Comparison of prestack stereotomography and NIP wave tomography for velocity model building: Instances from the Messinian evaporites

Abstract

Velocity-model determination during seismic data processing is crucial for any kind of depth imaging. We compared two approaches of grid tomography: prestack stereotomography and normal-incidence-point ͑NIP͒ wave tomography. Whereas NIP wave tomography is based on wavefield attributes obtained during the common reflection surface stack and thus on the underlying hyperbolic second-order traveltime approximation, prestack stereotomography describes traveltimes by local slopes ͑i.e., linearly͒ in the prestack data domain. To analyze the impact of the different traveltime approximations and the different input-data domains on velocity model building, we applied two implementations of these techniques to two profiles of a field marine data set from the Levante Basin, eastern Mediterranean. Because of the presence of a thick, tabular mobile unit of the Messinian evaporites, strong vertical and lateral velocity contrasts had been expected. The velocity models revealed the reconstruction of high-velocity contrasts by grid tomographic methods is limited because of the smooth description of the velocity distribution. The lateral resolution of velocities obtained from prestack stereotomography appears to be better than those from NIP wave tomography, which is related to the difference in the approximation of traveltimes, the determination of input data, and the description of the velocity distribution. Other differences are caused mainly by different implementations of the inversion schemes. Nevertheless, both algorithms provide suitable models for highquality depth imaging, whereas most of the reflections are fairly flat in CIGs.

Unsupervised event identification and tagging for diffraction focusing

“…Wavefront tomography (Duveneck 2004a) is an efficient and stable seismic inversion scheme, which uses zero-offset wavefront attributes for velocity model building in the depth domain. Initially, wavefront tomography was mainly applied using attributes measured for reflections (Duveneck 2004a;Dümmong et al 2008). Bauer et al (2017a) recently showed that diffractions can help to improve the resolution of the velocity models obtained with wavefront tomography and that their unique properties may contribute not only to further constrain the inversion, but also to estimate uncertainties (Bauer et al 2017b).…”

Utilizing diffractions in wavefront tomography

“…In previous studies (Duveneck, 2004;Meier, 2007;Dümmong et al, 2008), wavefront tomography has been applied mainly based on input data points picked on high-amplitude reflections. However, diffraction events possess properties, which make them an interesting target for wavefront tomography.…”

“…While previous applications had a strong emphasis on reflected events (Duveneck, 2004;Dümmong et al, 2008), we aim to take into account the diffractions in the data. Since diffractions are the seismic response of small-scale structures, they are crucial for high-resolution imaging of the subsurface (Klem-Musatov et al, 1994;Moser and Howard, 2008;Dell and Gajewski, 2011).…”

Towards a more robust input for stereotomography

“…Dümmong et al . (2008) presented a comparison between NIP wave tomography and stereotomography and concluded that stereotomography provides velocity models with a higher lateral resolution. They pointed out that the different lateral resolutions can be explained by the differing approximation of the traveltime curves.…”