Random and small-scale subsurface heterogeneities in velocity and/or density scatter the seismic wavefield when they have scale lengths on the order of the seismic wavelength. Seismic scattering is considered the origin of coda waves. Such inhomogeneities have an important effect on propagating waves, as they generate traveltime and amplitude fluctuations and may be the cause of attenuation or excitation of secondary waves. Understanding the effect of small-scale heterogeneities on the seismic wavefield is important for the characterization of the seismic source (e.g. source parameters of underground nuclear explosions) and to improve our knowledge of the Earth’s structure along the raypath. Several approaches and methods have been suggested to study the scattering of seismic waves and characterise subsurface heterogeneities. Here, we apply a combination of the analysis of the incoherent wavefield component and the coda decay with time to a dataset of over 350 teleseismic events (over 20000 traces) recorded at three seismic arrays (Warramunga, Alice Springs and Pilbara) in Australia. This combination allow us to obtain a series of parameters (correlation length, RMS velocity fluctuations of the heterogeneities and thickness of the scattering layer) that give us a measure of the spatial scale and the magnitude of the heterogeneities present in the lithosphere beneath the arrays. This is the first time such a large dataset is used for a study of these characteristics. Our new results show similar structures and scattering strength for Alice Springs and Warramunga, while revealing a different tectonic signature and stronger scattering in the case of Pilbara, possibly caused by the different thicknesses of crust and lithosphere between these regions and its different tectonic history. These stochastic models of the lithosphere are the first step in the development of a technique analogous to adaptive optics which, in this case, aims at removing the effect of the small-scale, near receiver structure from recorded wavefields, thus enabling us to improve our source characterization and to more clearly image the Earth’s interior.