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KAUST-IAMCS Workshop on Modeling and Simulation of Wave Propagation and Applications

Eric Verschuur, Delft University of Technology (The Netherlands)
Full Waveform Inversion Using Different Forward Modeling Methods and Parameterizations


Nowadays, in seismic processing and imaging, the so-called full waveform inversion (FWI) methods have become very popular. Full waveform inversion means using a forward modeling engine to explain every sample of the seismic measurements via a large-scale, non-linear parametric inversion process. However, depending on the desired output, being the values of the parameters that optimally describe the measurements, different flavors of FWI, and their associated forward modeling engines, can be defined. In this presentation, three versions of FWI will be discussed, using quite different associated modeling methods and parameterizations. The classical FWI method solves the full 2-way wave equation, usually via a differential equation or integral representation. The parameters are the actual elastic parameters of a gridded representation of the subsurface. A second FWI method explains the seismic data in terms of propagation and reflection, the output being a high-resolution image. The third, more implicit approach, explains the measurements in terms of primary impulse responses and their associated multiples. The estimated primary reflection responses are the output of this process. In all cases, the inversion is carried out using an iterative solver in order to find the optimum parameters.