Thusfar, waveform-based inversion methods have utilized the spatial distribution of back-projected reflectivities in order to refine velocity (and density) models. While these methods excel at refining a velocity model for high-wavenumber features, they face significant difficulties when attempting to invert for long-wavelength features several kilometres below the depth of acquisition. In this abstract, we develop the theory for a waveform-based inversion method that utilizes an impedance image, rather than a reflectivity image, in order to extract spatial variations in velocity and density. Results are presented for the first stage of an inversion using a 2-D line of dual-sensor, single-streamer, field recordings. It is shown that features with vertical scale sizes up to 0.5 km can be determined at depths up to 4 km, using data with a maximum offset of only 8 km and frequencies below 7.5 Hz.


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