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Abstract:

Seismic inversion is very sensitive to the presence of noise. In an inversion scheme, noise is any event in the data not predicted by the forward modeling because of either inaccurate physics or inadequate model parameterization. Therefore, noise exists in the residual space and, if coherent, slows convergence to an acceptable result, or in the worst case, dominates the whole process, inhibiting the efficacy of inversion. The ideal solution is to incorporate the modeling of the noise into the forward modeling. A more practical approach is to make the data agree with the physical assumptions of the inversion scheme. In this context, noise attenuation is a pre-processing step before inversion. Here, we illustrate the problem by applying one-way wave-equation inversion to a portion of the well known Sigsbee2b data. In the present example, noise takes the form of multiples, not modeled by the one-way wave-equation. After characterizing the noise in the migrated data, we use a dip filter to estimate it and a non-stationary adaptive filter technique to subtract it from the migrated data.




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Next: Introduction Up: Reproducible Documents

2009-04-13