Harnessing sedimentary reverberations: a joint inversion approach for enhanced crustal imaging

: This research is to develop joint-inversion methods involving P travel times, receiver functions, and surface wave dispersion measurements and to apply them to the western China region to obtain 3D models of P and S structures of the crust and upper mantle. We successfully implemented a search-based algorithm (neighborhood algorithm) for joint inversion of surface wave dispersion data, receiver functions, and Pn delay time. The implementation uses parallel programming with MPI calls, making massive data processing possible. We have systematically carried out individual components of the project, obtaining unprecedented data sets for surface wave dispersion, receiver functions, and Pn tomography, needed for the joint inversion. We have tested the joint inversion method and proposed a practical strategy for the joint inversions of the real data. We obtained detailed joint inversion results for the dense Hi-Climb array, which are generally consistent with previous results but show considerable difference in details (crustal structure and Moho depths). We have performed systematically joint inversions of all available stations in western China and obtained 3D S velocity model, average crustal Vp/Vs map, and derived 3D P velocity model of the region.

The northeastern part of South Korea, Gangwon Province, is closely connected to major tectonic activities of the Korean Peninsula, such as the formation of the Taebaek Mountain ranges and the opening of the East Sea (Sea of Japan). Therefore, analyzing the velocity structure of Gangwon Province can provide insights into the tectonic history of the Korean Peninsula. We calculated receiver functions for 96 broadband and accelerometer seismic stations using 369 teleseismic event data (Mw ≥ 5.8, with epicentral distances from 30° to 90°), recorded between March 18, 2019, and May 31, 2024. We estimated Moho depth and Vp/Vs ratio in Gangwon Province using H-k stacking method, and we obtained 1-D S-wave crustal velocity models for each stations using joint inversion of receiver functions and surface-wave dispersion. Moho depth and Vp/Vs ratios derived from H-k stacking method ranged from 23.0 to 35.6 km and 1.68 to 1.85, respectively. Most stations located along the eastern coast exhibited relatively shallow Moho depth and high Vp/Vs ratios. From the 1-D S-wave crustal velocity models obtained using the joint inversion, we identified velocity inversion layer and mid-crustal discontinuities beneath several stations. The Moho depth was determined as the layer with an S-wave velocity exceeding 4.0 km/s and the largest velocity gradient, resulting in depths ranging from 23.9 to 35.7 km, which are consistent with the Moho depths obtained from H-k stacking. The trend of Moho depth distribution in Gangwon Province is shallow along the coast and deepens through the Taebaek mountain ranges, but it does not align with Airy isostasy. Accordingly, We calculated residual topography, and the result suggests the possibility of additional isostatic uplift along the Taebaek Mountain ranges and the eastern coast.

The internal structure of a planet provides constraints for understanding its evolution and dynamics. In November 2018, the InSight spacecraft landed on Mars and deployed a set of geophysical instruments, including one seismological station. In this work, the subsurface structure at the InSight landing site (ILS) is explored, from the shallow subsurface to crustal depths, by applying single-station seismological techniques (SST) on martian ambient vibrations and seismic events data.The shallow subsurface at the ILS, in the order of meters, is investigated using the horizontal-to-vertical spectral ratios (HVSR) from the coda of martian seismic events. Assuming a fully diffuse wavefield, a nonlinear inversion using the conditional Neighbourhood Algorithm (NA) allowed to map the shallow subsurface at the ILS. Due to the non-uniqueness problem, different sets of models are retrieved. The 8 Hz HVSR peak can be explained by a Rayleigh wave resonance due to a shallow high-velocity layer, while the 2.4 Hz trough is explained by a P-wave resonance due to a buried low-velocity layer. The kilometer-scale subsurface was constrained by Rayleigh wave ellipticity measurements from large martian seismic events. The ellipticity measurements (0.03-0.07 Hz) were jointly inverted with P-to-s Receiver Functions and P-wave lag times from autocorrelations, to provide a subsurface model for the martian crust at the ILS. The joint inversion allowed the thickness and velocities of a new surface layer, previously proposed only conceptually, to be constrained by multiple seismological data. The HVSR in the 0.06-0.5 Hz frequency range from the coda of S1222a, the largest event ever recorded on Mars, suggests a gradual transition from shallow to crustal depths and consolidates the group of shallow subsurface models with the largest shear-wave velocities as the most compatible with the crustal structure.A comprehensive multi-scale model of the ILS subsurface is proposed. The ILS is characterized by the emplacement of a low-velocity regolith/coarse ejecta layer over a high-velocity Amazonian fractured lava flow (~2 km/s, ~30 m thick). A buried Late Hesperian-Amazonian sedimentary layer is deposited below (~450 m/s, ~30 m thick), underlain by a heavily weathered Early Hesperian lava flow. The latter overlays a thick, likely Noachian sedimentary layer that extends to a depth of 2-3 km. This shallow structure forms the first crustal layer derived from the joint inversion. Deeper crustal layers are consistent with other reported ILS models, with intracrustal discontinuities at 8-12 km and 18-23 km depth. The Moho depth at the ILS is found at 35-45 km depth. Shear-wave velocities above ~20 km depth are lower than 2.5 km/s, slower than in other regions of Mars, suggesting a higher alteration due to local processes or a different origin of the upper crust at the ILS. The proposed model is consistent with the geologic history of Mars and other independent observations, confirming the great potential of SST for multi-scale investigation of, e.g., other planetary bodies or understudied regions on Earth.

In recent years, surface‐wave dispersion has been used to image lithospheric structure jointly with receiver function or Rayleigh‐wave ellipticity. Because surface‐wave dispersion is the total propagation effect of the travel path, the joint inversion relies on dense seismic arrays or high seismicity to obtain local velocity structure. However, both receiver function and Rayleigh‐wave ellipticity are single‐station measurements with localized sensitivities and could be combined for joint inversion naturally. In this article, we explored the feasibility of the joint inversion of Rayleigh‐wave ellipticity and receiver function. We performed sensitivity tests with forward modeling and found that the receiver function is sensitive to sharp velocity interfaces but shows weak sensitivity to long‐wavelength structure, almost complementary to Rayleigh‐wave ellipticity. Therefore, joint inversion with two single‐station measurements provides tighter constraints on the velocity structure beneath the seismic station. A joint inversion algorithm based on the fast simulated‐annealing method is developed to invert Rayleigh‐wave ellipticity and receiver function for the lithospheric structure. Application of the algorithm to the Indian craton and the Williston basin in the United States demonstrates its effectiveness in reducing the nonuniqueness of the inversion. However, the joint inversion may fail to resolve the average crustal velocity, suggesting the need to combine surface‐wave dispersion (or other type of observations), receiver function, and Rayleigh‐wave ellipticity to more accurately resolve the velocity structure.

ساختار سرعتی پوسته و عمق ناپیوستگی موهو در زیر 7 ایستگاه لرزه نگاری باند پهن آفریز ((AFRZ، کوهدشت (TKDS)، پرواده (TPRV)، نستنج ((TNSJ، انارک (ANAR) و کارشاهی (KRSH) مربوط به مرکز لرزه‌نگاری کشوری (IRSC) و ایستگاه یزد (YZKH) مربوط به مرکز ملی شبکه لرزه-نگاری باندپهن ایران ( (INSNواقع در مرکز ایران با استفاده از روش برگردان همزمان توابع انتقال گیرنده موج P و منحنی‌های پاشندگی سرعت گروه امواج رایلی مورد مطالعه قرار گرفت. شکل‌موج‌های دورلرز (فاصله رومرکزی 90-25 درجه) در بازه‌ زمانی سه سال (2012 تا 2014) برای به ‌دست آوردن توابع از روش تکرار واهمامیخت در حوزه زمان مورد استفاده قرار گرفت و منحنی‌های پاشندگی سرعت گروه موج رایلی از مطالعه‌ی بر روی ساختار پوسته و گوشته‌ی بالایی فلات ایران در بازه‌ی دوره‌ی تناوبی 10 تا 100 ثانیه تامین شده است. ناهماهنگی عمق- سرعت در اطلاعات توابع گیرنده باعث غیریکتایی مساله‌ی برگردان می‌شود، که با دخالت دادن اطلاعات حاصل از سرعت‌ مطلق برآوردهای پاشندگی و برگردان هم‌زمان این دو مجموعه‌ی داده‌ای، می‌توان بر این محدودیت غلبه کرد. با این‌کار، اطلاعات دقیقتری درمورد ساختار پوسته‌ای فراهم می‌شود. جهت اعتبار سنجی مدل حاصل از برگردان از مدلسازی مستقیم استفاده گردید. نتایج مطالعه حاصل نشان می دهد که مرز موهو در در زیر ایستگاههای آفریز، کوهدشت و پرواده در عمق 40 کیلومتری، در زیر ایستگاه نستنج در عمق 42 کیلومتری، در زیر ایستگاه انارک، در عمق 38 کیلومتری و در زیر ایستگاههای یزد و کارشاهی، در عمق 44 کیلومتری قرار دارد. میانگین عمق موهو در مرکز ایران 42 کیلومتر می باشد.

Mapping the Moho with seismic surface waves: A review, resolution analysis, and recommended inversion strategies

SUMMARYIn the field of seismic interferometry, cross-correlations are used to extract Green’s function from ambient noise data. By applying a single station variation of the method, using autocorrelations, we are in principle able to retrieve zero-offset reflections in a stratified Earth. These reflections are valuable as they do not require an active seismic source and, being zero-offset, are better constrained in space than passive earthquake based measurements. However, studies that target Moho signals with ambient noise autocorrelations often give ambiguous results with unclear Moho reflections. Using a modified processing scheme and phase-weighted stacking, we determine the Moho P-wave reflection time from vertical autocorrelation traces for a test station with a known simple crustal structure (HYB in Hyderabad, India). However, in spite of the simplicity of the structure, the autocorrelation traces show several phases not related to direct reflections. Although we are able to match some of these additional phases in a qualitative way with synthetic modelling, their presence makes it hard to identify the reflection phases without prior knowledge. This prior knowledge can be provided by receiver functions. Receiver functions (arising from mode conversions) are sensitive to the same boundaries as autocorrelations, so should have a high degree of comparability and opportunity for combined analysis but in themselves are not able to independently resolve VP, VS and Moho depth. Using the timing suggested by the receiver functions as a guide, we observe the Moho S-wave reflection on the horizontal autocorrelation of the north component but not on the east component. The timing of the S reflection is consistent with the timing of the PpSs–PsPs receiver function multiple, which also depends only on the S velocity and Moho depth. Finally, we combine P receiver functions and autocorrelations from HYB in a depth–velocity stacking scheme that gives us independent estimates for VP, VS and Moho depth. These are found to be in good agreement with several studies that also supplement receiver functions to obtain unique crustal parameters. By applying the autocorrelation method to a portion of the EASI transect crossing the Bohemian Massif in central Europe, we find approximate consistency with Moho depths determined from receiver functions and spatial coherence between stations, thereby demonstrating that the method is also applicable for temporary deployments. Although application of the autocorrelation method requires great care in phase identification, it has the potential to resolve both average crustal P and S velocities alongside Moho depth in conjunction with receiver functions.

SUMMARY In this work, the Moho depth and the velocity structure of the crust and upper mantle beneath broad-band seismic stations of the Algerian broad-band seismic network are investigated. Teleseismic P-wave receiver functions jointly inverted with Rayleigh wave dispersion curves obtained from local earthquakes have been used. The seismic stations are located in different geological settings including the Tell Atlas, High Plateaus and the Saharan Atlas. The crustal thickness and the Vp/Vs ratio are first derived by the H–κ stacking method of receiver functions. The inversion results show the variation in Moho depth in the different geological contexts. The shallowest depths of the Moho (∼20–30 km) are estimated along the Algerian continental margin and Tell Atlas. In the High Plateaus region, the Moho depths vary from 30–36 km, whereas the deepest Moho depths are found in the Saharan Atlas (36–44 km). Two-layer crust is observed in the whole study area. In the upper crust, ∼8–14 km thick, the average shear wave velocity is ∼3.0 km s−1. The lower crust of about 12–30 km thick has an average shear wave velocity that ranges between 3.4 and 3.8 km s−1. The lower crust is thicker than the upper crust particularly in the Saharan Atlas. The upper mantle shear wave velocity varies from 4.1 to 4.5 km s−1 maximum and is stable, generally, below ∼60 km depth. Two low-velocity zones are clearly observed particularly in the eastern part of the Tell Atlas and the High Plateaus. The first one about 10 km thick is in the lower part of the lower crust and the other one is in the upper mantle between 40 and 60 km depth. The obtained results are in accordance with the previous results found in the region, particularly those using land gravity and seismic data. As the first estimate of the Moho depth from earthquake data in northern Algeria, using the receiver function method, this study sheds new light on the crustal structure and the Moho depth in this region of the world.

<strong class="journal-contentHeaderColor">Abstract.</strong> We use 1.5 years of continuous recordings from an amphibious seismic network deployment in the region of northeast South America and southeast Caribbean to study the crustal and uppermost mantle structure through a joint inversion of surface wave dispersion curves determined from ambient seismic noise and receiver functions. The availability of both ocean bottom seismometers (OBSs) and land stations makes this experiment ideal to determine the best processing methods to extract reliable empirical Green&rsquo;s functions (EGFs) and construct a 3D shear velocity model. Results show EGFs with high signal-to-noise ratio for land-land, land-OBS and OBS-OBS paths from a variety of stacking methods. Using the EGF estimates, we measure phase and group velocity dispersion curves for Rayleigh and Love waves. We complement these observations with receiver functions, which allow us to perform an H-k analysis to obtain Moho depth estimates across the study area. The measured dispersion curves and receiver functions are used in a Bayesian joint inversion to retrieve a series of 1D shear-wave velocity models, which are then interpolated to build a 3D model of the region. Our results display clear contrasts in the oceanic region across the border of the strike-slip fault system San Sebastian - El Pilar as well as a high velocity region that corresponds well with the continental craton of southeastern Venezuela. We resolve known geological features in our new model, including the Espino Graben and the Guiana Shield provinces, and provide new information about their crustal structures. Furthermore, we image the difference in the crust beneath the Maturin and Gu&aacute;rico Sub-Basin.

We use 1.5 years of continuous recordings from an amphibious seismic network deployment in the region of northeast South America and southeast Caribbean to study the crustal and uppermost mantle structure through a joint inversion of surface wave dispersion curves determined from ambient seismic noise and receiver functions. The availability of both ocean bottom seismometers (OBSs) and land stations makes this experiment ideal to determine the best processing methods to extract reliable empirical Green’s functions (EGFs) and construct a 3D shear velocity model. Results show EGFs with high signal-to-noise ratio for land-land, land-OBS and OBS-OBS paths from a variety of stacking methods. Using the EGF estimates, we measure phase and group velocity dispersion curves for Rayleigh and Love waves. We complement these observations with receiver functions, which allow us to perform an H-k analysis to obtain Moho depth estimates across the study area. The measured dispersion curves and receiver functions are used in a Bayesian joint inversion to retrieve a series of 1D shear-wave velocity models, which are then interpolated to build a 3D model of the region. Our results display clear contrasts in the oceanic region across the border of the strike-slip fault system San Sebastian - El Pilar as well as a high velocity region that corresponds well with the continental craton of southeastern Venezuela. We resolve known geological features in our new model, including the Espino Graben and the Guiana Shield provinces, and provide new information about their crustal structures. Furthermore, we image the difference in the crust beneath the Maturin and Guárico Sub-Basin.

We use 1.5 years of continuous recordings from an amphibious seismic network deployment in the region of northeast South America and southeast Caribbean to study the crustal and uppermost mantle structure through a joint inversion of surface wave dispersion curves determined from ambient seismic noise and receiver functions. The availability of both ocean bottom seismometers (OBSs) and land stations makes this experiment ideal to determine the best processing methods to extract reliable empirical Green’s functions (EGFs) and construct a 3D shear velocity model. Results show EGFs with high signal-to-noise ratio for land-land, land-OBS and OBS-OBS paths from a variety of stacking methods. Using the EGF estimates, we measure phase and group velocity dispersion curves for Rayleigh and Love waves. We complement these observations with receiver functions, which allow us to perform an H-k analysis to obtain Moho depth estimates across the study area. The measured dispersion curves and receiver functions are used in a Bayesian joint inversion to retrieve a series of 1D shear-wave velocity models, which are then interpolated to build a 3D model of the region. Our results display clear contrasts in the oceanic region across the border of the strike-slip fault system San Sebastian - El Pilar as well as a high velocity region that corresponds well with the continental craton of southeastern Venezuela. We resolve known geological features in our new model, including the Espino Graben and the Guiana Shield provinces, and provide new information about their crustal structures. Furthermore, we image the difference in the crust beneath the Maturin and Guárico Sub-Basin.

The Alpine orogen is a unique geological formation with a highly variable crustal structure. Despite numerous active and passive seismic investigations in the past, constraints on the crustal structure across the whole Alpine domain are still limited. To improve on this, we use waveform data from four past and ongoing large-scale passive experiments in the broader Alpine region: namely the AlpArray Seismic Network (AASN), which also includes many permanent stations in its footprint, the Eastern Alpine Seismic Investigation (EASI), the China-Italy-France Alps seismic transect (CIFALPS-1) and the Pannonian-Carpathian-Alpine Seismic Experiment (PACASE). This results in a composite seismic network of more than 700 broadband seismic stations, providing unprecedented data coverage.&amp;#160;&amp;#160;We apply a systematic processing workflow to these data and calculate Receiver Functions (RF). After applying strict quality control we obtained 107,633 high-quality RF traces, on average of 122 per station. Next, we developed codes to perform time-to-depth migration in a newly implemented 3D spherical coordinate system using a reference P and S wave velocity model. Finally, we compiled a new detailed Moho map by manually picking the depth of the discontinuity. Our Moho depth estimates generally support the results of previous studies in the region and vary from ca. 20 to ca. 55 km depth with the maximum values observed beneath the Alpine orogen. The RF dataset along with the codes and new Moho map are all open-access.&amp;#160;The high quality and homogeneously calculated RF dataset, along with the new, coherently derived Moho depth map of the Alpine region, can provide helpful information for interdisciplinary imaging and modeling studies investigating the geodynamics of the European Alps orogen and its forelands (e.g., joint inversions with other geophysical and geological datasets).&amp;#160;

Imaging lithospheric interfaces and 3D structures using receiver functions, gravity, and tomography in a common inversion scheme

The deep crustal structure of the Paraná Basin of southern Brazil is investigated by analyzing P‐ and PP‐wave receiver functions at 17 Brazilian Lithosphere Seismic Project stations within the basin. The study area can be described as a typical Paleozoic intracratonic basin that hosts one of the largest Large Igneous Province of the world and makes a unique setting for investigating models of basin subsidence and their interaction with mantle plumes. Our study consists of (1) an analysis of the Moho interaction phases in the receiver functions to obtain the thickness and bulk Vp/Vs ratio of the basin's underlying crust and (2) a joint inversion with Rayleigh‐wave dispersion velocities from an independent tomographic study to delineate the detailed S‐wave velocity variation with depth. The results of our analysis reveal that Moho depths and bulk Vp/Vs ratios (including sediments) vary between 41 and 48 km and between 1.70 and 1.76, respectively, with the largest values roughly coinciding with the basin's axis, and that S‐wave velocities in the lower crust are generally below 3.8 km/s. Select sites within the basin, however, show lower crustal S‐wave velocities slightly above 3.9 km/s suggestive of underplated mafic material. We show that these observations are consistent with a fragmented cratonic root under the Paraná basin that defined a zone of weakness for the initial Paleozoic subsidence of the basin and which allowed localized mafic underplating of the crust along the suture zones by Cenozoic magmatism.

Accurately determining the seismic structure of the continental deep crust is crucial for understanding its geological evolution and continental dynamics in general. However, traditional tools such as surface waves often face challenges in solving the trade‐offs between elastic parameters and discontinuities. In this work, we present a new approach that combines two established inversion techniques, receiver function H‐κ stacking and joint inversion of surface wave dispersion and receiver function waveforms, within a Bayesian Monte Carlo (MC) framework to address these challenges. Demonstrated by synthetic tests, the new method greatly reduces trade‐offs between critical parameters, such as the deep crustal Vs, Moho depth, and crustal Vp/Vs ratio. This eliminates the need for assumptions regarding crustal Vp/Vs ratios in joint inversion, leading to a more accurate outcome. Furthermore, it improves the precision of the upper mantle velocity structure by reducing its trade‐off with Moho depth. Additional notes on the sources of bias in the results are also included. Application of the new approach to USArray stations in the Northwestern US reveals consistency with previous studies and identifies new features. Notably, we find elevated Vp/Vs ratios in the crystalline crust of regions such as coastal Oregon, suggesting potential mafic composition or fluid presence. Shallower Moho depth in the Basin and Range indicates reduced crustal support to the elevation. The uppermost mantle Vs, averaging 5 km below Moho, aligns well with the Pn‐derived Moho temperature variations, offering the potential of using Vs as an additional constraint to Moho temperature and crustal thermal properties.