1887
Volume 12 Number 5
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

As far as superficial seismic reflection events are concerned, the classical normal moveout (NMO) process, which leads to the construction of seismic zero‐offset (or stacked) sections, encounters several difficulties due to the large data aperture. One of these difficulties is that the hyperbolic approximation of the reflection traveltime in common midpoint (CMP) gathers is no longer valid when offset largely exceeds the target depth. Recently, Fomel and Kazinnik proposed a novel, multi‐parameter, non‐hyperbolic formula for the traveltime of such reflection events. This formula, which will be referred to here as the FK traveltime after the authors, is exact for reflectors whose shape can be described by a hyperbola, and shows promising accuracy for long offsets and/or curved reflectors. It also depends on the same set of parameters as the common reflection surface (CRS) traveltime. In this paper, we propose strategies for estimating these CRS parameters based on the FK traveltime using large aperture data. However, in contrast to traditional CRS processing, and due to their widespread use, only common midpoint (CMP) gathers will be considered for the parameter searches. We will begin with a sensitivity analysis, showing the impact of each parameter on the traveltime. Based on this analysis, we will propose a two‐step estimation strategy, that could lead to improved seismic images, especially for very shallow, high aperture events. We will then highlight, through synthetic examples and discussions, the strengths and limitations of this strategy.

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/content/journals/10.3997/1873-0604.2014019
2014-01-01
2024-04-25
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References

  1. Al‐ChalabiM.1973. Series approximation in velocity and traveltime computations. Geophysical Prospecting21, 783–795.
    [Google Scholar]
  2. BerkovitchA., BelferI. and LandaE.2008. Multifocusing as a method of improving subsurface imaging. The Leading Edge27, 250–256.
    [Google Scholar]
  3. BradfordJ.H.2002. Depth characterization of shallow aquifers with seismic reflection, part 1: The failure of NMO velocity analysis and quantitative error prediction. Geophysics67, 89–97.
    [Google Scholar]
  4. DuveneckE.2004. Velocity model estimation with data‐derived wavefront attributes. Geophysics69, 265–274.
    [Google Scholar]
  5. FomelS. and KazinnikR.2013. Non‐hyperbolic common reflection surface. Geophysical Prospecting61, 21–27.
    [Google Scholar]
  6. GurevichB. and LandaE.2002. Multifocusing imaging with controlled reflection‐point dispersal. Geophysics67, 1586–1592.
    [Google Scholar]
  7. HertweckT., SchleicherJ. and MannJ.2007. Data stacking beyond cmp. The Leading Edge26, 818–827.
    [Google Scholar]
  8. LandaE., KeydarS. and MoserT.J.2010. Multifocusing revisited – inhomogeneous media and curved interfaces. Geophysical Prospecting58, 925–938.
    [Google Scholar]
  9. MayneW.H.1962. Common reflection point horizontal data stacking techniques. Geophysics27, 927–938.
    [Google Scholar]
  10. OlivaP.C., TygelM., HubralP. and SchleicherJ.2003. A fourth‐order crs moveout for reflection and diffraction events. Journal of Seismic Exploration12, 197–219.
    [Google Scholar]
  11. PerroudH., HubralP. and HochtG.1999. Common‐reflection‐point stacking in laterally inhomogeneous media. Geophysical Prospecting47, 1–24.
    [Google Scholar]
  12. PerroudH. and TygelM.2004. Nonstretch NMO. Geophysics69, 599–607.
    [Google Scholar]
  13. TygelM. and SantosL.T.2007. Quadratic normal moveouts of symmetric reflections in elastic media: a quick tutorial. Studia Geophysica et Geodaetica51, 185–206.
    [Google Scholar]
  14. YilmazO.2000. Seismic Data Analysis: Processing, Inversion, and Interpretation of Seismic Data, Vol. 1. SEG.
    [Google Scholar]
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  • Article Type: Research Article

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