Seismic full-waveform inversion using a compressed simultaneous sources and receivers scheme

Abstract

We apply the source-receiver compression approach for reducing the computational time and memory usage of the seismic (acoustic) full-waveform inversions. By detecting and quantifying the extent of redundancy in the data, we assemble a reduced set of simultaneous sources and receivers that are weighted sums of the physical sources and receivers employed in the survey. Because the number of these simultaneous sources and receivers can be significantly less than those of the physical sources and receivers, the computational time and memory usage of an inversion method can be tremendously reduced. The scheme is based on decomposing the data into their principal components using a singular-value decomposition approach and the data reduction is done through the elimination of the small eigenvalues. Consequently this will suppress the effect of noise in the data. Moreover, taking advantage of the redundancy in the data, this compression scheme effectively stacks the redundant data resulting in an increased signal-to-noise ratio. We present inversion results for the Marmousi model for surface measurements. We show that this approach has the potential of significantly reducing both computational time and memory usage of the Gauss-Newton method by 1-2 orders of magnitude.