1887

Abstract

Summary

The Full Waveform Inversion (FWI) is based on the optimization of a physical model in order to fit the generated synthetic data with the empirical data collected by the receivers used in the field. At each iteration of the FWI computational procedure, the wave equation is solved and an update direction of the model is computed. This process requires a large amount of memory, a critical step in the performance of the method. The compression of the wave field data can effectively be performed with the curvelet transform, a modern multi-scale tool. Because of their dependence on orientation, curvelets are suitable to represent the anisotropy of wave patterns. Besides, it has been demonstrated that the solution operators of a wide range of wave equations are optimally sparse. In this work, we explore curvelets for data compression in the seismic FWI context. We compare the memory use of standard FWI processing with similar FWI processing using curvelets decomposition.

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/content/papers/10.3997/2214-4609.201900661
2019-06-03
2020-06-03
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References

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