Honouring Geological Information in Seismic Amplitude-Versus-Slowness Inversion

Abstract

Seismic waves from active experiments carry information regarding the subsurface in the form of reflected data that is recorded at the surface. This recorded data is subjected to sophisticated processing methods to estimate relevant parameters describing the geology of the subsurface. Traditionally the recorded data is used to create an image of the subsurface in terms of reflectivities, using seismic migration, which back-projects the data recorded at the surface into the earth. The resulting image can be interpreted in terms of structures and depositional patterns. There is another route that is followed to quantify the elastic properties of the subsurface by means of inversion of the recorded data. The essence of seismic inversion is to obtain the elastic properties of the earth’s subsurface from a finite set of noisy measurements, by forward modelling based on assumed properties and feed-back that projects the data mismatch onto model parameter space. Full-waveform inversion (FWI) is a special form of inversion that is gaining considerable attention in the last decade, which can be attributed to the advancement in the computational power available. However, several challenges remain for multi-parameter FWI to be successfully implemented on real size data problems in industry or academia at a scale fine enough to be useful in reservoir characterization.