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).

Surface‐related multiple elimination on land seismic data—Strategies via case studies

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 719-734 ◽  
Author(s):  
Panos G. Kelamis ◽  
D. J. Verschuur
Keyword(s):  
Case Studies ◽  
Seismic Data ◽  
Input Data ◽  
Multiple Attenuation ◽  
Processing Strategies ◽  
Processing Step ◽  
Subsequent Elimination ◽  
Seismic Amplitudes ◽  
Multiple Elimination

Three processing strategies for the estimation and subsequent elimination of surface‐related multiple energy on land seismic data are presented. They can be applied in a prestack mode (to shot and common‐midpoint gathers) or in a poststack mode. The algorithm for the multiple attenuation is based on wave theoretical principles in which the data are used as a prediction operator. The estimated multiples are then adaptively subtracted from the input data to obtain primary‐only data. A processing step prior to applying multiple elimination is an important component of these methodologies, particularly in the prestack analysis. Its aim is to regularize the data, improve the S/N ratio, and balance the seismic amplitudes. This results in smooth prediction operators. The effectiveness of these schemes in suppressing multiples is demonstrated with a number of case studies involving processing land seismic data.

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

3D surface-related multiple elimination using parabolic sparse inversion

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. V145-V152 ◽  
Author(s):  
Ketil Hokstad ◽  
Roger Sollie
Keyword(s):  
Seismic Data ◽  
Alternative Formulation ◽  
Practical Implementation ◽  
3D Seismic ◽  
Systems Of Equations ◽  
Production Scale ◽  
Seismic Acquisition ◽  
Sparse Inversion ◽  
Multiple Elimination ◽  
3D Seismic Data

The basic theory of surface-related multiple elimination (SRME) can be formulated easily for 3D seismic data. However, because standard 3D seismic acquisition geometries violate the requirements of the method, the practical implementation for 3D seismic data is far from trivial. A major problem is to perform the crossline-summation step of 3D SRME, which becomes aliased because of the large separation between receiver cables and between source lines. A solution to this problem, based on hyperbolic sparse inversion, has been presented previously. This method is an alternative to extensive interpolation and extrapolation of data. The hyperbolic sparse inversion is formulated in the time domain and leads to few, but large, systems of equations. In this paper, we propose an alternative formulation using parabolic sparse inversion based on an efficient weighted minimum-norm solution that can be computed in the angular frequency domain. The main advantage of the new method is numerical efficiency because solving many small systems of equations often is faster than solving a few big ones. The method is demonstrated on 3D synthetic and real data with reflected and diffracted multiples. Numerical results show that the proposed method gives improved results compared to 2D SRME. For typical seismic acquisition geometries, the numerical cost running on 50 processors is [Formula: see text] per output trace. This makes production-scale processing of 3D seismic data feasible on current Linux clusters.

Multiple attenuation in complex geology with a pattern-based approach

Geophysics ◽  
2005 ◽  
Vol 70 (4) ◽  
pp. V97-V107 ◽  
Author(s):  
Antoine Guitton
Keyword(s):  
Seismic Data ◽  
Prediction Error ◽  
Input Data ◽  
Multiple Model ◽  
Ideal Case ◽  
Multiple Attenuation ◽  
Time Space ◽  
Multiple Prediction ◽  
Complex Geology ◽  
Space Variant

Primaries (signal) and multiples (noise) often exhibit different kinematics and amplitudes (i.e., patterns) in time and space. Multidimensional prediction-error filters (PEFs) approximate these patterns to separate noise and signal in a least-squares sense. These filters are time-space variant to handle the nonstationarity of multioffset seismic data. PEFs for the primaries and multiples are estimated from pattern models. In an ideal case where accurate pattern models of both noise and signal exist, the pattern-based method recovers the primaries while preserving their amplitudes. In the more general case, the pattern model of the multiples is obtained by using the data as prediction operators. The pattern model of the primaries is obtained by convolving the noise PEFs with the input data. In this situation, 3D PEFs are preferred to separate (in prestack data) the multiples properly and to preserve the primaries. Comparisons of the proposed method with adaptive subtraction with an [Formula: see text] norm demonstrate that for a given multiple model, the pattern-based approach generally attenuates the multiples and recovers the primaries better. In addition, tests on a 2D line from the Gulf of Mexico demonstrate that the proposed technique copes fairly well with modeling inadequacies present in the multiple prediction.

scholarly journals Efficient 2D multiple attenuation using SRME with curvelet-domain subtraction

2022 ◽  
Vol 43 (1) ◽  
Author(s):  
Szu-Ying Lai ◽  
Yunung Nina Lin ◽  
Ho-Han Hsu
Keyword(s):  
Finite Number ◽  
Least Squares ◽  
Seismic Data ◽  
Parameter Determination ◽  
Prediction Errors ◽  
Geological Condition ◽  
Multiple Model ◽  
Multiple Attenuation ◽  
Time Space ◽  
Multiple Elimination

AbstractSurface Related Multiple Elimination (SRME) usually suffers the issue of either over-attenuation that damages the primaries or under-attenuation that leaves strong residual multiples. This dilemma happens commonly when SRME is combined with least-squares subtraction. Here we introduce a more sophisticated subtraction approach that facilitates better separation of multiples from primaries. Curvelet-domain subtraction transforms both the data and the multiple model into the curvelet domain, where different frequency bands (scales) and event directions (orientations) are represented by a finite number of curvelet coefficients. When combined with adaptive subtraction in the time–space domain, this method can handle model prediction errors to achieve effective subtraction. We demonstrate this method on two 2D surveys from the TAiwan Integrated GEodynamics Research (TAIGER) project. With a careful parameter determination flow, our result shows curvelet-domain subtraction outperforms least-squares subtraction in all geological settings. We also present one failed case where specific geological condition hinders proper multiple subtraction. We further demonstrate that even for data acquired with short cables, curvelet-domain subtraction can still provide better results than least-squares subtraction. We recommend this method as the standard processing flow for multi-channel seismic data.

scholarly journals PENERAPAN METODE F-K DEMULTIPLE DALAM KASUS ATENUASI WATER-BOTTOM MULTIPLE

2016 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Subarsyah Subarsyah ◽  
Sahudin Sahudin
Keyword(s):  
Seismic Data ◽  
Final Section ◽  
Signal To Noise Ratio ◽  
Multiple Reflections ◽  
Seismic Section ◽  
Multiple Attenuation ◽  
Seismic Acquisition ◽  
Marine Seismic ◽  
Second Category ◽  
Water Bottom

Keberadaan water-bottom multiple merupakan hal yang tidak bisa dihindari dalam akuisisi data seismik laut, tentu saja hal ini akan menurunkan tingkat perbandingan sinyal dan noise. Beberapa metode atenuasi telah dikembangkan dalam menekan noise ini. Metode atenuasi multiple diklasifikasikan dalam tiga kelompok meliputi metode dekonvolusi yang mengidentifikasi multiple berdasarkan periodisitasnya, metode filtering yang memisahkan refleksi primer dan multiple dalam domain tertentu (F-K,Tau-P dan Radon domain) serta metode prediksi medan gelombang. Penerapan metode F-K demultiple yang masuk kategori kedua akan diterapkan terhadap data seismik PPPGL tahun 2010 di perairan Teluk Tomini. Atenuasi terhadap water-bottom multiple berhasil dilakukan akan tetapi pada beberapa bagian multiple masih terlihat dengan amplitude relatif lebih kecil. F-K demultiple tidak efektif dalam mereduksi multiple pada offset yang pendek dan multiple pada zona ini yang memberikan kontribusi terhadap keberadaan multiple pada penampang akhir. Kata kunci : F-K demultiple, multiple, atenuasi The presence of water-bottom multiple is unavoidable in marine seismic acquisition, of course, this will reduce signal to noise ratio. Several attenuation methods have been developed to suppress this noise. Multiple attenuation methods are classified into three groups first deconvolution method based on periodicity, second filtering method that separates the primary and multiple reflections in certain domains (FK, Tau-P and the Radon domain) ang the third method based on wavefield prediction. Application of F-K demultiple incoming second category will be applied to the seismic data in 2010 PPPGL at Tomini Gulf waters. Attenuation of the water-bottom multiple successful in reduce multiple but in some parts of seismic section multiple still visible with relatively smaller amplitude. FK demultiple not effective in reducing multiple at near offset and multiple in this zone contribute to the existence of multiple in final section. Key words : F-K demultiple, multiple, attenuation

Free-surface multiple attenuation for blended data

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. V227-V233
Author(s):  
Jitao Ma ◽  
Xiaohong Chen ◽  
Mrinal K. Sen ◽  
Yaru Xue
Keyword(s):  
Free Surface ◽  
Seismic Data ◽  
Synthetic Data ◽  
Primary Energy ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Crosstalk Noise ◽  
Multiple Attenuation ◽  
Blended Data ◽  
Value Decomposition

Blended data sets are now being acquired because of improved efficiency and reduction in cost compared with conventional seismic data acquisition. We have developed two methods for blended data free-surface multiple attenuation. The first method is based on an extension of surface-related multiple elimination (SRME) theory, in which free-surface multiples of the blended data can be predicted by a multidimensional convolution of the seismic data with the inverse of the blending operator. A least-squares inversion method is used, which indicates that crosstalk noise existed in the prediction result due to the approximate inversion. An adaptive subtraction procedure similar to that used in conventional SRME is then applied to obtain the blended primary — this can damage the energy of primaries. The second method is based on inverse data processing (IDP) theory adapted to blended data. We derived a formula similar to that used in conventional IDP, and we attenuated free-surface multiples by simple muting of the focused points in the inverse data space (IDS). The location of the focused points in the IDS for blended data, which can be calculated, is also related to the blending operator. We chose a singular value decomposition-based inversion algorithm to stabilize the inversion in the IDP method. The advantage of IDP compared with SRME is that, it does not have crosstalk noise and is able to better preserve the primary energy. The outputs of our methods are all blended primaries, and they can be further processed using blended data-based algorithms. Synthetic data examples show that the SRME and IDP algorithms for blended data are successful in attenuating free-surface multiples.

Effects of incomplete parameterization on full-wavefield viscoelastic seismic data for petrophysical reservoir properties

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. O9-O17 ◽  
Author(s):  
Upendra K. Tiwari ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Input Data ◽  
Elastic Model ◽  
Quality Factors ◽  
Noise Levels ◽  
Reservoir Properties ◽  
Estimated Parameters ◽  
Model Parameterization ◽  
The Earth ◽  
Incomplete Model

In inversion of viscoelastic full-wavefield seismic data, the choice of model parameterization influences the uncertainties and biases in estimating seismic and petrophysical parameters. Using an incomplete model parameterization results in solutions in which the effects of missing parameters are attributed erroneously to the parameters that are included. Incompleteness in this context means assuming the earth is elastic rather than viscoelastic. The inclusion of compressional and shear-wave quality factors [Formula: see text] and [Formula: see text] in inversion gives better estimates of reservoir properties than the less complete (elastic) model parameterization. [Formula: see text] and [Formula: see text] are sensitive primarily to fluid types and saturations. The parameter correlations are sensitive also to the model parameterization. As noise increases in the viscoelastic input data, the resolution of the estimated parameters decreases, but the parameter correlations are relatively unaffected by modest noise levels.

Coherent noise in marine seismic data

Geophysics ◽  
1983 ◽  
Vol 48 (7) ◽  
pp. 854-886 ◽  
Author(s):  
Ken Larner ◽  
Ron Chambers ◽  
Mai Yang ◽  
Walt Lynn ◽  
Willon Wai
Keyword(s):  
Seismic Data ◽  
Noise Suppression ◽  
Seismic Source ◽  
Coherent Noise ◽  
Critical Data ◽  
Predictive Deconvolution ◽  
Scattered Energy ◽  
Marine Seismic ◽  
The Many ◽  
Water Bottom

Despite significant advances in marine streamer design, seismic data are often plagued by coherent noise having approximately linear moveout across stacked sections. With an understanding of the characteristics that distinguish such noise from signal, we can decide which noise‐suppression techniques to use and at what stages to apply them in acquisition and processing. Three general mechanisms that might produce such noise patterns on stacked sections are examined: direct and trapped waves that propagate outward from the seismic source, cable motion caused by the tugging action of the boat and tail buoy, and scattered energy from irregularities in the water bottom and sub‐bottom. Depending upon the mechanism, entirely different noise patterns can be observed on shot profiles and common‐midpoint (CMP) gathers; these patterns can be diagnostic of the dominant mechanism in a given set of data. Field data from Canada and Alaska suggest that the dominant noise is from waves scattered within the shallow sub‐buttom. This type of noise, while not obvious on the shot records, is actually enhanced by CMP stacking. Moreover, this noise is not confined to marine data; it can be as strong as surface wave noise on stacked land seismic data as well. Of the many processing tools available, moveout filtering is best for suppressing the noise while preserving signal. Since the scattered noise does not exhibit a linear moveout pattern on CMP‐sorted gathers, moveout filtering must be applied either to traces within shot records and common‐receiver gathers or to stacked traces. Our data example demonstrates that although it is more costly, moveout filtering of the unstacked data is particularly effective because it conditions the data for the critical data‐dependent processing steps of predictive deconvolution and velocity analysis.

LONG-PERIOD SURFACE-RELATED MULTIPLE SUPPRESSION IN 2D MARINE SEISMIC DATA USING PREDICTIVE DECONVOLUTION AND COMBINATION OF SURFACE-RELATED MULTIPLE ELIMINATION AND PARABOLIC RADON FILTERING

2021 ◽  
Author(s):  
Pimpawee Sittipan ◽  
Pisanu Wongpornchai
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Petroleum Reservoirs ◽  
The United States ◽  
Multiple Reflections ◽  
Long Period ◽  
Predictive Deconvolution ◽  
Short Period ◽  
Marine Seismic ◽  
Multiple Elimination

Some of the important petroleum reservoirs accumulate beneath the seas and oceans. Marine seismic reflection method is the most efficient method and is widely used in the petroleum industry to map and interpret the potential of petroleum reservoirs. Multiple reflections are a particular problem in marine seismic reflection investigation, as they often obscure the target reflectors in seismic profiles. Multiple reflections can be categorized by considering the shallowest interface on which the bounces take place into two types: internal multiples and surface-related multiples. Besides, the multiples can be categorized on the interfaces where the bounces take place, a difference between long-period and short-period multiples can be considered. The long-period surface-related multiples on 2D marine seismic data of the East Coast of the United States-Southern Atlantic Margin were focused on this research. The seismic profile demonstrates the effectiveness of the results from predictive deconvolution and the combination of surface-related multiple eliminations (SRME) and parabolic Radon filtering. First, predictive deconvolution applied on conventional processing is the method of multiple suppression. The other, SRME is a model-based and data-driven surface-related multiple elimination method which does not need any assumptions. And the last, parabolic Radon filtering is a moveout-based method for residual multiple reflections based on velocity discrimination between primary and multiple reflections, thus velocity model and normal-moveout correction are required for this method. The predictive deconvolution is ineffective for long-period surface-related multiple removals. However, the combination of SRME and parabolic Radon filtering can attenuate almost long-period surface-related multiple reflections and provide a high-quality seismic images of marine seismic data.

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