Tolulope Olugboji

and 4 more

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, i.e., 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 (CCP) stack at continental margins, and seismic data from ocean islands. The application of CRISP-RF to global datasets will advance our understanding of the enigmatic origins of the upper mantle discontinuities like the ubiquitous Mid-Lithospheric Discontinuity (MLD) and the elusive X-discontinuity.

Ziqi Zhang

and 1 more

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) the Alaska amphibious community seismic experiment (AACSE), (2) Earthscope transportable array stations deployed in the sedimentary basin around the Mississippi embayment, and (3) stations 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. Application of our technique to single stations shows that signal enhancement is best when reverberation is attributable to a single layer. 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.

Ziqi Zhang

and 1 more

While the receiver function technique has been successfully applied to high-resolution imaging of sharp discontinuities within and across the lithosphere, it has been shown, however, that 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. Here, we show how one can silence this singing effect. We demonstrate, using analytical and synthetic waveform modeling, that this singing effect can be reversed using dereverberation filters tuned to match the elastic property of each layer. We apply the filter approach to high-quality earthquake records collected from the NoMelt seismic array deployed on normal, mature (~70 Ma) Pacific seafloor. An appropriate filter designed using the elastic properties of the underlying sediments, and obtained from prior studies, greatly improves the detection of Ps conversions generated 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 filter is robust to small errors in the sediment properties. Our analysis suggests that appropriately 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 base of the oceanic plate across a growing fleet of ocean bottom seismic arrays being deployed in the global oceans.