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Collaborating Authors
Thi\ is the only way of evaluating the an effective suppression of dipping noise.
Multichannel seismic MCS images are often contaminated with in and outofplane scattering from the sea floor. This problem is especially acute in the midocean ridge environment where seafloor roughness is pronounced. Energy shed from the unsedimented basaltic sea floor can obscure primary reflections such as Moho, and scattering off of elongated seafloor features like abyssal hills and fault scarps can produce linear events in the seismic data that could be misinterpreted as subsurface reflections. Moreover, stacking at normal subsurface velocities may enhance these waterborne events, whose stacking velocity depends on azimuth and generally increases with time, making them indistinguishable from subsurface arrivals. To suppress scattered energy in deep water settings, we propose a processing scheme that invokes the application of dip moveout DMO to deliberately increase the differential moveout between seafloorscattered and subsurface events, thereby facilitating the removal of unwanted energy in the stacked section. After application of DMO, all seafloor scatterers stack at the water velocity, while subsurface reflections like Moho still stack at their original velocity. The application of DMO in this manner is contrary to the intended use that reduces the differential moveout between dipping events and allows a single stacking velocity to be used. Unlike previous approaches to suppress scattered energy, dip filtering is applied in the commonmidpoint CMP domain after DMO. Moveover, our DMObased approach suppresses outofplane scattering, and therefore is not limited to removal of inplane scattering as is the case with shot and receiver dip filtering techniques. The success of our DMObased suppression scheme is limited to deep water a few kilometers of water depth for conventional offsets, where the traveltime moveout of energy scattered from the sea floor has a hyperbolic moveout with a stacking velocity that depends on the cosine of the scatterer steering angle in a manner analogous to how the moveout of a dipping reflector depends on the dip angle. The application of DMObased suppression to synthetics and MCS data collected along the southern East Pacific Rise demonstrates the effectiveness of our approach. Cleaner images of primary reflectors such as Moho are produced, even though present shot coverage along the East Pacific Rise is unduly sparse, resulting in a limited effective spatial bandwidth.
- Geophysics > Seismic Surveying > Seismic Processing > Seismic Migration (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)
Unfortunately program\ derived from this equation cannot be u\ed for migration in two pabsc . The purpose of this paper is to drhcribe an extension ofthe More generally.
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 noisesuppression 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 subbottom. Depending upon the mechanism, entirely different noise patterns can be observed on shot profiles and commonmidpoint 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 subbuttom. 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 CMPsorted gathers, moveout filtering must be applied either to traces within shot records and commonreceiver 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 datadependent processing steps of predictive deconvolution and velocity analysis.
5. Diffraction Imaging (Seismic Diffraction)
Hubral, P., Landa, E., Shtivelman, V., Gelchinsky, B., Kanasewich, Ernest R., Phadke, Suhas M., Keydar, Shemer, Zavalishin, B. R., Khaidukov, V., Moser, T. J., Grasmueck, Mark, Weger, Ralf, Horstmeyer, Heinrich, Bansal, Reeshidev, Imhof, Matthias G., Sava, Paul C., Biondi, Biondo, Etgen, John, Fomel, Sergey, Taner, M. Turhan, Howard, C. B., Reshef, Moshe, Berkovitch, Alex, Belfer, Igor, Hassin, Yehuda, Bachrach, Ran
Chapter 5, the final section in this volume, focuses on the separation and imaging of diffractions, starting with pioneering work in the 1970s and proceeding to the current state. The separation process removes the reflection data and retains the lower-energy diffraction data. The imaging process focuses the diffraction energy at the surface locations from which the diffractions originated. Synthetic and real data examples are included. The objective of diffraction imaging is to locate the discontinuities in the subsurface that give rise to diffraction energy. Papers in this section detail a progression of different approaches to this problem.
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