Lithospheric Imaging through Reverberant Layers: Sediments, Oceans, and Glaciers

Abstract

<p>The Earth, in large portions, is covered in oceans, sediments, and glaciers. High-resolution body wave imaging in such environments often suffers from severe reverberations, that is, repeating echoes of the incoming scattered wavefield trapped in the reverberant layer, making interpretation of lithospheric layering difficult. In this study, we propose a systematic data-driven approach, using autocorrelation and homomorphic analysis, to solve the twin problem of detection and elimination of reverberations without a priori knowledge of the elastic structure of the reverberant layers. We demonstrate, using synthetic experiments and data examples, that our approach can effectively identify the signature of reverberations even in cases where the recording seismic array is deployed in complex settings, for example, using data from (1) a land station sitting on Songliao basin, (2) an ocean bottom station in the fore-arc setting of the Alaska amphibious community seismic experiment (AACSE), and (3) a station deployed on ice-sediment strata in the glaciers of Antarctica. The elimination of the reverberation is implemented by a frequency domain filter whose parameters are automatically tuned using seismic data alone. On glaciers where the reverberating sediment layer is sandwiched between the lithosphere and an overlying ice layer, homomorphic analysis is preferable in detecting the signature of reverberation. We expect that our technique will see wide application for high-resolution body wave imaging across a wide variety of conditions.</p>

Incorporating H‐κ Stacking With Monte Carlo Joint Inversion of Multiple Seismic Observables: A Case Study for the Northwestern US

“…One possible solution is to use higher‐frequency RFs to separate the Moho‐converted phases and sediment‐reverberations since the low‐velocity sedimentary layer can result in low‐frequency reverberations. A more direct solution is removing the sediment‐reverberations from the RFs (e.g., Yu et al., 2015; Z. Zhang & Olugboji, 2023). If these approaches can be applied to the RFs that we used in MC inversion, the asymmetric problem may be solved.…”

Waveform Fitting of Receiver Functions for Enhanced Retrieval of Crustal Structure in the Presence of Sediments

“…Furthermore, the effectiveness of the resonance filter degrades when the delay in the PbS arrival is large (e.g., due to a thick or very low‐velocity sediment layer), when the impedance contrast at the base the sediment layer is low or when sediment layer is very thin (<one fourth of the wavelength of a PbS phase) or very thick (∼5 km or thicker) (Yu et al., 2015). Zhang and Olugboji (2023) further extended the reverberation filtering technique in a data‐driven approach for cases where two or more types of reverberant layers are present (sediment, ocean and glaciers) using homomorphic analysis. A slightly different, two‐step approach was proposed by Yeck et al.…”

Characterizing the Seafloor Sediment Layer Using Teleseismic Body Waves Recorded by Ocean Bottom Seismometers

“…Concerted efforts to investigate and understand the consequences of the seafloor sediment layer on OBS signals are needed to effectively differentiate the phases due to the sediment layer from signals associated with deeper structures (e.g., lithosphere–asthenosphere boundary). Recent receiver function studies have attempted to detect and remove monotonic oscillations (e.g., Zhang & Olugboji, 2023) and reduce/correct the sediment effects to image the structure under oceans (e.g., Kim et al., 2021; Rychert et al., 2018).…”