New insights into seismic absorption imaging

In recent years, attenuation has been used as a marker for source and dynamic Earth processes due to its higher sensitivity to small variations of lithospheric properties compared to seismic velocity. From seismic hazard analysis to oil and gas exploration and rock physics, many fields need a better reconstruction of energy absorption, a constituent of seismic attenuation generally considered a reliable marker of fluid saturation in space. Here, we propose absorption tomography (AT), a technique grounded on the principles of scattering tomography and Multiple Lapse Time Window Analysis. We benchmark its efficiency to image absorption in space by comparing its results with those obtained using two of the most common mapping strategies, regionalization and kernel-based inversion for a diffusive regime. We applied these methodologies to three datasets, each characterized by a different tectonic setting and quality of the dataset: the Pollino fault area (Southern Italy), Mount St. Helens volcano (USA) and Vrancea (Romania). AT overcomes the assignment of a single coda quality factor value between each source-receiver pair by modelling and inverting for the spatial distribution of energy as a function of different lapse times. It can then reconstruct node-dependent envelopes using analytic and computational sensitivity kernels and solve for coda attenuation with a grid-search approach. AT allows for a better reconstruction of the localized absorption anomalies than standard methodologies, even if the efficiency of the technique depends on the quality of the dataset, and identifies outliers in the data that could alter the final result and its interpretation. The implementation of analytical diffusive kernels in AT allows for a fast and highly-resolved imaging of well-sampled seismic faults structures. While slightly reducing resolution on faults and being computationally more expensive, implementing multiple-scattering lapse-time-dependent kernels still provides satisfactory results as well as a more physically-correct forward model.