Abstract

Diffraction imaging aims to emphasize small-scale subsurface heterogeneities, such as faults, pinch-outs, fracture swarms, channels, etc. and can help seismic reservoir characterization. The key step in diffraction imaging workflows is based on the separation procedure suppressing higher energy reflections and emphasizing diffractions, after which diffractions can be imaged independently. Separation results often contain crosstalk between reflections and diffractions and are prone to noise. We have developed an inversion scheme to reduce the crosstalk and denoise diffractions. The scheme decomposes an input full wavefield into three components: reflections, diffractions, and noise. We construct the inverted forward modeling operator as the chain of three operators: Kirchhoff modeling, plane-wave destruction, and path-summation integral filter. Reflections and diffractions have the same modeling operator. Separation of the components is done by shaping regularization. We impose sparsity constraints to extract diffractions, enforce smoothing along dominant local event slopes to restore reflections, and suppress the crosstalk between the components by local signal-and-noise orthogonalization. Synthetic- and field-data examples confirm the effectiveness of the proposed method.

Highlights

  • Diffraction imaging aims to emphasize small-scale subsurface heterogeneities, such as faults, pinch-outs, fracture swarms, channels, and other small features and can play an important role in seismic reservoir characterization (Landa, 2012)

  • The reflection and diffraction separation procedure is a key step in diffraction imaging workflows (Harlan et al, 1984; Khaidukov et al, 2004; Fomel et al, 2007)

  • To restore reflections and diffractions simultaneously, we extend the least-squares migration workflow presented by Merzlikin and Fomel (2016), in which the inverted forward modeling operator is the chain of Kirchhoff modeling, plane-wave destruction (PWD), and path-summation integral filter operators

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Summary

Introduction

Diffraction imaging aims to emphasize small-scale subsurface heterogeneities, such as faults, pinch-outs, fracture swarms, channels, and other small features and can play an important role in seismic reservoir characterization (Landa, 2012). Methods based on optimal stacking of diffracted energy and suppression of reflections are described by Kanasewich and Phadke (1988), Landa and Keydar (1998), Berkovitch et al (2009), Dell and Gajewski (2011), Tsingas et al (2011), and Rad et al (2014). Wavefield-separation methods aim to decompose conventional full-wavefield seismic records into different components representing reflections and diffractions (Harlan et al, 1984; Papziner and Nick, 1998; Taner et al, 2006; Fomel et al, 2007; Reshef and Landa, 2009; Klokov and Fomel, 2012b; Tyiasning et al, 2016; Klokov et al, 2017; Merzlikin et al, 2017a, 2017b). Wavefield-separation methods aim to decompose conventional full-wavefield seismic records into different components representing reflections and diffractions (Harlan et al, 1984; Papziner and Nick, 1998; Taner et al, 2006; Fomel et al, 2007; Reshef and Landa, 2009; Klokov and Fomel, 2012b; Tyiasning et al, 2016; Klokov et al, 2017; Merzlikin et al, 2017a, 2017b). Kozlov et al (2004), Moser and Howard (2008), Koren and Ravve (2011), Klokov and Fomel (2013), and Popovici et al (2015) modify the Kirchhoff migration kernel to eliminate specular energy coming from the first Fresnel zone and image diffractions only

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