Shallow water multiple prediction and attenuation, case study on data from the Arabian Gulf

Alai, Riaz; Verschuur, D.J.; Drummond, Jock; Morris, Stan; Haughey, Gerard

doi:10.1190/1.1817154

Cited by 13 publications

(7 citation statements)

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“…In shallow water depths, one of the main challenging issues is the attenuation of the seabed multiples, guided waves, peg-legs and/or out-of-plane events (Yilmaz, 2001). Many authors have proposed different methods to attenuate these undesired signals based on CMP-stack, separating different moveout, and predictability, or, on separating primaries and multiples applied in x-t and tau-p domains (i.e., Verschuur et al, 1992;Alái et al, 2002;Hung et al, 2010). Alternatively, in the case of complex geology, another valid method is the application of seismic migration algorithms, which consider a velocity model and the angle of incidence at the reflectors (i.e., Yilmaz, 2001).…”

Section: Introductionmentioning

confidence: 99%

Integrated Geophysical Analyses of Shallow-Water Seismic Imaging With Scholte Wave Inversion: The Northern Adriatic Sea Case Study

et al. 2020

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The integrated analysis using different seismic wave types in a record is a very efficient approach for a comprehensive characterization of marine sediments, especially in shallow water conditions. The proposed integrated method to analyze seismic data in post-critical conditions consists of: 1) the inversion of Scholte waves to obtain a reliable Vs distribution of the near seafloor; 2) pre-processing of seismic data; 3) construction of the P-wave velocity field by using all available information, including available well data; and 4) the application of the wave equation datuming and post-processing, such as pre-stack time migration. We demonstrate how this approach could be successfully applied on seismic datasets characterized by post-critical conditions and the occurrence of the Scholte waves, which may be exploited to provide fundamental information instead of being only an unwanted effect. The integrated analysis of seismic events can thus help, together with data processing, by providing better seismic imaging, which is a priority for a reliable seismostratigraphic interpretation.

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Section: Introductionmentioning

confidence: 99%

Integrated Geophysical Analyses of Shallow-Water Seismic Imaging With Scholte Wave Inversion: The Northern Adriatic Sea Case Study

et al. 2020

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“…In shallow water, short-period multiples have been usually attenuated by using predictive deconvolution in the x-t or tau-p domains (i.e., [5,6]). However, this approach attenuates all events with the period close to the water layer, including the primaries and interbed multiples.…”

Section: Introductionmentioning

confidence: 99%

Wave Equation Datuming Applied to Seismic Data in Shallow Water Environment and Post-Critical Water Bottom Reflection

2017

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Abstract:Coastal areas are generally characterized by human manufacturing; thus, seismic data analysis is necessary to characterize the properties of the subsoil, the main purpose of which is to clarify risk situations. In the case of very shallow water environments, seismic multiple attenuation becomes a challenge when the reflection of the seafloor is post-critical, so it is not recorded because of the acquisition parameters. We propose an approach to attenuate the multiples by using wave equation datuming that does not require the detection of seafloor reflection and avoids the seafloor reflection prediction and related approximations in the post-critical conditions. Moreover, this approach allows for the enhancement of higher frequencies, and, consequently, an increase in resolution, demonstrating that it is a powerful tool to attenuate multiples and reverberations, especially where other approaches are found to be inefficient. An example of the application of seismic data acquired in the continental shelf of South Chile is reported.

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“…Predictive deconvolution methods (Alái et al, 2002) have been proposed, in shallow-water situations to first attenuate the short-period multiples followed by a conventional SRME to cope with the longer-period multiples. Predictive deconvolution relaxes the dependency on WLPRs.…”

Section: Introductionmentioning

confidence: 99%

A model-based water-layer demultiple algorithm

Wang¹,

Jin²,

Yang³

et al. 2014

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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 primaries over tau-p gapped deconvolution. This, in turn, contributes to a more realistic velocity model and higher-quality images.

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Shallow water multiple prediction and attenuation, case study on data from the Arabian Gulf

Cited by 13 publications

References 0 publications

Integrated Geophysical Analyses of Shallow-Water Seismic Imaging With Scholte Wave Inversion: The Northern Adriatic Sea Case Study

Integrated Geophysical Analyses of Shallow-Water Seismic Imaging With Scholte Wave Inversion: The Northern Adriatic Sea Case Study

Wave Equation Datuming Applied to Seismic Data in Shallow Water Environment and Post-Critical Water Bottom Reflection

A model-based water-layer demultiple algorithm

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