We have evaluated an explicit relationship between the representations of internal multiples by source-receiver interferometry and an inverse-scattering series. This provides a new insight into the interaction of different terms in each of these internal multiple prediction equations and explains why amplitudes of estimated multiples are typically incorrect. A downside of the existing representations is that their computational cost is extremely high, which can be a precluding factor especially in 3D applications. Using our insight from source-receiver interferometry, we have developed an alternative, computationally more efficient way to predict internal multiples. The new formula is based on crosscorrelation and convolution: two operations that are computationally cheap and routinely used in interferometric methods. We have compared the results of the standard and the alternative formulas qualitatively in terms of the constructed wavefields and quantitatively in terms of the computational cost using examples from a synthetic data set.

/pdf/relating-source-receiver-interferometry-to-an-inverse-7t2149juxo.pdf

Relating source-receiver interferometry to an inverse-scattering series to derive a new method to estimate internal multiples

This paper focuses on the attenuation of Water-Layer-Related Multiples (WLRMs or peg-leg multiples) which reflect at least once between the water bottom and the water surface. WLRMs are often the most dominant multiples in shallow-water seismic data. We propose a Model-based Water-layer Demultiple (MWD) algorithm to calculate the Green's functions of the Water-Layer Primary Reflections (WLPRs: Green's functions convolved with source signature) based on the known seabed and water-layer velocity model and then convolve them with the recorded data to predict the WLRMs. Combined with adaptive subtraction, MWD can effectively attenuate WLRMs. We apply MWD to field data from the Hibernia oilfield area which has a water depth of 70-90 m. The results show that while Surface-Related Multiple Elimination (SRME) by itself has limited success, MWD is effective in attacking WLRMs. Once the WLRMs have been removed by MWD, successive SRME can then be applied to predict and eliminate other types of surface-related multiples (SRMs).�The combination of MWD and SRME is demonstrated as an effective multiple attenuation package for shallow-water data and results in fewer residual multiples and better preserved pri- maries over tau-p gapped deconvolution. This, in turn, contributes to a more realistic velocity model and higher-quality images. from the auto-correlation, to predict WLRMs. DWD pre- dicts WLRMs with correct amplitudes. However, when the water-bottom is complex (and thus multi-arrivals of WLPRs present) the water-layer model derived from the time-domain

A model-based water-layer demultiple algorithm

Imaging of first-order surface-related multiples by reverse-time migration

An adaptive multiple subtraction step is necessary for almost all methods that predict seismic multiple reflected waves. We aim at giving a better understanding of matching filters based on lq-norms and on statistical independence. We found that the formulation of all of these techniques can be gathered in a mutual framework by introducing a space-time operator, called the primary enhancer, acting on the estimated primaries. The differences between the considered matching filters become more intuitive because this operator behaves as a simple amplitude compressor. In this perspective, all the methods tend to uncorrelate the predicted multiples and the enhanced estimated primaries. The study of these matching-filter methods can be narrowed to the study of the primary enhancer operator because it is the only difference. Moreover, we have emphasized the role of using adjacent traces or windowing approaches in terms of statistics, and we show that an adequate windowing strategy may overbear the choice...

Adaptive multiple subtraction: Unification and comparison of matching filters based on the ℓq-norm and statistical independence

The Arctic Ocean is an area of increasing interest for research. Variations in the sensitive polar ecosystem influence the environment of the global Earth system and climate change. Therefore, reviews of modern Arctic Ocean system thereby provide the basis to interpret the Arctic Ocean evolution through its past. However, the evolution of the Arctic Ocean, especially the Amerasian Basin, remains controversial and multiple oceanic rift models still exist. During the ARK-XXIII/3 expedition in the summer of 2008, the Alfred Wegener Institute could acquire the first seismic data set - consisting of seismic reflection lines as well as wide-angle reflection and refraction data - in the northern Chukchi region and on the southern Mendeleev Ridge. In addition, further data sets (logging information, additional seismic lines, gravity data) were available and used within this thesis. Summarising the results, we could date six sediment horizons in the research area, using the age control from the exploration wells. Furthermore, with the interpretation of the tectonic elements the ages of evolution of the northern Chukchi region and the southern Mendeleev Ridge were derived. In addition, a complex 3D gravity model of the research area was calculated. Hence, two tectonic models for the origin of the Chukchi Borderland and the Mendeleev Ridge were developed. Moreover, two already existing oceanic rift models for the opening of the Amerasian Basin were modified based on our results. On the other hand, we used prograding sediment horizons on the Chukchi Shelf to reconstruct the first relative sea level curve for the Chukchi region, beginning in the Late Eocene. This curve led to conclusions about the existence of gateways between the Arctic Ocean and the other global oceans. Therefore, we suggest an isolated Arctic Ocean from the Eocene/Oligocene boundary to the Early Miocene, and a higher relative sea level in the isolated Arctic basin than in the global oceans during this time.

The Chukchi region: Arctic ocean : tectonic and sedimentary evolution

Ebook: Seismic Multiple Removal Techniques: Past, present and future. Revised Edition

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Ebook: Seismic Multiple Removal Techniques: Past, present and future. Revised Edition