3D surface related multiple elimination in the presence of a complex water bottom geometry — A case study from offshore Nigeria

2009 ◽  
Author(s):  
Stephen McHugo ◽  
Alex Cooke ◽  
Patrick Charron
Keyword(s):  
3D Surface ◽  
Multiple Elimination ◽  
Water Bottom

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).

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).

Shallow water demultiple in complex water bottom area, a case study from South China Sea

2018 ◽  
Author(s):  
Zheng Liu ◽  
Ming Zhu ◽  
Jiao He ◽  
Rong Li ◽  
Sherman Yang
Keyword(s):  
South China Sea ◽  
Shallow Water ◽  
South China ◽  
China Sea ◽  
Water Bottom

Modeling the impact of wide-azimuth acquisition on subsalt imaging

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. SM241-SM250 ◽  
Author(s):  
Bruce J. VerWest ◽  
Dechun Lin
Keyword(s):  
Simple Model ◽  
Input Data ◽  
Three Dimensional ◽  
Complex Model ◽  
3D Surface ◽  
Seismic Image ◽  
Ray Trace ◽  
Subsalt Imaging ◽  
Multiple Elimination ◽  
The Impact

Wide-azimuth towed streamer (WATS) acquisition improves the subsalt seismic image by suppressing multiples, improves the results of 3D surface-related-multiple elimination (SRME) processing, and provides more uniform seismic illumination of subsalt targets. A simple model shows that the additional suppression of multiples in the case of WATS acquisition is the result of a natural weighting of the traces going into the stack due to the areal nature of the acquisition. This simple model also shows that the extent of the additional multiple suppression is strongly dependent on the acquisition effort. A sparse acquisition effort will result in little additional multiple suppression. The use of 3D SRME processing is shown to be more accurate in predicting multiples, given input data with multiple azimuths, compared to making similar predictions from narrow-azimuth data. Three-dimensional SRME has the potential to reduce the residual multiples to the same extent as WATS acquisition with a higher acquisition effort. A complex model demonstrates that WATS acquisition does reduce the multiple-generated noise in subsalt images, but 3D SRME processing further reduces the residual multiple noise. The use of 3D SRME may reduce the multiples more than that achieved by increasing the cable half-aperture in the WATS acquisition effort. Finally, ray trace modeling is used to investigate the effect of WATS acquisition on subsurface illumination for subsalt imaging. We show that narrow-azimuth acquisition produces irregularities in subsalt illumination perpendicular to the acquisition direction which are a potential cause of migration noise. WATS acquisition results in higher and more uniform subsalt illumination and, hence, improves the subsalt image by reducing subsalt migration noise.

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