Traveltime Inversion Research Articles

Monochromatic wave-equation traveltime inversion in vertical transverse isotropic media: Theory and application

Wave-equation traveltime inversion (WTI) is a promising tool for reconstructing the intrinsic anisotropy properties of the earth’s interior. However, conventional time-domain implementation of anisotropic WTI involves crosscorrelation between source- and receiver-side time-domain wavefields for gradient calculation, which requires heavy memory consumption and computational cost for storing/recomputing the source-side time-domain wavefields. To overcome this problem, we develop a novel frequency-domain anisotropic WTI method using only monochromatic wavefields during inversion. Thus, the memory requirement and computational cost are significantly reduced, which makes the monochromatic anisotropic WTI practical for real large-size applications. We focus on transversely isotropic media with a vertical symmetry axis (VTI) and aim to invert the P-wave vertical velocity [Formula: see text] and anisotropic parameter [Formula: see text]. The subspace approach is adopted for calculating multiple step lengths to balance the updates of [Formula: see text] and [Formula: see text] values in our VTI WTI method. Synthetic numerical examples based on an inclusion model and the BP 2007 model prove that the proposed monochromatic VTI WTI method can reconstruct background VTI models as accurately as VTI WTI with multiple frequencies. Then, we apply our method to an ocean-bottom seismic data set acquired at the Qiuyue field in the East China Sea. The inverted vertical velocity [Formula: see text] matches well with the long-wavelength component of the sonic well-logging velocity. Compared with the inverted isotropic velocity model, the inverted VTI model produces more focused seismic imaging reflectors throughout the section and more accurately positions the reflector depths, which is confirmed by the sonic well logging.

Accounting for Modeling Errors in Linear Inversion of Crosshole Ground‐Penetrating Radar Amplitude Data: Detecting Sand in Clayey Till

AbstractMapping high permeability sand occurrences in clayey till is fundamental for protecting the underlying drinking water resources. Crosshole ground penetrating radar (GPR) amplitude data have the potential to differentiate between sand and clay, and can provide 2D subsurface models with a decimeter‐scale resolution. We develop a probabilistic straight‐ray‐based inversion scheme, where we account for the forward modeling error arising from choosing a straight‐ray forward solver. The forward modeling error is described by a Gaussian probability distribution and included in the total noise model by addition of covariance models. Due to the linear formulation, we are able to decouple the inversion of traveltime and amplitude data and obtain results fast. We evaluate the approach through a synthetic study, where synthetic traveltime and amplitude data are inverted to obtain slowness and attenuation tomograms using several noise model scenarios. We find that accounting for the forward modeling error is fundamental to successfully obtain tomograms without artifacts. This is especially the case for inversion of amplitude data since the structure of the noise model for the forward modeling error is significantly different from the other data error models. Overall, inversion of field data confirms the results from the synthetic study; however, amplitude inversion performs slightly better than traveltime inversion. We are able to characterize a 0.4–0.6 m thick sand layer as well as internal variations in the clayey till matching observed geological information from borehole logs and excavation.

Onshore model building using elastic full-waveform inversion on surface and body waves: A case study from Sultanate of Oman

We have determined the potential of the elastic full-waveform inversion (FWI) to overcome some difficult challenges in onshore seismic imaging. The approach allows for simultaneous inversion of surface and body waves and, theoretically, is free from the limitations of traditional dispersion curve analysis and traveltime inversion. Indeed, identification and separation of different wavefield types are not required, and all wave types can be treated within a unified inversion scheme. However, FWI requires a reasonably good initial model, and the sensitivity of the misfit function with respect to the different wave types should be appropriately accounted for. This is the most essential step with onshore seismic data because the ground roll is much more energetic in comparison with the body waves. Our approach is based on a time-offset weighting function to balance the contribution of the different wave types in combination with a conventional frequency continuation approach. We first illustrate the feasibility of our approach on a 2D synthetic example representing a complex geology from south Oman. Then, we develop a 3D real data example from south Oman, where the application of our workflow till 8 Hz plays a pivotal role in retrieving a reliable model and in explaining the entire observed wavefields. In this example, the inversion of the ground roll helps improving the recovery of the shallow part of the earth, and hence better constraining the inversion of the body waves.

Wave-equation traveltime slope inversion by combining finite difference and cross-correlation methods

As an essential step in seismic inversion, velocity macromodel building provides a low-wavenumber background velocity model for seismic imaging and full waveform inversion. Defined as the first-order partial derivative of traveltime with regard to spatial coordinates, slope information has been directly or indirectly applied in ray-based geophysical inversion to retrieve models containing low and intermediate wavenumbers. In this study, to use slopes of locally coherent events in background velocity model building, we extend the slope inversion from ray theory to wave equation, which we name wave-equation traveltime slope inversion (WSI). Unlike traditional ray-based slope inversion, which relies on tedious picking of continuous horizons, we compute slope conveniently and robustly through cross-correlation and finite difference methods. Furthermore, we present the formulation of wave-equation traveltime slope inversion under the framework of wave-equation traveltime inversion. Traveltime and slopes are distinct data attributes that play different roles in reconstructing low-wavenumber background velocity models. Compared with the classic traveltime inversion, the wave-equation traveltime slope inversion is more sensitive to local velocity changes. Numerical examples demonstrate that the proposed method improves the horizontal resolution in velocity model building, which especially shows excellent potential in obtaining a higher lateral resolution of reconstruction for steeply dipping structures than traditional wave-equation traveltime inversion. What's more, this study makes the joint inversion of travel time and slope based on the wave equation possible, which can theoretically bring a higher resolution stabilized inversion.

Structure and Evolution of Northern Juan de Fuca Crust and Uppermost Mantle Over the Last 8 Ma From an Active‐Source Seismic Tomography Study

AbstractWe present results from a two‐dimensional wide‐angle controlled source seismic transect designed to characterize the velocity structure of the oceanic crust and uppermost mantle spanning the northern Juan de Fuca (JdF) plate from near Endeavor ridge to the Cascadia margin. Reflection and refraction travel time inversion is used to derive a tomographic Vp model of sediments, crust, and upper mantle. Velocity model results are compared to baseline reference Vp values for unaltered crustal and upper mantle rocks at temperatures assuming plate cooling. Effective medium theory is used to infer the degree of hydration of the crust and mantle. Results indicate a somewhat fractured and hydrated upper crust (≤2.5 wt% water), a near dry lower crust (≤0.7 wt%) and upper mantle (≤0.5 wt%) west of the deformation front, and an ∼75 km wide region of modestly lower velocity in the mid‐plate. Comparison with prior results from a complementary transect offshore Oregon indicates significant differences in Vp of the upper crust, with lower Vp‐inferred porosity along most of the Washington transects that may reflect different extents of fault‐related alteration and sediment burial histories. Approaching the deformation front, Washington transect Vp structure indicates dryer conditions than offshore Oregon, consistent with differences in extent of subduction bend faulting found in reflection imaging studies. On both transects, quasi‐abrupt changes in plate properties at ages of 8, 6, and 3.4/4 Ma are found. Distinct crustal accretion modes are recognized, aligning with changes in JdF plate motion and recent history of Cobb‐Eickelberg hotspot influence on crustal accretion at the JdF ridge.

Microearthquake location and uncertainty analysis using a Kirchhoff wavefront imaging method: A comparison with traveltime inversion and full wavefield imaging methods

The uncertainty and resolution of microearthquake location are an important topic for reservoir characterization and early warning of induced earthquakes. Many independent studies have either improved certain source location methods or applied a certain method to a data set without perhaps studying the full limitations compared with other methods. We have developed a P- and PS-wavefront imaging (WI) method to estimate the source origin time sequentially, which overcomes the unknown variable of source origin time in Kirchhoff-type imaging and helps to reduce the location uncertainties originating from the source origin time. We develop a 3D synthetic example by finite-difference modeling the realistic elastic 3C data using the SEG advanced modeling (SEAM) 4D earth model, and jointly compare the reservoir and basement microearthquake source location uncertainties based on traveltime inversion (TI), WI, and full wavefield imaging (FWIMG) methods. For each method, we also investigate the source location uncertainties between the P- and PS-wave results. Our results indicate that, using P waves and typical surface receiver arrays, TI has larger depth location uncertainties and cannot separately resolve the reservoir and basement events, whereas WI has larger horizontal uncertainties; FWIMG has the smallest horizontal location uncertainty, its depth uncertainty is similar to the WI method, and it is much smaller than the TI. Using PS waves can significantly reduce the location uncertainty compared with using only P waves for the three methods, and the full wavefield method has the smallest location uncertainty. The WI method has a moderate computation cost between TI and full wavefield methods. Data noise and velocity scaling errors change the source location uncertainties based on different imaging methods.

Influence of shear velocity on elastic full-waveform inversion: Gulf of Mexico case study using multicomponent ocean-bottom node data

Elastic full-waveform inversion (FWI) is superior to acoustic FWI due to its ability to simulate complex mode conversions in fast-varying elastic media. Using elastic FWI may become important when building velocity models in areas of large complex salt bodies that we typically see in the Gulf of Mexico. Accounting for elastic effects in FWI can reduce the artifacts that are caused by using an acoustic approximation. We often rely on petrophysics relations to define an initial shear velocity model, which also could be challenging. We demonstrate how to take advantage of the reflected converted waves from the top of the salt interface recorded in horizontal geophones to improve the estimation of the background shear velocity. Then, we illustrate the impact of the initial background shear velocity in the elastic inversion of the long-offset low-frequency hydrophone data. The workflow is based on a combination of wave-equation traveltime inversion, to cope with the cycle skipping, and FWI, to obtain higher-resolution results.

Reflection-based traveltime and waveform inversion with second-order optimization

Reflection-based inversion that aims to reconstruct the low-to-intermediate wavenumbers of the subsurface model, can be a complementary to refraction-data-driven full-waveform inversion (FWI), especially for the deep target area where diving waves cannot be acquired at the surface. Nevertheless, as a typical nonlinear inverse problem, reflection waveform inversion may easily suffer from the cycle-skipping issue and have a slow convergence rate, if gradient-based first-order optimization methods are used. To improve the accuracy and convergence rate, we introduce the Hessian operator into reflection traveltime inversion (RTI) and reflection waveform inversion (RWI) in the framework of second-order optimization. A practical two-stage workflow is proposed to build the velocity model, in which Gauss-Newton RTI is first applied to mitigate the cycle-skipping problem and then Gauss-Newton RWI is employed to enhance the model resolution. To make the Gauss-Newton iterations more efficiently and robustly for large-scale applications, we introduce proper preconditioning for the Hessian matrix and design appropriate strategies to reduce the computational costs. The example of a real dataset from East China Sea demonstrates that the cascaded Hessian-based RTI and RWI have good potential to improve velocity model building and seismic imaging, especially for the deep targets.

Reflection traveltime inversion with excitation approximation wavefields

Reflection traveltime inversion (RTI) plays an important role in the realm of exploration geophysics due to its ability to restore long-wavelength subsurface structures. However, due to the necessary migration/demigration process, every iteration of RTI requires six times as many forward calculations, resulting in high computational and storage costs. High-performance computing can accelerate RTI calculations, but it has little effect on the consumption of large storage volumes. Thus, the background and perturbed wavefields with excitation approximation are used in RTI to overcome the storage issue. In the authors’ RTI, the strategies of source-wavelet convolution and wavefield direction decomposition are introduced to solve the problems of missing source signature and multipathing in the excitation approximation wavefields. Numerical examples have demonstrated that excitation approximation RTI can provide an accurate background velocity model and reduce the storage burden of RTI.

Physically Constrained 2D Joint Inversion of Surface and Body Wave Tomography

Joint inversion of different geophysical methods is a powerful tool to overcome the limitations of individual inversions. Body wave tomography is used to obtain P-wave velocity models by inversion of P-wave travel times. Surface wave tomography is used to obtain S-wave velocity models through inversion of the dispersion curves data. Both methods have inherent limitations. We focus on the joint body and surface waves tomography inversion to reduce the limitations of each individual inversion. In our joint inversion scheme, the Poisson ratio was used as the link between P-wave and S-wave velocities, and the same geometry was imposed on the final velocity models. The joint inversion algorithm was applied to a 2D synthetic dataset and then to two 2D field datasets. We compare the obtained velocity models from individual inversions and the joint inversion. We show that the proposed joint inversion method not only produces superior velocity models but also generates physically more meaningful and accurate Poisson ratio models.

Tomographic Joint Inversion of Direct Arrivals, Primaries and Multiples for Monochannel Marine Surveys

Conventional multichannel surveys provide good images in 2D and 3D of the Earth in depth, which are successfully used for the oil and gas industries. However, their cost and environmental impact make them rarely affordable for engineering applications, especially for offshore infrastructures. In this case, monochannel systems, such as Boomers, having cables that are a few-meters long, provide time-domain images that are useful but miss relevant lithological information for engineers, such as the P-wave velocity of shallow layers. In this paper, we present a tomographic approach that exploits multiple reflections, in addition to primaries and direct arrivals, which work for monochannel surveys with a short offset. It can detect lateral variations of velocity and thickness of the first layer under the sea floor. Two complementary algorithms are compared: a pure tomographic inversion, and a tuning exploiting the classical Dix formula; the first one is more precise, while the second is more robust with respect to noise. A two-step inversion with incidence-angle parametrization performs slightly better than a single-step algorithm based on the direct traveltime inversion. We validate the method by synthetic and real data examples.

Inversion of velocity models using genetic algorithm method with sigmoidal parameterization

A seismic traveltime inversion method is proposed for building smooth velocity models using traveltime observed on irregular surface. Model parameterization in this study is described by a piecewise constant velocity field on a rectangular grid parameterized by sigmodal functions, which is beneficial for the description of irregular surface with high degree of approximation. The velocity field is defined in the rectangular grid which is used for the description of velocity distribution everywhere in the model sigmoidal interpolation. In addition, we use the simple Genetic Algorithm for the inversion procedure. Through this global scope inversion method, we provide high-resolution estimates of the model parameter and ensure that the results obtained are in accordance with the actual data. Our method is validated with synthetic examples of heterogeneous isotropic media and compared to Simulating Annealing. The inverted velocity models and approximate ray paths obtained coincide well with the trajectories simulated using the seismic ray tracing in synthetic heterogeneous isotropic media.

Processing the Artificial Edge-Effects for Finite-Difference Frequency-Domain in Viscoelastic Anisotropic Formations

Real sedimentary media can usually be characterized as transverse isotropy. To reveal wave propagation in the true models and improve the accuracy of migrations and evaluations, we investigated the algorithm of wavefield simulations in an anisotropic viscoelastic medium. The finite difference in the frequency domain (FDFD) has several advantages compared with that in the time domain, e.g., implementing multiple sources, multi-scaled inversion, and introducing attenuation. However, medium anisotropy will lead to the complexity of the wavefield in the calculation. The damping profile of the conventional absorption boundary is only defined in one single direction, which produces instability when the wavefields of strong anisotropy are reflected on that truncated boundary. We applied the multi-axis perfectly matched layer (M-PML) to the wavefield simulations in anisotropic viscoelastic media to overcome this issue, which defines the damping profiles along different axes. In the numerical examples, we simulated seismic wave propagation in three viscous anisotropic media and focused on the wave attenuation in the absorbing layers using time domain snapshots. The M-PML was more effective for wave absorption compared to the conventional perfectly matched layer (PML). In strongly anisotropic media, the PML became unstable, and prominent reflections appeared at truncated boundaries. In contrast, the M-PML remained stable and efficient in the same model. Finally, the modeling of the stratified cross-well model showed the applicability of this proposed algorithm to heterogeneous viscous anisotropic media. The numerical algorithm can analyze wave propagation in viscoelastic anisotropic media. It also provides a reliable forward operator for waveform inversion, wave equation travel-time inversion, and seismic migration in anisotropic viscoelastic media.

Characterizing shallow subsurface using 3D seismic while drilling with a downhole pilot

Seismic while drilling (SWD) can provide high-resolution subsurface information and characterize near-surface geology. We present a case study of SWD analysis using a data set from a desert environment acquired over a complex overburden. The data were acquired with a system composed of wireless surface geophones as well as top-drive and downhole sensors. The drill-bit noise data were reprocessed using a specialized workflow with two essential elements. First, a downhole pilot from a near-bit sensor was used for deconvolution, which led to improved data quality, particularly in the shallow subsurface. Second, nonlinear beamforming leveraged the 3D carpet of geophones to enhance signal quality and enable picking 3D traveltimes. A simple workflow for building a 1D velocity model used 3D traveltimes from an offset of 180 to 500 m. We vertically projected and averaged all 3D traveltimes to obtain a robust checkshot profile for the section from 190 to 1855 m. For the shallow subsurface (0–800 m), we further applied an advanced workflow with 3D traveltime inversion that more accurately handled mid- and far-offset data using a ray-tracing engine. More than 100,000 offset traveltime picks were inverted for a 1D velocity model. The model closely ties with the geology of the near surface, namely the formation tops associated with major impedance and lithologic contrasts. Amplitude signatures of 3D SWD gathers also correlate with the velocity model and lithologic changes, showing weak energy associated with soft formations and higher-energy first-arrival waveforms associated with compacted formations. Finally, we used the data extracted from a 2D line to reconstruct a migrated image of the back-propagated drill-bit sources. Joint use of kinematic and dynamic signatures helps characterize markers associated with loss circulation zones and target layers.

Coupled full-waveform inversion of horizontal borehole ground penetrating radar data to estimate soil hydraulic parameters: A synthetic study

Coupled inversion is a promising technique for determining soil hydraulic properties from time-lapse geophysical measurements. In this inversion approach, a hydrological model is coupled with ground penetrating radar (GPR) forward modelling to avoid interpretation errors from data processing. In this study, a workflow for coupled GPR full-waveform inversion (CFWI) is proposed that combines the benefits of coupled inversion and full-waveform inversion (FWI) to estimate soil hydraulic properties from time-lapse horizontal borehole GPR measurements. In particular, a synthetic modelling study is presented that compares the performance of coupled inversion of full waveforms and first arrival time data from zero-offset profile (ZOP) borehole measurements obtained during an infiltration event for estimating hydraulic parameters and the thickness of the first layer for a 2-layer soil profile. It was found that the thickness of the first layer could be more accurately estimated by CFWI because of the additional information contained in reflected and refracted waves from the air–soil layer boundary. Furthermore, the hydraulic parameters estimated by the coupled inversion of GPR travel times slightly deviated from true values and showed a relatively large uncertainty, whereas the results of CFWI precisely matched the known water retention and hydraulic conductivity functions. Despite these promising results, several challenges should be solved before CFWI can be applied to experimental GPR data. First, conducting CFWI needs accurate conceptual setups for the hydro(geo-)logical model. Furthermore, a robust approach should be developed to accurately estimate an effective source wavelet from the experimental ZOP data, and a more sophisticated hydrological modelling approach has to be considered to better estimate the distribution of soil electrical conductivity during the infiltration event. Finally, the accuracy and efficiency of current GPR modelling methods may need to be improved.

The Influence of Basement Terranes on Tectonic Deformation: Joint Earthquake Travel‐Time and Ambient Noise Tomography of the Southern South Island, New Zealand

AbstractDetermining how the crustal structure developed in previous tectonic regimes influences current deformation is important for understanding seismogenic behavior. Paleozoic‐Mesozoic convergent‐margin tectonics produced the southeastern South Island crust, which is currently involved in late Cenozoic transpressional collision. We examine crustal velocity structure through joint inversion of earthquake travel times and ambient noise derived group velocities to increase the resolution of Vp (P‐wave velocity) and Vp/Vs across the region. This method improves the details of the shallow velocity structure and highlights lithological properties, uplifted regions, and distributed fracture zones. The Otago schist shows thick lower crust while contrasting higher Vp below 15 km depth characterizes the Matai terrane and Median batholith, both backstops during accretion and deformation. The complex velocity structure, integrated with late Cenozoic faults, structural domains, seismicity patterns, and geodynamic modeling, shows how Cenozoic structures relate to deeper properties. Seismicity within the schist is distributed within transition regions rather than along specific faults, and these zones contain low Vp and low Qp (1/attenuation). The most prominent seismicity zone is along the transition from northern Otago ranges to the Southern Alps, where faulting and brittle deformation corresponds to the eastern edge of ductile crustal thickening above the bending of the strong oceanic lower crust. The thick weak crust rheology of Otago, relative to Canterbury, enables broad deformation, with numerous late Cenozoic faults that may not persist to great depth. Along the southern stronger plutonic terranes, there is a band of sparse deeper (15–35 km) seismicity, consistent with strong elastic brittle crust.

Downward continuation of marine seismic reflection data: an undervalued tool to improve velocity models

SUMMARY The purpose of marine seismic experiments is to provide information of the structure and physical properties of the subsurface. The P-wave velocity distribution is the most commonly modelled property, usually by inversion of arrival times or waveform attributes. In wide-angle seismic reflection/refraction (WAS) experiments, arrival times of seismic phases identified in data recorded by ocean bottom seismometers (OBS) are used to image relatively deep structures. Most WAS experiments have relatively low redundancy and produce robust velocity models of limited resolution. The shallow subsurface is also commonly studied with multichannel seismic (MCS) data recorded by towed streamers, a technique that is highly complementary to WAS. In this case, the recording of refractions as first arrivals is limited primarily by the streamer length and by features like water depth and the velocity structure and, in general, most refractions are masked by reflections and noise. However, MCS data of variable quality are available in many regions where no other data exist and previous work has shown that these data can also be used to retrieve velocity models through traveltime and full waveform inversion provided that first arrival information is properly extracted from the record sections. The most widely used tool to extract refractions as first arrivals from MCS recordings is the so-called downward continuation technique, which is designed for redatuming streamer field data to the seafloor. In this new virtual configuration, the early refractions transform to seismic phases that are becoming visible as first arrivals from nearly zero offset, facilitating their identification and use in traveltime tomography. However, there is limited literature, let alone available codes, to be used with the available MCS data sets. This work presents a user-friendly open source HPC software for redatuming 2-D streamer field data to the sea bottom for any seafloor relief. The main ingredient is the acoustic wave equation used backwards in time, allowing first the redatuming of the receivers and then the redatuming of the sources. Assessment tools are provided to evaluate the information available after redatuming for specific data acquisition configurations. Also, we present a step-by-step analysis that defines the most important features that influence the quality of the virtual, redatumed recordings.

Joint inversion of Rayleigh wave fundamental and higher order mode phase velocity dispersion curves using multi‐objective grey wolf optimization

AbstractRayleigh wave dispersion curves can be inverted to retrieve subsurface seismic velocity profiles. The inverse problem is ill‐posed, nonlinear and poorly conditioned, necessitating the application of global optimization methods. We present the application of the multi‐objective grey wolf optimization algorithm to perform joint inversion of the phase velocity dispersion curves corresponding to the fundamental and higher order modes of Rayleigh waves to obtain shear (S‐) and primary (P‐) wave velocity profiles. Multi‐objective grey wolf optimization is an extension of the grey wolf optimization algorithm for application to multi‐objective optimization and can be adapted to solve joint inversion problems. We compare the joint inversion results obtained from the multi‐objective grey wolf optimizer with those obtained from Markov chain Monte Carlo and fundamental mode inversion using the grey wolf optimizer on synthetic examples. The errors associated with phase velocity measurements are simulated by adding frequency‐dependent noise, with a higher level of noise added to the phase velocities corresponding to lower frequencies as compared to the higher frequencies. In the multimode joint inversion problem, the multi‐objective grey wolf optimizer gives a suite of solutions corresponding to each model parameter. The suite of S‐wave and P‐wave velocity profiles estimated from the multi‐objective grey wolf optimizer matches closely with the true model for the synthetic case studies even in the presence of noise. However, the suite of solutions has a greater spread for the last few layers, qualitatively indicating a higher degree of uncertainty in the predicted model parameter. The uncertainty in the solution for the deeper layers is a consequence of the uncertainty in the phase velocity at lower frequencies. We demonstrate the efficacy of the algorithm on recorded data from a shallow seismic survey conducted at the Indian Institute of Technology Bombay. The results from the multi‐objective grey wolf optimizer are in close agreement with those from Markov chain Monte Carlo, and the depth of investigation is found to be greater in comparison to results from refraction traveltime inversion.

Active ocean–continent transform margins: seismic investigation of the Cayman Trough-Swan Island ridge-transform intersection

SUMMARY The southern boundary of the Cayman Trough in the Caribbean is marked by the Swan Islands transform fault (SITF), which also represents the ocean–continent transition of the Honduras continental margin. This is one of the few places globally where a transform continental margin is currently active. The CAYSEIS experiment acquired an ∼165-km-long seismic refraction and gravity profile (P01) running across this transform margin, and along the ridge-axis of the Mid-Cayman Spreading Centre (MCSC) to the north. This profile reveals not only the crustal structure of an actively evolving transform continental margin, that juxtaposes Mesozoic-age continental crust to the south against zero-age ultraslow spread oceanic crust to the north, but also the nature of the crust and uppermost mantle beneath the ridge-transform intersection (RTI). The traveltimes of arrivals recorded by ocean-bottom seismographs (OBSs) deployed along-profile have been inverse and forward modelled, in combination with gravity modelling, to reveal an ∼25-km-thick continental crust that has been continuously thinned over a distance of ∼65 km to ∼10 km adjacent to the SITF, where it is juxtaposed against ∼3–4-km-thick oceanic crust. This thinning is primarily accommodated within the lower crust. Since Moho reflections are only sparsely observed, and, even then, only by a few OBSs located on the continental margin, the 7.5 km s–1 velocity contour is used as a proxy to locate the crust–mantle boundary along-profile. Along the MCSC, the crust–mantle boundary appears to be a transition zone, at least at the seismic wavelengths used for CAYSEIS data acquisition. Although the traveltime inversion only directly constrains the upper crust at the SITF, gravity modelling suggests that it is underlain by a higher density (>3000 kg m–3) region spanning the width (∼15 km) of its bathymetric expression, that may reflect a broad region of metasomatism, mantle hydration or melt-depleted lithospheric mantle. At the MCSC ridge-axis to the north, the oceanic crust appears to be forming in zones, where each zone is defined by the volume of its magma supply. The ridge tip adjacent to the SITF is currently in a magma rich phase of accretion. However, there is no evidence for melt leakage into the transform zone. The width and crustal structure of the SITF suggests its motion is currently predominantly orthogonal to spreading. Comparison to CAYSEIS Profile P04, located to the west and running across-margin and through 10 Ma MCSC oceanic crust, suggests that, at about this time, motion along the SITF had a left-lateral transtensional component, that accounts for its apparently broad seabed appearance westwards.

Data-Domain Traveltime Inversion of Reflected Waves Using Segment Dynamic Image Warping

Reflection traveltime information is generally used for producing a kinematically accurate velocity model for seismic imaging. Accurately estimating the traveltime difference between the demigrated and observed data is crucial for data-domain reflection traveltime tomography. To enhance the robustness of signal's alignment, we propose a new method of segment dynamic image warping (SDIW). It first exploits windowed polynomial fitting for signal processing and then aligns the signals based on point-wise segment-to-segment matching. Compared with the conventional point-to-point matching strategy, our method is more robust and insensitive toward strong random noise. By minimizing the traveltime difference computed by SDIW, data-domain reflection traveltime inversion (DRTI) is then used to find an accurate background velocity model. Synthetic tests show that SDIW provides reliable time shifts between the demigrated and observed data even if the signal-to-noise ratio of input data is rather low. This enables DRTI to automatically reconstruct the deep background velocity model. The subsequent full waveform inversion (FWI) gradually added short-wavelength velocity structures and finally recovers a high-resolution and high-fidelity model. The results demonstrate that the DRTI provides a kinematically accurate background velocity model sufficient for following FWI to fully retrieve the detail of the subsurface structures even when the low frequencies are missing.