Although considered as noise in the past, multiples are being increasingly seen as a tool for better illumination of the subsurface.

We explore the different strategies of exploiting the surface-related multiples specifically in the case of large acquisition gaps.

Surface-related multiples travel via different propagation paths compared to the primaries and hence, illuminate a wider area.

This property makes them valuable in cases of limited illumination.

Existing migration methods incorporate surface-related multiples in imaging by re-injecting the total measured data as a downgoing wavefield; this makes the method dependent on a dense receiver configuration and, therefore, sensitive to missing data.

Using 3D synthetic examples we will illustrate a ‘non-linear’ inversion approach in which all multiples are modeled from the original source field.

This makes the method less dependent on the receiver geometry, therefore, helping us in case of limited illumination.

We also discuss a ‘hybrid’ method on the same 3D model that utilises the benefits of both ‘linear’ and ‘non-linear’ methods.

The results indicate substantial reduction of migration holes compared to the ‘linear’ inversion methods, which is demonstrated on a 3D synthetic data with an obstruction zone from the platform.


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