. The additional cost is not significant compared to that incurred by shot-profile migration, though split-spread gathers must be used. Image-space multiple predictions are generated by autoconvolving the traces in each shot-gather at every depth level during the course of a shot-profile migration. The prediction in the image domain is equivalent to that produced by migrating the data-space convolutional prediction. Adaptive subtraction of the prediction from the image is required. Subtraction in the image domain, however, provides the advantages of focused energy in a smaller domain since extrapolation removes some of the imperfections of the input data.

3D Model Reconstruction from Multi-views of 2D Images using Radon Transform

2015 ◽  
Vol 74 (6) ◽  
Author(s):  
Siti Syazalina Mohd. Sobani ◽  
Nasrul Humaimi Mahmood ◽  
Nor Aini Zakaria ◽  
Ismail Ariffin
Keyword(s):  
Radon Transform ◽  
3D Model ◽  
Digital Camera ◽  
Computation Method ◽  
Model Reconstruction ◽  
Fixed Sequence ◽  
Model Object ◽  
3D Model Reconstruction ◽  
Images Processing ◽  
2D Images

This paper presents a simple computation method to reconstruct 3-dimensional (3D) model from a sequence of 2-dimensional (2D) images using a multiple-view camera setup. The 3D model is acquired by applying several images processing on few 2D images captured by digital camera with different angle of views. The setup for this study consisted of a digital camera mounted on a tripod stand focusing at a block of model object on a turntable with black floor and background. 36 different angles are used to capture the images where every view angle differs by ten degree (10°) with another view in a fixed sequence. The image processing applied on all 2D images to be reconstructed as 3D surface are image segmentation, Radon transform (RT), image filtering, morphological operation, edge detection, and boundary extraction. The results for 3D model reconstruction shows it is well reconstructed, with a smooth texture obtained using 3D mesh and Delaunay triangulation, while the shape is nearly identical to the original model while the remaining are distinguishable.  

scholarly journals ATENUASI WATER-BOTTOM MULTIPLE DENGAN METODE TRANSFORMASI PARABOLIC RADON

2016 ◽  
Vol 12 (3) ◽  
pp. 145
Author(s):  
Subarsyah Subarsyah ◽  
Tumpal Benhard Nainggolan
Keyword(s):  
Radon Transform ◽  
Seismic Data ◽  
Wide Distribution ◽  
Seismic Section ◽  
Optimal Separation ◽  
Multiple Attenuation ◽  
Parabolic Radon Transform ◽  
Water Bottom

Interferensi water-bottom multipel terhadap reflektor primer menimbulkan efek bersifat destruktif yang menyebabkan penampang seismik menjadi tidak tepat akibat kehadiran reflektor semu. Teknik demultiple perlu diaplikasikan untuk mengatenuasi multipel. Transformasi parabolic radon merupakan teknik atenuasi multipel dengan metode pemisahan dalam domain radon. Multipel sering teridentifikasi pada penampang seismik. Untuk memperbaiki penampang seismik akan dilakukan dengan metode transformasi parabolic radon. Penerapan metode ini mengakibatkan reflektor multipel melemah dan tereduksi setelah dilakukan muting dalam domain radon terhadap zona multipel. Beberapa reflektor primer juga ikut melemah akibat pemisahan dalam domain radon yang kurang optimal, pemisahan akan optimal membutuhkan distribusi offset yang lebar. Kata kunci: Parabolic radon, multipel, atenuasi Water-bottom mutiple interference often destructively interfere with primary reflection that led to incorrect seismic section due to presence apparent reflector. Demultiple techniques need to be applied to attenuate the multiple. Parabolic Radon transform is demultiple attenuation technique that separate multiple and primary in radon domain. Water-bottom mutiple ussualy appear and easly identified on seismic data, parabolic radon transform applied to improve the seismic section. Application of this method to data showing multiple reflectors weakened and reduced after muting multiple zones in the radon domain. Some of the primary reflector also weakened due to bad separation in radon domain, optimal separation will require a wide distribution of offsets. Keywords: Parabolic radon, multiple, attenuation

scholarly journals Practical Implementation of Multiple Attenuation Methods on 2D Deepwater Seismic Data : Seram Sea Case Study

2017 ◽  
Vol 32 (1) ◽  
Author(s):  
Tumpal Bernhard Nainggolan ◽  
Deny Setiady
Keyword(s):  
Seismic Data ◽  
Input Data ◽  
Complex Structure ◽  
Least Square ◽  
Inversion Method ◽  
Practical Implementation ◽  
Proper Solution ◽  
Multiple Attenuation ◽  
Multiple Elimination ◽  
Water Bottom

Some deepwater multiple attenuation processing methods have been developed in the past with partial success. The success of surface multiple attenuation relies on good water bottom reflections for most deepwater marine situations. It brings the bigger ability to build an accurate water bottom multiple prediction model. Major challenges on 2D deepwater seismic data processing especially such a geologically complex structure of Seram Sea, West Papua – Indonesia are to attenuate surface related multiple and to preserve the primary data. Many multiple attenuation methods have been developed to remove surface multiple on these seismic data including most common least-squares, prediction-error filtering and more advanced Radon transform.Predictive Deconvolution and Surface Related Multiple Elimination (SRME) method appears to be a proper solution, especially in complex structure where the above methods fail to distinguish interval velocity difference between primaries and multiples. It does not require any subsurface info as long as source signature and surface reflectivity are provided. SRME method consists of 3 major steps: SRME regularization, multiple modeling and least-square adaptive subtraction. Near offset regularization is needed to fill the gaps on near offset due to unrecorded near traces during the acquisition process. Then, isolating primaries from multiples using forward modeling. Inversion method by subtraction of input data with multiple models to a more attenuated multiple seismic section.Results on real 2D deepwater seismic data show that SRME method as the proper solution should be considered as one of the practical implementation steps in geologically complex structure and to give more accurate seismic imaging for the interpretation.Keywords : multiple attenuation, 2D deepwater seismic, Radon transform, Surface Related Multiple Elimination (SRME). Banyak metode atenuasi pengulangan ganda dikembangkan pada pengolahan data seismik dengan tingkat keberhasilan yang rendah pada masa lalu. Keberhasilan dalam atenuasi pengulangan ganda permukaan salah satunya bergantung pada hasil gelombang pantul pada batas dasar laut dan permukaan pada hampir seluruh survei seismik laut. Hal tersebut menentukan keakuratan dalam membuat model prediksi pengulangan ganda dasar laut dan permukaan air. Tantangan utama dalam pemrosesan data seismik 2D laut dalam khususnya struktur geologi kompleks seperti Laut Seram, Papua Barat – Indonesia adalah pada kegiatan menekan pengulangan ganda permukaan sekaligus mempertahankan data primer. Beberapa metode yang dikembangkan untuk menghilangkan pengulangan ganda permukaan pada data seismik seperti least-square, filter prediksi kesalahan dan transformasi Radon.Dekonvolusi Prediktif dan Metode Surface Related Multiple Elimination (SRME) digunakan sebagai solusi yang baik pada struktur kompleks dimana metode-metode lain gagal untuk memisahkan perbedaan kecepatan interval data primer dan pengulangan ganda. Metode tersebut tidak membutuhkan informasi bawah permukaan selain parameter sumber dan reflektivitas permukaan. Metode SRME terdiri dari 3 tahapan utama : regularisasi SRME, pemodelan pengulangan ganda dan pengurangan adaktif least-square. Regularisasi near offset diperlukan untuk mengisi kekosongan pada near offset yang disebabkan oleh adanya sejumlah tras terdekat yang tidak terekam selama akuisisi. Pemodelan maju digunakan untuk memisahkan data primer dan pengulangan ganda kemudian inversi dengan pengurangan input data dengan model multiple.Hasil pada data seismik 2D laut dalam menunjukkan bahwa metode SRME layak diterapkan sebagai salah satu pengembangan metode atenuasi multiple permukaan serta untuk meningkatkan akurasi data seismik terutama untuk struktur geologi kompleks.Kata kunci : peredaman pengulangan ganda (multiple), seismik 2D laut dalam, transformasi Radon, Surface Related Multiple Attenuation (SRME).

scholarly journals Modeling in AUTOCAD for bachelors

2021 ◽  
pp. 25-28
Author(s):  
Л.В. Карпюк ◽  
Н.О. Давіденко
Keyword(s):  
3D Model ◽  
Three Dimensional ◽  
Model Space ◽  
Educational Process ◽  
Point Of View ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Three Dimensional Objects ◽  
Graphic Editor

The article discusses the methods of using the AutoCad graphic editor for creating three-dimensional objects. The possibilities of three-dimensional modeling in the AutoCad graphic editor for optimizing the educational process of bachelors of technical specialties are also considered. The article analyzes the best ways to create mechanical engineering drawings.The most developed software tool for the production of design documentation is AutoCAD - a universal graphic design system. Creating models of any complexity in space by using this graphic editor, the user will be able to see their relative position, estimate the distance between them. The model can be freely moved in space, viewing many options. The ability to control the point of view allows to conveniently select the view of the 3D model that is being developed. Zooming, panning in real time with the ability to freely rotate the camera around the model provide the ability to quickly view objects from any point of view. The article provides examples of choosing the most optimal option for creating a three-dimensional model. The traditional way to create a 3D model drawing is to make 2D views of the model. When creating a flat drawing, there is a possibility of error when making projections, since they are created independently from each other and consist of several images. It is rather difficult to represent an object in space from a flat drawing. At present, modern software graphic editors are aimed at creating three-dimensional models that allow to create realistic models and, on their basis, get two-dimensional projections. Graphic editor AutoCad allows to create three-dimensional objects based on standard commands, in the form of a cylinder, cone, box, torus, etc., when editing which you can get the desired shapes. After creating a three-dimensional model, the user can get its two-dimensional projections not only on the main planes, but also on any plane at will. The 3D modeling method allows you to create a complex drawing with any number of images based on a 3D model. There are ways to create 2D plane drawings from a 3D model and the ability to edit ready-made designs that can be inserted from model space into paper space. Editing takes place by changing the parameters of a 3D object in model space, and these changes are automatically reflected in paper space. This method allows us to use the tools to quickly create a system of 3-4 linked views for a 3D AutoCad model.

On airborne IP effects in standard AEM systems: tightening model space with data space

2019 ◽  
Vol 51 (1) ◽  
pp. 155-169 ◽  
Author(s):  
Andrea Viezzoli ◽  
Giovanni Manca
Keyword(s):  
Model Space ◽  
Data Space

MULTIPLE ELIMINATION USING WAVEFIELD TRANSFORMATIONS OFF THE COAST OF WESTERN AUSTRALIA

1997 ◽  
Vol 37 (1) ◽  
pp. 777
Author(s):  
M.G. Lamont ◽  
N.F. Uren
Keyword(s):  
Western Australia ◽  
Stationary Time Series ◽  
Velocity Inversion ◽  
Sea Floor ◽  
Event Prediction ◽  
Predictive Deconvolution ◽  
Constant Stretch ◽  
The Right ◽  
Multiple Elimination ◽  
Water Bottom

There are two principle reasons why water bottom multiples off the coast of Western Australia can be very difficult to attenuate:A strongly reflective sea floor (often caused by shallow carbonates) gives multiples large amplitudes compared with the primary events they overlay.A widely occurring velocity inversion, beneath the carbonates, causes multiples and primaries to have similar moveouts.A range of processes are commercially available to attenuate multiples, including FK Demultiple, Radon Demultiple, and Predictive Deconvolution. These methods can be very successful under the right conditions. Two dimensional autoconvolution methods, although very promising, still have drawbacks and are extremely computationally expensive.Two new wavefield transformations, Multiple MoveOut (MMO) and IsoStretch Radial Trace (ISR), have been developed to precondition data prior to the removal of surface related multiples by existing techniques. These form the basis of a new multiple attenuating procedure.MMO shifts the data so that the simple water bottom multiples become periodic with the primary event. Water bottom pegleg multiples become approximately periodic.ISR interpolates oblique traces of constant stretch which also approximately map constant angles of incidence on the sea floor. The water bottom primary and multiple events form stationary time series after ISR. They are then amenable to removal by Event Prediction (one dimensional autoconvolution) or Predictive Deconvolution.The results of the new procedure are demonstrated on field data from off-shore Western Australia. It is shown to be more effective at removing both simple and pegleg water bottom multiples than traditional techniques. Finally, it is not computer intensive and does not require velocity analysis prior to its application (besides estimate of water velocity).

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