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Abstract The investigation of upper mantle structure beneath the US has revealed a growing diversity of discontinuities within, across, and underneath the sub‐continental lithosphere. As the complexity and variability of these detected discontinuities increase—for example, velocity increase/decrease, number of layers and depth—it is hard to judge which constraints are robust and which explanatory models generalize to the largest set of constraints. Much work has been done to image discontinuities of interest using S‐waves that convert to P‐waves (or top‐side reflected SS waves). A higher resolution method using P‐to‐S scattered waves is preferred but often obscured by multiply reflected waves trapped in a shallower layer, limiting the visibility of deeper boundaries. Here, we address the interference problem and re‐evaluate upper mantle stratification using filtered P‐to‐S receiver functions (Ps‐RFs) interpreted using unsupervised machine‐learning. Robust insight into upper mantle layering is facilitated with CRISP‐RF: Clean Receiver‐Function Imaging using Sparse Radon Filters. Subsequent sequencing and clustering organizes the polarity‐filtered Ps‐RFs into distinct depth‐based clusters. We find three types of upper mantle stratification beneath the old and stable continental US: (a) intra‐lithosphere discontinuities (paired or single boundary), (b) transitional discontinuities (single boundary or with a top layer), and (c) sub‐lithosphere discontinuities. Our findings contribute a more nuanced understanding of mantle discontinuities, offering new perspectives on the nature of upper mantle layering beneath continents. 

ABSTRACT The receiver function (RF) is a widely used crustal imaging technique. In principle, it assumes relatively noise-free traces that can be used to target receiver-side structures following source deconvolution. In practice, however, mode conversions and reflections may be severely degraded by noisy conditions, hampering robust estimation of crustal parameters. In this study, we use a sparsity-promoting Radon transform to decompose the observed RF traces into their wavefield contributions, that is, direct conversions, multiples, and incoherent noise. By applying a crustal mask on the Radon-transformed RF, we obtain noise-free RF traces with only Moho conversions and reflections. We demonstrate, using a synthetic experiment and a real-data example from the Sierra Nevada, that our approach can effectively denoise the RFs and extract the underlying Moho signals. This greatly improves the robustness of crustal structure recovery as exemplified by subsequent H−κ stacking. We further demonstrate, using a station sitting on loose sediments in the Upper Mississippi embayment, that a combination of our approach and frequency-domain filtering can significantly improve crustal imaging in reverberant settings. In the presence of complex crustal structures, for example, dipping Moho, intracrustal layers, and crustal anisotropy, we recommend caution when applying our proposed approach due to the difficulty of interpreting a possibly more complicated Radon image. We expect that our technique will enable high-resolution crustal imaging and inspire more applications of Radon transforms in seismic signal processing. 

SUMMARY Seismic interrogation of the upper mantle from the base of the crust to the top of the mantle transition zone has revealed discontinuities that are variable in space, depth, lateral extent, amplitude and lack a unified explanation for their origin. Improved constraints on the detectability and properties of mantle discontinuities can be obtained with P-to-S receiver function (Ps-RF) where energy scatters from P to S as seismic waves propagate across discontinuities of interest. However, due to the interference of crustal multiples, uppermost mantle discontinuities are more commonly imaged with lower resolution S-to-P receiver function (Sp-RF). In this study, a new method called CRISP-RF (Clean Receiver-function Imaging using SParse Radon Filters) is proposed, which incorporates ideas from compressive sensing and model-based image reconstruction. The central idea involves applying a sparse Radon transform to effectively decompose the Ps-RF into its underlying wavefield contributions, that is direct conversions, multiples, and noise, based on the phase moveout and coherence. A masking filter is then designed and applied to create a multiple-free and denoised Ps-RF. We demonstrate, using synthetic experiment, that our implementation of the Radon transform using a sparsity-promoting regularization outperforms the conventional least-squares methods and can effectively isolate direct Ps conversions. We further apply the CRISP-RF workflow on real data, including single station data on cratons, common-conversion-point stack at continental margins and seismic data from ocean islands. The application of CRISP-RF to global data sets will advance our understanding of the enigmatic origins of the upper mantle discontinuities like the ubiquitous mid-lithospheric discontinuity and the elusive X-discontinuity. 

Abstract 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 (a) a land station sitting on Songliao basin, (b) an ocean bottom station in the fore‐arc setting of the Alaska amphibious community seismic experiment, and (c) 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. 

Abstract While the receiver function technique has been successfully applied to high‐resolution imaging of sharp discontinuities within and across the lithosphere, it suffers from severe limitations when applied to seafloor seismic recordings. This is because the water and sediment layer could strongly influence the receiver function traces, making detection and interpretation of crust and mantle layering difficult. This effect is often referred to as the singing phenomena in marine environments. We demonstrate, using analytical and synthetic modeling, that this singing effect can be reversed using a selective dereverberation filter tuned to match the elastic property of each layer. We apply the dereverberation filter to high‐quality earthquake records collected from the NoMelt seismic array deployed on normal, mature Pacific seafloor. An appropriate filter designed using the elastic properties of the underlying sediments, obtained from prior studies, greatly improves the detection of Ps conversions from the Moho (∼8.6 km) and from a sharp discontinuity (<∼5 km) across the lithosphere asthenosphere transition (∼72 km). Sensitivity tests show that the dereverberation filter is mostly sensitive to the two‐way travel time of the shear wave in sediment and is robust to seismic noise and small errors in the sediment properties. Our analysis suggests that selectively filtering out the sediment reverberations from ocean seismic data could make inferences on subsurface structure more robust. We expect that this study will enable high‐resolution receiver function imaging of the oceanic plate across the growing ocean bottom seismic arrays being deployed in the global oceans.