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Multiples are echoes or reverberations of primary reflections. They are usually unwanted and hence removed from the seismic to allow for optimal processing, imaging and interpretation results. Their presence can mask or interfere with underlying primary reflections which can often be weaker in amplitude.
There are many different methods for multiple attenuation. Some target a specific class of multiple, often related to the water-layer in marine seismic. Others work on the basis of separating primary from multiple via transforms. Many form a model of the multiples which is then adaptively subtracted from the input. A variety of approaches are usually cascaded through an entire processing flow. Our experience and expertise allow us to maximize multiple attenuation whilst preserving primary energy. With so many methods and options available you can rely on our guidance, backed up by thorough testing, to obtain the best result for your particular project.
Surface related multiple elimination uses the recorded data to predict multiples produced by the downward reflection at the sea-surface, without the need for any information on the subsurface. In addition to direct water bottom multiples and water layer peg legs, direct multiples from deeper horizons are also addressed.
CGG’s true-azimuth 3D SRME provides highly effective multiple attenuation for any acquisition geometry. Our complementary data-driven and wave-equation modelling techniques respect the true offset and azimuth of the traces and can be applied directly to wide-azimuth data. The additional cross-line offsets which wide-azimuth data provide, allow the generation of a more accurate multiple model, which results in more effective multiple attenuation and better preservation of primaries.
Internal multiple attenuation is based on an extension of the ideas of SRME. Surface related multiple attenuation recognizes that surface multiples can be broken down into combinations of various primary events and that therefore they can be modelled by convolution of the pre-stack input data. In a similar fashion, internal multiples can be broken down into combinations of primary reflections, but with a missing primary leg.
The prediction of internal multiples that cross a nominal interface requires the convolution of data below the interface, plus a correlation of the data above the interface to remove the missing primary leg. This requires that all surface multiples have first been attenuated, along with any internal multiples generated above the interface. Input to the module is data that has already been processed to remove all source and receiver side surface multiples, plus an interface that separates the multiple generating events. CGG can offer several different techniques for Internal Multiple Attenuation.
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