Çok kanallı sismik verilerde tekrarlı yansımaların bastırılması
Multiple elimination in the multichannel marine seismic reflection data
- Tez No: 556602
- Danışmanlar: DOÇ. DR. NESLİHAN OCAKOĞLU GÖKAŞAN
- Tez Türü: Yüksek Lisans
- Konular: Jeofizik Mühendisliği, Geophysics Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2019
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Jeofizik Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Jeofizik Mühendisliği Bilim Dalı
- Sayfa Sayısı: 159
Özet
Bu çalışmada çok kanallı sismik yansıma verilerinin rutin veri-işlem aşamaları ile işlenmesi sırasında verilerde önemli bir gürültü olarak karşımıza çıkan tekrarlı yansımaların yığma öncesi dekonvolüsyon yöntemi ile verilerden uzaklaştırılması konusu işlenmiştir. Özellikle deniz sismiği yansıma verilerinde deniz tabanı ve hemen onun altındaki sedimanlardan gelen kuvvetli tekrarlılar atış gruplarında birincil yansımaları örtmektedir. Bu durum çalışma kapsamında Karadeniz güney şelfinde Cide açıklarından seçilen bir çok kanallı sismik yansıma profilinde gözlenmiştir. Örnek veri seti üzerinde su kolonu derinlik değişimi ve yeraltının sismik stratigrafik ve yapısal unsurlarına bağlı olarak söz konusu tekrarlı yansımalar; derin, orta derin ve sığ alanlar olmak üzere üç bölüme ayrılarak araştırılmıştır. Seçilen dekonvolüsyon yöntemlerinde, Wiener ters süzgeçlerinin kaynak dalgacığını sıkıştırması ve tekrarlı yansımaları bastırması özelliğinden yararlanılarak, dekonvolüsyonun tekrarlı yansımalar üzerindeki etkisi, farklı dekonvolüsyon parametreleri ile incelenmiştir. Dekonvolüsyon öncesi çok kanallı sismik yansıma verilerine bazı ön veri işlem aşamaları uygulanmış, bu aşamalarda atış gruplarından bozuk kanallar ve istenmeyen gürültüler atılmıştır. Ön veri-işlem aşamalarından sonra örnek sismik hattın, derin, orta derin ve sığ kısımlarında sırasıyla iğnecikleştirme ve ön kestirim dekonvolüsyon uygulamaları yapılmıştır. Tekrarlı yansımaların ne ölçüde bastırıldığı Frekans-genlik grafiklerinde karşılaştırmalı olarak incelenmiştir. Her üç uygulama alanı için sırasıyla iğnecikleştirme ve önkestirim dekonvonlüsyon uygulamaları için en uygun parametreler denemeler ile seçilmiştir. Farklı uygulamalar ve sonuçları sismik profil üzerindeki üç bölge için grafikler ile gösterilmiştir. Daha sonra en iyi yanıtı veren ters evrişim yöntemi ve ona ait parametreler ile tüm sismik kesit, yığma öncesi dekonvolüsyon işlemine tabi tutulmuştur. İki yöntem içerisinde ön kestirim dekonvolüsyon yönteminin daha başarılı sonuçlar ürettiği görülmüştür. Özellikle profil boyunca derin ve orta derin alanlarda tekrarlı yansımalar daha başarılı bir şekilde bastırılmıştır.
Özet (Çeviri)
In this study, it has been discussed to suppress the multiple reflections from the data by pre-stacking deconvolution method. Multiple reflections are an important noise in multichannel seismic reflection data. Especially, in marine seismic reflection data primary reflections are covered by strong multiple reflections in shot gathers from the seabed and sediments below it. In this study, spiking and predictive deconvolution methods were applied to a multi-channel seismic reflection profile acquired offshore Cide in the southern shelf of the Black Sea. The multiple reflections were investigated by dividing the data set to three parts as deep (first part), medium-deep (second part) and shallow (third part) areas according to the variation of the water column thickness and the seismic stratigraphic and structural features of the subsurface. By using the Wiener reverse filters compressing the source wavelet and suppressing multiple reflections, the effect of deconvolution on the multiple reflections in the selected deconvolution methods were investigated with different deconvolution parameters. Prior to deconvolution, several pre-processing steps such as trace editing, muting and notch filtering were applied to the multichannel seismic reflection data. After these steps, deconvolution applications were performed in all three parts of the sample seismic line. The extent of which multiple reflections were suppressed was examined comparatively with frequency-amplitude analysis. For each of the three parts of application, the most appropriate parameters for spiking and predictive deconvolution applications were chosen by experiments. Different applications and their results are shown by graphs for the three parts on the seismic profile. Afterwards, the whole seismic section was applied to the pre-stack deconvolution process with the best deconvolution parameters. Multichannel seismic reflection data has been applied to some pre-processing steps to eliminate noises before the deconvolution process. First of all, raw shot gathers in SEGY format have been transferred to 'ECHOS' software's internal format. Then, to improve the signal-to-noise ratio of the data, noisy traces from each shot gathers were detected and killed. In the next step, shot and receiver geometry is entered to the program. Then the datum correction was made for the source and receivers drawn from a certain depth. In this correction, the position of the source and receivers were brought on the sea surface level by adding the time difference was to each seismic trace in milliseconds. In the next step, direct arrivals and refractions in the shot gathers were muted from the data. Before deconvolution, the data must be free of noise as much as possible. For this purpose, a notch filter was applied to the shot data. In the spiking deconvolution, the application gate was chosen as 0-7 s. For the selection of design gate, five different design gates were made in the first part of the seismic line. The operator length as 400 ms is fixed and chosen as long as possible. Two gate design was chosen as the most appropriate design gate for the application area. In the other parts of the seismic line 0-7 s design gates were used due to the complexity of the primary reflections and multiple reflections which is not separated from each other as necessary. After the selection of the design and application gates, applications were made for the most suitable length for the deconvolution operator. Within this scope, 20, 40, 60, 80, 100, 200, 400, 600 ms operator lengths were selected for all three parts and applied to them. The results are compared in groups of three parameters and provided with the enlarged images of single channel sections. The section with the best operator length was enclosed with a frame and indicated by a star symbol. For the first part of the seismic line, it is seen that the resolution in the data is at the best for 400 ms operator length and it provides a more balanced increase in the amplitude of the signal and slightly better in the appearance. For the second part, 200 ms operator length was chosen as it provides the minimum noise and the best resolution. For the third part, where the strong multiple reflections are present, 100 ms operator length gives the best frequency band and increases the amplitudes. As a result of the experiments performed for three different parts, the most ideal spiking deconvolution parameters are applied to whole seismic line data. For the whole seismic line, the most suitable operator length was chosen 200 ms. The design and application gates are selected from 0 to 7 s. Compared to the raw single channel seismic line, the frequency band has expanded considerably and the amplitudes have increased significantly. It can be said that multiple reflections have been suppressed and the resolution was enhanced as much as possible. In the predictive deconvolution application with short gap lengths, the application and design gates were chosen as 0-7 s. The gap has been changed by keeping the best operator length obtained from the spiking deconvolution application. This operator length was fixed for each part of seismic section. 6 ms, 18 ms and 30 ms gap distances are the first, second and third zero crossing times of the first transient part of autocorrelation function of the seismogram respectively. This represents the autocorrelation of the source wavelet. Deconvolution results are compared in groups of three parts with their frequency amplitude analysis and enhanced images. The best prediction gaps were enclosed with a frame and indicated by a star symbol. For the first part of the seismic line, the best gap distance was chosen as 10 ms providing better resolution and more balanced increase in the amplitude of the signal's frequency band. For the second part, the best gap distance was also chosen as 10 ms. For the third part, the prediction gap also chosen as 10 ms which increases the frequency spectrum of the data and the resolution. However, this process added noise to the data. The amount of noise decreases as the prediction gap increases. But this time however, the efficiency of the deconvolution process decreases. Considering all this, it can be said that the 10 ms gap value is the best for the third part. For the whole seismic line, as a result of the applications performed for three different parts, the most ideal predictive deconvolution parameters were selected. According to this, the most suitable design and application windows were taken between 0 - 7s. The operator length was selected as 400 ms. The most effective gap distance was chosen as 10 ms. After application, it can be seen that signal to noise ratio increased and frequency band widened and amplitudes were increased compared to the raw section. It can be said that, multiple reflections have been mostly suppressed. In the prediction deconvolution applications with long gap lengths, the application and design gates were chosen as 0-7 s. As a second approach to the suppressing of the multiple reflections, long prediction gaps and operator lengths were used for the deconvolution process and results were discussed. The prediction distance for each of the three parts was chosen close to the arrival time of the multiple reflections in the autocorrelation functions of the shot gathers. The operator lengths were selected close to the time lengths of the multiple reflections. Deconvolution results were compared with raw data for all application sections, including frequency amplitude analysis. It can be said that some of the primary reflections particularly at the shallow areas were lost after the application. On the other hand, it can be said that the long prediction distances worked well and suppressed the multiple reflections mostly. If the two methods are compared, it can be said that predictive deconvolution is more effective than the spiking deconvolution and produced more successful results. Also it can be said that the predictive deconvolution is more flexible having more parameters than the spiking deconvolution. As a result, multiple reflections have been partially suppressed, especially in deep and medium deep areas.
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