Stochastic velocity modeling for structural uncertainty assessment during migration: application to salt body imaging

in: 2020 RING Meeting, ASGA

Abstract

Variations in the migration velocity model directly impact the position of the imaged reflections in the subsurface. Deterministically building an adequate velocity model - either by manual iterative updating and remigration or by solving a large inverse problem - does not allow, however, to investigate the structural uncertainties that stem from velocity uncertainty. To assess these uncertainties, we propose to use stochastic structural modeling to generate a set of velocity models and to analyze the set of seismic images that are obtained after remigration. We apply it to a 2D synthetic example of salt diapir. We use a recently published method to generate a large set of salt structural interpretations having varying geometries and topologies. These interpretations are then combined with an adaptive background sediment velocity model to obtain the set of migration velocity models. The corresponding perturbed seismic images are obtained by performing a reverse time migration (RTM). We analyze the structural variability of the image set using various measures. The first ones are the mean seismic image and its standard deviation. They provide both qualitative and quantitative information about the sensitivity of the seismic data to variations in the migration velocity model. Results show that stacking the different seismic images emphasizes the model parts where the seismic response is consistent from one realization to another, providing insights about the structures at depth. In order to also account for sediment velocity variations, we then investigate the use of post-stack seismic attributes to characterize the structural variations by the changes in the seismic image texture, which is more robust to vertical phase shifts.

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BibTeX Reference

@inproceedings{CLAUSOLLES_RM2020,
 abstract = { Variations in the migration velocity model directly impact the position of the imaged reflections in the subsurface. Deterministically building an adequate velocity model - either by manual iterative updating and remigration or by solving a large inverse problem - does not allow, however, to investigate the structural uncertainties that stem from velocity uncertainty. To assess these uncertainties, we propose to use stochastic structural modeling to generate a set of velocity models and to analyze the set of seismic images that are obtained after remigration. We apply it to a 2D synthetic example of salt diapir. We use a recently published method to generate a large set of salt structural interpretations having varying geometries and topologies. These interpretations are then combined with an adaptive background sediment velocity model to obtain the set of migration velocity models. The corresponding perturbed seismic images are obtained by performing a reverse time migration (RTM). We analyze the structural variability of the image set using various measures. The first ones are the mean seismic image and its standard deviation. They provide both qualitative and quantitative information about the sensitivity of the seismic data to variations in the migration velocity model. Results show that stacking the different seismic images emphasizes the model parts where the seismic response is consistent from one realization to another, providing insights about the structures at depth. In order to also account for sediment velocity variations, we then investigate the use of post-stack seismic attributes to characterize the structural variations by the changes in the seismic image texture, which is more robust to vertical phase shifts. },
 author = { Clausolles, Nicolas AND Collon, Pauline AND Caumon, Guillaume AND Irakarama, Modeste },
 booktitle = { 2020 RING Meeting },
 publisher = { ASGA },
 title = { Stochastic velocity modeling for structural uncertainty assessment during migration: application to salt body imaging },
 year = { 2020 }
}