Estimation of a High Resolution P-wave Velocity Model of the Seabed Layers by Means of Global and a Gradient-based FWI

Abstract

Summary We present a two-step procedure to full-waveform inversion (FWI) that combines a stochastic, genetic algorithm optimization and a subsequent gradient-based inversion with the aim to estimate a high-resolution P-wave velocity (Vp) model of the shallow seabed layers. In particular, we take advantage of the broad band frequency content of the seismic well-site (WSS) data to extend the frequency range up to 70 Hz. The first step is a genetic algorithm optimization aimed at deriving a reliable starting model for the subsequent gradient-based FWI. The lack of low frequencies and the limited maximum offset of the WSS acquisition, make the GA inversion particularly crucial as it provides a Vp field that contains the low-medium wavelengths of the subsurface compressional velocity field. These wavelengths are essential to attenuate the risk for the following gradient-based FWI of being trapped into local minima. The gradient-based FWI is performed in the acoustic approximation thus inverting for the Vp only. This two-step procedure yields a final Vp model characterized by an improved resolution with respect to the outcomes of GA-FWI and many fine details of the layering. The fair match between the reflections kinematics in the actual and predicted data supports the reliability of the final model.