Spectrum considers multiple attenuation to be an iterative process with two or three data passes to achieve optimum results. First pass demultiple typically is applied in the shot domain.
Surface Related Multiple Attenuation (SRMA)
Spectrum is a member of the Delft consortium, our Surface Related Multiple Attenuation (SRMA) program is based on the published work of Verschuur & Berkhout (1997).
In the SRME process the surface related multiples are estimated by convolving each trace on each input shot with the shot at the trace location and stacking in a common receiver sense. This yields the ‘shot record’ of the next Taylor term, which can be used in subsequent acoustic model building or adaptive subtraction. This multiple model is removed from the original data using Optimum Least-Squares filtering over whole ensemble. A Wiener-Levinson filter adjusts the amplitude and phase of the estimated multiples to match the original data. The filter which best subtracts all multiples is derived for each ensemble in the common shot or common channel domain. Matched multiple estimate is then subtracted from the original data via proprietary adaptive subtraction algorithm that ensures that predicted multiples are attenuated with minimal leakage of the primaries (the signal).
Resources: Verschuur, D.J., and Berkhout, A. J., 1997, Estimation of multiple scattering by iterative inversion, Part II: Practical aspects and examples, Geophysics, 62, 1596-1611
Examples of SRME application
In the x-t domain, multiples are only periodic at zero-offset. At the non-zero offsets the multiples are not periodic due to the effect of move-out. By transforming data into the linear tau-p domain multiples can be made periodic for all values of P and effectively attenuated with predictive deconvolution. This technique is particularly effective in shallow water areas where muting in the tau-p domain can assist with linear noise attenuation. However in some shallow water areas a single pass of shot based tau-P deconvolution may only attenuate some of the water bottom multiple. In these cases a second pass of tau-p deconvolution can be applied in the receiver domain – interpolation may be required to prevent aliasing in the common receiver domain.
2nd pass demultiple is typically high resolution parabolic radon. After normal moveout (NMO) correction, a shot or CMP gather can be thought of as being composed of many different parabolic or hyperbolic events. Each curve can be described by the zero-offset time and the residual moveout time at a reference offset (usually the far offset).Radon first decomposes an ensemble into its many parabolic or hyperbolic components in the Radon-transformed domain. To suppress some of the events, Radon mutes out part of the transformed domain according to the user specification. Finally, Radon inverts the muted transform back into the time-versus-offset domain, i.e. the original ensemble.
Multiple removal can be performed in one of 2 ways:-
(a) [PREFERRED BY SPECTRUM] Model the multiples i.e. mute the primaries in the transformed domain, invert transform back and subtract the multiples from the input data. This will only suppress the multiples, the random noise still remains. Therefore, the output ensemble appears more like the original.
(b) Model the primaries i.e. mute the multiples (noise) in the transformed domain. This will lead to the suppression of both multiples and random noise.
Example gathers prior to radon (prior to Pre-STM)
Example stack zoom prior to radon (prior to Pre-STM)