Peer-reviewed literature and reference texts confirm that seismic P waves can convert into S waves when encountering boundaries or interfaces within the Earth's subsurface.
We present the results of P‐to‐S receiver function analysis to improve the 3D image of the sedimentary layer, the upper crust, and lower crust in the Pannonian Basin area. The Pannonian Basin hosts deep sedimentary depocentres superimposed on a complex basement structure and it is surrounded by mountain belts. We processed waveforms from 221 three‐component broadband seismological stations. As a result of the dense station coverage, we were able to achieve so far unprecedented spatial resolution in determining the velocity structure of the crust. We applied a three‐fold quality control process; the first two being applied to the observed waveforms and the third to the calculated radial receiver functions. This work is the first comprehensive receiver function study of the entire region. To prepare the inversions, we performed station‐wise H‐Vp/Vs grid search, as well as Common Conversion Point migration. Our main focus was then the S‐wave velocity structure of the area, which we determined by the Neighborhood Algorithm inversion method at each station, where data were sub‐divided into back‐azimuthal bundles based on similar Ps delay times. The 1D, nonlinear inversions provided the depth of the discontinuities, shear‐wave velocities and Vp/Vs ratios of each layer per bundle, and we calculated uncertainty values for each of these parameters. We then developed a 3D interpolation method based on natural neighbor interpolation to obtain the 3D crustal structure from the local inversion results. We present the sedimentary thickness map, the first Conrad depth map and an improved, detailed Moho map, as well as the first upper and lower crustal thickness maps obtained from receiver function analysis. The velocity jump across the Conrad discontinuity is estimated at less than 0.2 km/s over most of the investigated area. We also compare the new Moho map from our approach to simple grid search results and prior knowledge from other techniques. Our Moho depth map presents local variations in the investigated area: the crust‐mantle boundary is at 20–26 km beneath the sedimentary basins, while it is situated deeper below the Apuseni Mountains, Transdanubian and North Hungarian Ranges (28–33 km), and it is the deepest beneath the Eastern Alps and the Southern Carpathians (40–45 km). These values reflect well the Neogene evolution of the region, such as crustal thinning of the Pannonian Basin and orogenic thickening in the neighboring mountain belts.
Shear wave velocity (Vs) is a fundamental property of elastic media whose estimation from PS converted waves is challenging and requires modeling the boundary where P to S conversion occurs. This paper presents a PS tomography where seismic wave conversion/reflection points correspond to reflectors modelled with the level-set function set to zero (φ(x, z) = 0). The proposed method aims for stable Vs inversion in a seismic acquisition setting using multicomponent receivers. Synthetic models simulating true Vs, Vp and the location of the geological reflector are used in the study. The inversion starts by locating a flat reflector, φ(x, z) = 0, which defines the zone Ω1 between the surface and the reflector, where the initial Vs and Vp fields are also set. To calculate the traveltimes of incident PT (P wave that propagates in Ω1 from source to the reflector) , converted PS, and reflected PP waves, for both observed and modelled data (forward problem), the methodology proposed by Rawlinson and Sambridge is adopted. This method uses the arrival times of the P-waves, Tpt, from the seismic source at each reflector point as secondary sources generating the times Tps and Tpp. These times are calculated as a solution to the Eikonal equation by using the Fast Marching method. The PS and PP residual times are minimized by updating Vs, Vp, and φ(x, z) = 0 through adjoint variables designed from a formulation using Lagrange Multipliers in a variational context. The performance of the algorithm is evaluated for models with synclinal, sinusoidal and monoclinal reflector geometries using numerical tests considering the inversion of: 1) φ, given the true values of Vs and Vp; 2) φ and Vs, given the true value of Vp; 3) φ and Vp, given the true value of Vs; and 4) the three parameters φ, Vs, and Vp, simultaneously. Good results are obtained by inverting Vs and φ, given the true value of Vp. The simultaneous inversion of the three parameters exhibits promising results, despite the illumination problems caused by the different distribution of the PS, PP, and PT time gradients due to the geometry of the reflectors and the acquisition setting (sources-receivers in the same plane). The proposed tomography estimates Vs and reflector positions which could help in statics corrections and improve the lithological characterization of near surface.
difficult for seismic waves to penetrate. Moreover, S-wave detection is challenging due to minimal compressional-shear wave conversion at the boundary and substantial
Seismic velocity structure is the distribution and variation of seismic wave speeds within Earth's and other planetary bodies' subsurface. It is reflective of subsurface properties such as material composition, density, porosity, and temperature. Geophysicists rely on the analysis and interpretation of the velocity structure to develop refined models of the subsurface geology, which are essential
Seismic…
Seismic waves traverse the Earth's layers at speeds that differ according to each layer's unique properties, with their velocities shaped by the respective temperature, composition, and pressure. The Earth's structure features distinct seismic discontinuities where these velocities shift abruptly, signifying changes in mineral composition or physical state.
The main topics are: 1) the effects of lateral structure, in particular, complicated sedimentary basins on the propagation and amplication of seismic strong motion; and 2) the effects of ocean continent transition zones on L sub g waves. 1) 2-D finite difference techniques are used to model the seismic strong motions observed for the 1971 San Fernando earthquake. The finite difference seismograms show strong effects due to lateral variation in sediment thickness in the San Fernando valley and the Los Angeles basin. Using basin structure derived mostly from well logs and teleseismically determined source parameters, two dimensional SH and P-SV finite difference calculations reproduce the amplitude and duration of the strong motion velocities recorded across the Los Angeles and San Fernando basins for the period range 2-10 secs. The edges of basins nearest the seismic source show ground motion amplification up to a factor of three over the case without the basin, and tend to convert direct shear waves into Love and Rayleigh waves that travel within the basin. 2) The methods for Representation Theorem coupling of finite element or finite difference calculations and propagator matrix method calculations to produce a hybrid method for propagation of SH mode sum seismograms across paths that contain regions of non plane-layered structure are explained and developed.
Abstract In addition to monitoring the oceans for signs of nuclear explosions, data from the hydroacoustic component of the International Monitoring System (IMS) have been used for a broad range of civil and scientific applications. This includes studying T phases: seismic waves that convert to underwater acoustic energy at the bottom of the ocean and can travel with low attenuation in the ocean’s Sound Fixing and Ranging channel. This study analyzes T phases recorded from 2001 to 2024 at the six IMS hydrophone stations. Analysis reveals global ocean coverage and demonstrates the network’s ability to detect T phases primarily linked to submarine earthquakes concentrated along tectonic plate boundaries, particularly midocean ridges and transform faults. Notably, some T phases were recorded after propagating more than 20,000 km, exceeding the antipodal range. Results highlight the network’s significant contribution to our understanding of global ocean seismicity. A discussion is provided on earthquake events that led to major detection peaks of T phases in analyst-reviewed bulletins. Finally, it is shown that while T phase detection itself is not network dependent, associating them with events relies on IMS seismic network sensitivity for building the events.
SSS correspond to S waves reflected at the surface. Because P waves can convert to S waves, and vice versa … interfaces, P waves convert to SV waves, and vice versa, whereas SH waves do not convert to either P or … that P waves incident from the water give rise to significant S waves in the crust and that S waves incident
Everything we examined (6) — 5 independent sources
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