Velocity update for pre‐stack time migration

Lambaré, Gilles; Touré, J.P.; Moigne, José Le; Zimine, S.; Herrmann, P.; Carbonara, Stefano; Federici, F.

doi:10.1190/1.3064020

Cited by 4 publications

References 7 publications

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On the estimation of local slopes

et al. 2009

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Current time-processing algorithms often are based on one-parameter or multiparameter coherency analysis (semblance) schemes applied to the data. Such procedures, besides being computationally expensive, lead to significant uncertainties in the searched parameters. Conventional semblance methods can be avoided for a number of imaging tasks if local slopes can be extracted directly from prestack data—for example, by filtering schemes. Although the idea is not new, it has revived for various purposes, such as velocity analysis, [Formula: see text] imaging, migration to zero offset, and time migration. We propose a simple, straightforward correction to linear plane-wave destructors based on the observation that in addition to the local slope, its inverse can be extracted from the data in a fully analogous way. Combining the information of both extractions yields a simple yet effective correction to the local slopes. The naive application of linear plane-wave destructors with our correction produces high-quality results, even with a high noise level and interfering events.

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On the estimation of local slopes

et al. 2009

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Non‐linear tomography for time imaging

Lambaré

Deladerrière

Traonmilin

et al. 2009

SEG Technical Program Expanded Abstracts 2009

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Offset-continuation stacking: Theory and proof of concept

2016

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The offset-continuation operation (OCO) is a seismic configuration transform designed to simulate a seismic section, as if obtained with a certain source-receiver offset using the data measured with another offset. Based on this operation, we have introduced the OCO stack, which is a multiparameter stacking technique that transforms 2D/2.5D prestack multicoverage data into a stacked common-offset (CO) section. Similarly to common-midpoint and common-reflection-surface stacks, the OCO stack does not rely on an a priori velocity model but provided velocity information itself. Because OCO is dependent on the velocity model used in the process, the method can be combined with trial-stacking techniques for a set of models, thus allowing for the extraction of velocity information. The algorithm consists of data stacking along so-called OCO trajectories, which approximate the common-reflection-point trajectory, i.e., the position of a reflection event in the multicoverage data as a function of source-receiver offset in dependence on the medium velocity and the local event slope. These trajectories are the ray-theoretical solutions to the OCO image-wave equation, which describes the continuous transformation of a CO reflection event from one offset to another. Stacking along trial OCO trajectories for different values of average velocity and local event slope allows us to determine horizon-based optimal parameter pairs and a final stacked section at arbitrary offset. Synthetic examples demonstrate that the OCO stack works as predicted, almost completely removing random noise added to the data and successfully recovering the reflection events.

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Velocity update for pre‐stack time migration

Cited by 4 publications

References 7 publications

On the estimation of local slopes

On the estimation of local slopes

Non‐linear tomography for time imaging

Offset-continuation stacking: Theory and proof of concept

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