A Reflectivity Guided Elastic Full Waveform Inversion

Abstract

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.