Description: A vast majority of marine geological research is based on academic seismic data collected with single-channel systems or short-offset multichannel seismic cables, which often lack reflection moveout for conventional velocity analysis. Consequently, our understanding of Earth processes often relies on seismic time sections, which hampers quantitative analysis in terms of depth, formation thicknesses, or dip angles of faults. In order to overcome these limitations, we present a robust diffraction extraction scheme that models and adaptively subtracts the reflected wavefield from the data. We use diffractions to estimate insightful wavefront attributes and perform wavefront tomography to obtain laterally resolved seismic velocity information in depth. Using diffraction focusing as a quality control tool, we perform an interpretation-driven refinement to derive a geologically plausible depth-velocity model. In a final step, we perform depth migration to arrive at a spatial reconstruction of the shallow crust. Further, we focus the diffracted wavefield to demonstrate how these diffraction images can be used as physics-guided attribute maps to support the identification of faults and unconformities. We demonstrate the potential of this processing scheme by its application to a seismic line from the Santorini Amorgos Tectonic Zone, located on the Hellenic Volcanic Arc, which is notorious for its catastrophic volcanic eruptions, earthquakes, and tsunamis. The resulting depth image allows a refined fault pattern delineation and, for the first time, a quantitative analysis of the basin stratigraphy. We conclude that diffraction-based data analysis has a high potential, especially when the acquisition geometry of seismic data does not allow conventional velocity analysis.

Description: The active seismic method is a standard tool for studying the Earth's lithosphere. On scales from centimeters to kilometers, academic research is generally interested in highly complex geological targets such as volcanic edifices, crustal faults or salt environments. In order to properly image these structures, large and expensive multichannel acquisitions with a high offset-to-target depth ratio are required. In practice, however, these are often hardly affordable for academic institutions, with the result that reflections often only poorly illuminate laterally variable structures, which in turn compromises imaging and interpretation. As in common practice, most of the processing and interpretational steps are tailored to the reflected wavefield, faint diffracted contributions are typically considered as an unwanted by-product. In recent works, however, it has been shown that diffractions possess unique properties which bear the potential to overcome the aforementioned limitations. Wave diffraction occurs at geodynamically important features like faults, pinch-outs, erosional surfaces or other small-scale scattering objects and encodes sub-wavelength information on the scattering geometry. Since diffracted waves do not obey Snell's Law, they provide superior illumination compared to reflected waves. Moreover, due to their passive-source like radiation, they encode their full multichannel response in prominent data subsets like the zero-offset section. In order to explore what can be learned from the faint diffracted wavefield, we use academic seismic data from the Santorini-Amorgos Tectonic Zone (SATZ) in the Southern Aegean Sea. This is an area well known for its local complexity, indicated by the occurrence of extended fault systems and volcanic edifices as well as a complex acoustic basement. As the available seismic data in this region were acquired using a relatively short streamer, the SATZ represents a classical example for the need of innovative methods for seismic processing and interpretation. By means of a robust and computationally efficient scheme for the extraction of diffractions that models and adaptively subtracts the reflected wavefield from the data, we reveal a rich diffracted wavefield from zero-offset data. On the one hand, we use the diffraction-only sections for analysing the small-scale structural complexity and demonstrate that the geological interpretation can benefit from these observations. On the other hand, we use the diffractions to estimate insightful wavefront attributes in the zero-offset domain. Based on these attributes, we perform wavefront tomography to obtain depth-velocity models. Compared to depth-velocity models derived from the reflected contributions, the diffraction-based velocity model fits the data significantly better. After refining this velocity model, we perform prestack depth migration and obtain highly valuable depth converted seismic sections. Concluding our results, we strongly encourage the incorporation of diffractions in standard processing and interpretational schemes.

Description: Most established methods for the estimation of subsurface velocity models rely on the measurements of reflected or diving waves and therefore require data with sufficiently large source-receiver offsets. For seismic data that lacks these offsets, such as vintage data, low-fold academic data or near zero-offset P-Cable data, these methods fail. Building on recent studies, we apply a workflow that exploits the diffracted wavefield for depth-velocity-model building. This workflow consists of three principal steps: (1) revealing the diffracted wavefield by modeling and adaptively subtracting reflections from the raw data, (2) characterizing the diffractions with physically meaningful wavefront attributes, (3) estimating depth-velocity models with wavefront tomography. We propose a hybrid 2D/3D approach, in which we apply the well-established and automated 2D workflow to numerous inlines of a high-resolution 3D P-Cable dataset acquired near Ritter Island, a small volcanic island located north-east of New Guinea known for a catastrophic flank collapse in 1888. We use the obtained set of parallel 2D velocity models to interpolate a 3D velocity model for the whole data cube, thus overcoming possible issues such as varying data quality in inline and crossline direction and the high computational cost of 3D data analysis. Even though the 2D workflow may suffer from out-of-plane effects, we obtain a smooth 3D velocity model that is consistent with the data.

Description: While established methods for the retrieval of depth-velocity models require seismic data with sufficiently large channel counts, velocity-model building for zero-offset data remains challenging. Building on recent studies, we propose a workflow that exploits the diffracted wavefield for depth-velocity model building. This workflow consists of three principal steps: (1) revealing the diffracted wavefield by modeling and adaptively subtracting reflections from the raw data, (2) characterizing the diffractions with physically meaningful wavefront attributes, (3) estimating depth-velocity models with wavefront tomography. In this study, we apply this workflow to a set of inlines taken from a 3D P-Cable dataset acquired near Ritter Island and use the obtained 2D velocity models to approximate a 3D velocity model for the whole data cube.

Description: A vast majority of marine geological research is based on academic seismic data collected with single‐channel systems or short‐offset multichannel seismic cables, which often lack reflection moveout for conventional velocity analysis. Consequently, our understanding of Earth processes often relies on seismic time sections, which hampers quantitative analysis in terms of depth, formation thicknesses, or dip angles of faults. In order to overcome these limitations, we present a robust diffraction extraction scheme that models and adaptively subtracts the reflected wavefield from the data. We use diffractions to estimate insightful wavefront attributes and perform wavefront tomography to obtain laterally resolved seismic velocity information in depth. Using diffraction focusing as a quality control tool, we perform an interpretation‐driven refinement to derive a geologically plausible depth‐velocity model. In a final step, we perform depth migration to arrive at a spatial reconstruction of the shallow crust. Further, we focus the diffracted wavefield to demonstrate how these diffraction images can be used as physics‐guided attribute maps to support the identification of faults and unconformities. We demonstrate the potential of this processing scheme by its application to a seismic line from the Santorini Amorgos Tectonic Zone, located on the Hellenic Volcanic Arc, which is notorious for its catastrophic volcanic eruptions, earthquakes, and tsunamis. The resulting depth image allows a refined fault pattern delineation and, for the first time, a quantitative analysis of the basin stratigraphy. We conclude that diffraction‐based data analysis has a high potential, especially when the acquisition geometry of seismic data does not allow conventional velocity analysis.