Full waveform inversion (FWI) produces subsurface images by minimizing the misfit between observed data and calculated model using iterative local optimization algorithms like conjugate gradient method. This approach requires a starting model which should appear in the neighborhood of the global solution of the FWI problem to ensure that the modeled waveforms are less than half a period away from the recorded data. Usually, reflection traveltime tomography is used to create a long-wavelength background velocity model for starting FWI iterations. In this paper we suggest an alternative method to develop the starting model for FWI by using a reflectivity inversion technique. A depth section of migrated data is used to extract the reflection coefficients and impedance section, then the impedance section is converted to velocity model by considering a known density model. The reflectivity inversion can detect subsurface geological structures very well and on the other hand, an approximate known density model is a fair assumption for FWI and does not dramatically affect the long-wavelength model. We applied our method on a part of Marmousi2 model in order to develop P and S wave velocity models via elastic full waveform inversion in the frequency domain.


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