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Gaussian Beam Summation Migration of Deep Reflection Seismic Data: Numerical Examples | IEEE Journals & Magazine | IEEE Xplore

Gaussian Beam Summation Migration of Deep Reflection Seismic Data: Numerical Examples


Abstract:

The deep reflection seismic technique is essential to detect the basement of petroliferous basins and the fine structure of the lithosphere. Traditional stacking or time ...Show More

Abstract:

The deep reflection seismic technique is essential to detect the basement of petroliferous basins and the fine structure of the lithosphere. Traditional stacking or time migration is usually adopted for imaging deep reflection seismic data, but the accuracy is too limited to acquire precise imaging profiles. The development of an effective prestack depth migration method for deep reflection seismic data is an urgent requirement in the field of lithosphere structure detection. The Gaussian beam summation (GBS) migration requires no local slant stacking or phase approximation. It has higher imaging precision and better flexibility and applicability to the acquisition system, which can be well applied to imaging long-array and large-trace-interval deep reflection seismic data. In this letter, the GBS migration is extended into depth-domain imaging of deep-reflection seismic data. Firstly, the basic principles of GBS migration are reviewed. Then, the validity of the method is verified by a migration test on a simple crustal-scale model. Finally, according to the crust-mantle structure of typical areas, a crustal model of western Sichuan and eastern Tibet and a classical collision model are established for migration experiments, and accurate deep-domain images are obtained. We mainly conducted numerical tests for the GBS migration of deep reflection seismic data in this letter. It was verified through imaging studies by the typical crust-mantle structure model that the proposed method was a prestack depth migration method suitable for the precise imaging of deep reflection seismic data, which provided a numerical basis for its subsequent imaging application in field data.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 19)
Article Sequence Number: 8030805
Date of Publication: 23 November 2022

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