Data-driven retrieval of primary plane-wave responses

TL;DR

This paper introduces a data-driven, computationally efficient method for synthesizing primary plane-wave responses from reflection data, improving seismic imaging by reducing multiples in reverse time migration.

Contribution

It adapts a point source gather method to plane-wave datasets, enabling primary response synthesis directly from data for multiple-free seismic imaging.

Findings

Effective in producing multiple-free images from few plane-wave datasets

Demonstrates robustness across increasing complexity in numerical tests

Offers a computationally attractive alternative to traditional methods

Abstract

Seismic images provided by reverse time migration can be contaminated by artefacts associated with the migration of multiples. Multiples can corrupt seismic images, producing both false positives, i.e. by focusing energy at unphysical interfaces, and false negatives, i.e. by destructively interfering with primaries. Multiple prediction / primary synthesis methods are usually designed to operate on point source gathers, and can therefore be computationally demanding when large problems are considered. A computationally attractive scheme that operates on plane-wave datasets is derived by adapting a data-driven point source gathers method, based on convolutions and cross-correlations of the reflection response with itself, to include plane-wave concepts. As a result, the presented algorithm allows fully data-driven synthesis of primary reflections associated with plane-wave source responses. Once primary plane-wave responses are estimated, they are used for multiple-free imaging via plane-wave reverse time migration. Numerical tests of increasing complexity demonstrate the potential of the proposed algorithm to produce multiple-free images from only a small number of plane-wave datasets.