Geophysical Journal International

SummaryFull-waveform inversion (FWI) of seismic data provides quantitative constraints on subsurface structures. Despite its widespread success, FWI of data around the critical angle is challenging because of the abrupt change in amplitude and phase at the critical angle and the complex waveforms, especially in the presence of a sharp velocity contrast, such as at the Moho transition zone (MTZ). Furthermore, the interference of refracted lower crustal (Pg) and upper mantle (Pn) arrivals with the critically reflected Moho (PmP) arrivals in crustal and mantle studies makes the application of conventional FWI based on linearized model updates difficult. To address such a complex relationship between the model and data, one should use an inversion method based on a Bayesian formulation.Here, we propose to use a Hamiltonian Monte Carlo (HMC) method for FWI of wide-angle seismic data. HMC is a non-linear inversion technique where model updates follow the Hamiltonian mechanics while using the gradient information present in the probability distribution, making it similar to iterative gradient techniques like FWI. It also involves procedures for generating distant models for sampling the posterior distribution, making it a Bayesian method. We test the performance and applicability of HMC based elastic FWI by inverting the non-linear part of the synthetic seismic data from a three-layer and a complex velocity model, followed by the inversion of wide-angle seismic data recorded by two ocean bottom seismometers (OBS’s) over a 70 Ma old oceanic crustal segment in the equatorial Atlantic Ocean. The inversion results from both synthetic and real data suggest that HMC based FWI is an appropriate method for inverting the non-linear part of seismic data for crustal studies.

SummaryThe effects of pore fluids on the elastic properties of sedimentary rocks can be broadly categorized into two mechanisms: variations in pore compressibility due to the physical properties of the fluids, and alterations in the stiffness of the rock frame resulting from rock-fluid interactions. Particularly, as rock-fluid interactions alter the stiffness of contacts between mineral grains, changes in the fluid properties around grain contacts can induce volumetric deformation of the rock as well as in variations of the associated elastic coefficients. Even though many previous studies have explored the influence of swelling of clay minerals, the relationships between changes in elastic moduli and deformation in rocks, which hardly contain swellable minerals, remain to date enigmatic. In this paper, to evaluate quantitatively these effects, drying rates, strains, and ultrasonic velocities of small cylindrical Berea sandstone samples were measured as their water saturation was decreased by evaporative drying. The measurements clearly showed drying shrinkage and drastic increases in shear and compressional moduli for all the samples under an almost fully dried condition. Previous studies considered that the alteration in surface energy of grain minerals between wet and dry states affected the contact stiffness between them. Some of them used micromechanical model, uniting Digby grain contact model with the effective medium theory, to interpret the changes in elastic moduli observed in the non-swellable sandstones during water adsorption on the grain surface. The conventional micromechanical model assumes that a mineral grain is a pure sphere and that the number of contacts between the grains is one. However, grains in a sedimentary rock are generally not purely spherical, and the contact surface is composed of several adhesive asperities. We therefore modified the conventional model by introducing the curvature radius and the number of asperities per contact surface. The modified model well reproduced the shear moduli under wet conditions using the strain and moduli measured under dry conditions. On the other hand, the predictions of the compressional moduli using the model were partially in agreement with the experimental results. Therefore, we attempted to qualitatively interpret the relationship by combining the model with the viscoelastic effect associated with wave-induced fluid flow. The deformation and changes in the elastic moduli of rocks resulting from multiple pore fluids within them can be better understood by the present combined model.

SummaryWe computed a 3-D shear wave velocity model of the Marmara Sea region from ambient noise tomography. The correlations of up to 8 years of vertical-component seismic recordings from 80 broad-band stations provided Rayleigh wave group velocity measurements in the period band 6–21 s at more than 1400 selected virtual source–receiver pairs. Rayleigh wave group velocity maps were used to derive a shear wave velocity model through simulated annealing inversion. The resulting crustal model provides coverage of the Marmara Sea along with its surrounding regional tectonic features. This allows for an investigation of the spatial extents of the Marmara Sea on a scale larger than that of basins.The low velocity structures of the Marmara Sea and the Thrace Basins are coeval to a depth of approximately 9 km. The crustal velocities beneath the Marmara Sea basins exhibit a low vertical gradient and smooth horizontal variations. The regional tectonic structures, such as Istranca Massif, Istanbul and Sakarya Zones, display sharp velocity contrasts with the lower-velocity crust beneath the Marmara Sea.The observed low crustal velocities, along with depth variations of the velocity isosurfaces (i.e., 3.4 km/s) indicate that the Marmara region is a structural depression much deeper and larger than the three basins of the North Marmara Trough. The North Anatolian Fault Zone is unlikely to be the primary factor contributing to the origin of this significant depression, as the basin's development appears to have occurred before the fault propagated into the region.

SummaryThe chronic exposure to particulate matter (PM) pollution causes societal and environmental issues, in particular in urban areas where most citizen are regularly exposed to vehicular traffic. Since almost two decades, environmental magnetic monitoring has demonstrated its efficiency to successfully map relative concentrations of airborne particle deposition on accumulative surfaces. A better understanding of the magnetic results requires discriminating the main traffic-related sources of the observed signal on particle collectors. To meet this objective, we investigated a sample set of exhaust and non-exhaust sources with respect to their magnetic fingerprints inferred from hysteresis loops, first order reversal curve (FORC) diagrams, temperature dependency of initial susceptibility, and unmixing of IRM acquisition curves. The source sample set comprises 14 diesel and gasoline exhaust smoke residues, 12 abrasive-fatigue wear test pieces from worn brake-pads, brake powders, worn tire-tread, and three resuspension products: asphalt concrete, street dust, and Saharan mineral dust deposited by precipitation after long-range eolian transport. Magnetic properties of the source samples were compared to those from various accumulative surfaces exposed to urban traffic (passive collectors, filters of facemasks for cycling, plant leaves, and tree barks). We found some fingerprints of exhaust pipes and brake wear products on these collectors. The findings highlight the relevance of environmental magnetism tools to characterize different traffic-related source signals in accumulative surfaces in urban environment.

SummaryIn distributed acoustic sensing (DAS), optical fibre is used as sensors, which enables us to observe strain over tens of kilometres at intervals of several metres. S-wave velocity (Vs) structures of shallow sediments of high resolution have been obtained from surface wave dispersion curves by applying seismic interferometry to DAS data both onshore and offshore. However, it is known that there is a disadvantage to DAS seismic interferometry. In addition to Rayleigh waves, Love waves are also included. Consequently, the accuracy of the estimated phase velocities for Rayleigh waves is reduced due to the contamination of Love waves. To address this shortcoming, we suggest a spatial autocorrelation (SPAC) method between DAS and the vertical component of seismometer data. The SPAC method is equivalent to seismic interferometry and is useful for obtaining phase velocity dispersion curves of surface waves from the cross-correlation functions (CCFs) between the records of two receivers. The CCFs obtained from a combination of DAS and vertical seismometer data should contain only Rayleigh waves because Love waves have no vertical component. CCFs between DAS and vertical seismometer data are therefore expected to give more accurate phase velocities of Rayleigh waves than CCFs with DAS data only. In this study, we first formulated analytical expressions of cross-spectra for DAS and three-component seismometer data because seismic observation is generally carried out using a three-component seismometer. A new SPAC method is presented in the form of analytical expressions. We showed that our formulation only includes Rayleigh and not Love waves in the cross-spectra with DAS and the vertical-component seismometer data. We applied our SPAC method to actual DAS and vertical seismometer data recorded on the seafloor. Then, we compared our new SPAC method for DAS and vertical seismometer data with a conventional SPAC method for only DAS data. The results reveal that our new SPAC method can estimate the phase velocities of Rayleigh waves more accurately than the conventional method. In addition, the analytical formulations of the cross-spectrum between DAS and three-component seismometer data, which we obtained in this study, are expected to be useful for the estimation of accurate three-dimensional structures in the future, although this is not available at the moment due to the lack of an applicable dataset.

SummaryMore accurate inversion of source fault geometry and slip parameters under the constraint of the Bayesian algorithm has become a research hotspot in the field of geodetic inversion in recent years. In nonlinear inversion, the determination of the weight ratio of the joint inversion of multi-source data is more complicated. In this context, this paper proposes a simple and easily generalized weighting method for inversion of source fault parameters by joint geodetic multi-source data under the Bayesian framework. This method determines the relative weight ratio of multi-source data by RMSE (Root Mean Square Error) value and can be extended to other nonlinear search algorithms.To verify the validity of the method in this paper, this paper first sets up four sets of simulated seismic experiment schemes. The inversion results show that the joint inversion weighting method proposed in this paper has a significant decrease in the large residual value compared with the equal weight joint inversion and the single data source joint inversion method. The east-west deformation RMSE is 0.1458 mm, the north-south deformation RMSE is 0.2119 mm, and the vertical deformation RMSE is 0.2756 mm. The RMSE of the three directions is lower than that of other schemes, indicating that the proposed method is suitable for the joint inversion of source parameters under Bayesian algorithm. To further verify the applicability of the proposed method in complex earthquakes, the source parameters of the Maduo earthquake were inverted using the method of this paper. The focal depth of the inversion results in this paper is closer to the focal depth released by the GCMT agency. In terms of strike angle and dip angle, the joint inversion in this paper is also more inclined to the GCMT results. The joint inversion results generally conform to the characteristics of left-lateral strike-slip, which shows the adaptability of this method in complex earthquakes.

SummaryThis work presents a model to characterize the behavior of waves propagating in non-isothermal poroelastic solids saturated by two-phase fluids. The dynamic differential equations include the poroelasticity and heat equations with the solid, fluid and thermal fields combined using coupling terms. A plane wave analysis shows that five waves can propagate, three compressional, one fast (P1) and two slow (P2, P3), a shear fast (S) and a thermal slow (T). P2, P3 and T are diffusive waves at low frequencies, while P1 and S behave as propagating waves. The T-wave is coupled with the compressional waves and uncoupled with the S-wave. The plane wave analysis applied to a real sandstone saturated with gas-water mixtures compares phase velocities and attenuation factors for two-phase and effective single-phase fluids, considering or neglecting the coupling terms. It is observed that P1 and P2 waves have higher velocities for coupled cases, while P3 and T-waves exhibit the opposite behavior. Furthermore the plane wave analysis is performed in the coupled case for oil-water and gas-water two-phase fluids, with compressional waves exhibiting higher velocities for gas-water than for oil-water mixtures. The propagation of waves in a 1D thermo-poroelastic medium saturated by a gas-water mixture is presented and analyzed using a Finite Element procedure. Considering temperature may become important in high-pressure high-temperature hydrocarbon and geothermal reservoirs.

SummaryThis study examines the feature space of seismic waveforms often used in machine learning applications for seismic event detection and classification problems. Our investigation centers on the southern Alaska region, where the seismic record captures diverse seismic activity, notably from the calving of marine-terminating glaciers and tectonic earthquakes along active plate boundaries. While the automated discrimination of earthquakes and glacier quakes is our nominal goal, this dataset provides an outstanding opportunity to explore the general feature space of regional seismic phases. That objective has applicability beyond ice quakes and our geographic region of study. We make a noteworthy discovery that features rooted in the spectral content of seismic waveforms consistently outperform statistical and temporal features. Spectral features demonstrate robust performance, exhibiting resilience to class imbalance while being minimally impacted by factors such as epicentral distance and signal-to-noise ratio. We also conduct experiments on the transferability of the model and find that transferability primarily depends on the appearance of the waveforms. Finally, we analyze misclassified events and find examples that are identified incorrectly in the original regional catalog.

SummarySubsurface temperature measurements play a crucial role, for instance, in optimizing geothermal power plants and monitoring heat-storage systems. Previous studies have demonstrated that time-lapse variations in temperature can be correlated with variations in seismic wave speeds, offering the potential for temperature monitoring via seismic surveys. However, an apparent discrepancy has emerged between field and laboratory experiments. Field studies predominantly report positive correlations between temperature and seismic wave speeds, while laboratory experiments often show anti-correlations. This inconsistency underscores the need for a more comprehensive, physics-based understanding of temperature-induced wave speed changes. In this study, we strive to bridge the gap between field and laboratory findings by examining several mechanisms governing temperature-induced seismic wave speed changes, namely the intrinsic temperature dependency of elastic parameters and thermally-induced elasticity. We present a physics-based modelling approach to identify the primary mechanisms responsible for temperature-induced seismic wave speed changes. By considering several end-member models, we find that intrinsic temperature dependency of elastic parameters (negative correlation) compete with thermal pressure effects (positive correlation). The precise initial and boundary conditions and physical parameters of the system under consideration will determine the weight of both effects. Temperature related dilatation does not seem to play an important role. We apply our approach to loosely consolidated sediments in the shallow subsurface of the Groningen region, where subsurface temperature fluctuations are driven by seasonal atmospheric temperature fluctuations roughly between −5 and 30 ○C. For these models, we predict seasonal temperature-induced changes in body wave speeds of up to 8% in the first few meters of the subsurface, high-frequency (above 2 Hz) surface wave phase velocity variations in the range of 1-2%, and relative changes in site amplification on the order of 4%. These findings contribute to a more comprehensive understanding of the intricate relationship between temperature and near-surface seismic properties, offering insights for applications as subsurface temperature monitoring systems.

SummaryIn this work, we revisit the seminal concept of Johnson-Koplik-Schwartz (JKS) length Λ, i.e. a characteristic length representing an effective pore size which controls various transport-related properties of porous media, such as, the permeability and the electrical conductivity. We present a novel closed-form equation that predicts the behavior of Λ in partially saturated media, for different saturation states. Using previous models in the literature that predict the intrinsic and relative electrical conductivities under partially saturated conditions, we infer the JKS length Λ and the electrical formation factor F as functions of water saturation and properties associated with the pore-size distribution of the probed porous medium. The proposed method permits to estimate the effective permeability and the relative permeability directly from electrical conductivity measurements, thus opening new-avenues for the remote characterization of partially saturated media. We believe that this new model will prove useful for various characterization and modeling applications from reservoir (CO2 or hydrogen storage) to vadose zone studies.

SummaryThe possibility of a transient rheological response to ice age loading, first discussed in the literature of the 1980s, has received renewed attention. Transient behavior across centennial to millennial time scales has been invoked to reconcile apparently contradictory inferences of steady state (Maxwell) viscosity based on two distinct data sets from Greenland: Holocene sea-level curves and GNSS-derived modern crustal uplift data. To revisit this issue, we first compute depth dependent Fréchet kernels using 1-D Maxwell viscoelastic Earth models and demonstrate that the mantle resolving power of the two Greenland data sets is highly distinct, reflecting the differing spatial scale of the associated surface loading: the sea-level records are sensitive to viscosity structure across the entire upper mantle while uplift rates associated with post-1000 CE fluctuations of the Greenland Ice Sheet have a dominant sensitivity to shallow asthenosphere viscosity. Guided by these results, we present forward models which demonstrate that a moderate low viscosity zone beneath the lithosphere in Maxwell Earth models provides a simple route to simultaneously reconciling both data sets by significantly increasing predictions of present-day uplift rates in Greenland whilst having negligible impact on predictions of Holocene relative sea-level curves from the region. Our analysis does not rule out the possibility of transient deformation, but it suggests that it is not required to simultaneously explain these two data sets. A definitive demonstration of transient behavior requires that one account for the resolving power of the datasets in modeling the GIA process.

SummarySeismic-wave scattering is observed, to variable degrees, on Earth, its moon, and Mars. Current scattering models and data processing typically rely on two end-member phenomena: weak single- or multiple-scattering events (ballistic) on the one hand, or intense scattering such that the wavefield retains no path information or bearing on its origin (diffuse).This study explores the existence of scattering behaviour intermediate between these end-members, as well as the properties of heterogeneous media that facilitate a transition between them. We apply multi-scale entropy and frequency-correlation analysis to seismic coda, and observe a distinct transitional behaviour is present within a part of the investigated parameter space. Analysis of terrestrial, lunar and Martian seismograms further demonstrate the applicability of these new methods across a wide range of scattering behaviours, while also highlighting their shortcomings. Results from the planetary data indicate partially non-diffuse behaviour and low complexity within specific bandwidths of lunar wavefields, potentially contradicting the current paradigm that lunar wavefields are diffuse, and require continued study. Further, Martian seismograms are shown to possess greater statistical entropy than lunar seismograms and diffuse energy properties, yet still display distinct phase arrivals, suggesting substantial scattering and transitional scattering behaviour on Mars. The robust, comparative nature of multi-scale entropy and frequency-correlation analysis, applied to idealised simulation as well as three separate planetary bodies, therefore provides a promising framework for future exploration of scattered wavefields across ballistic, transitional, and diffuse regimes, that complements existing methods.

SummarySeismic interferometry (SI) retrieves new seismic responses, e.g., reflections, between either receivers or sources. When SI is applied to a reflection survey with active sources and receivers at the surface, non-physical (ghost) reflections are retrieved as well. Ghost reflections, retrieved from the correlation of two primary reflections or multiples from two different depth levels, are only sensitive to the properties in the layer that cause them to appear in the result of SI, such as velocity, density, and thickness. We aim to use these ghost reflections for monitoring subsurface changes, to address challenges associated with detecting and isolating changes within the target layer in monitoring. We focus on the feasibility of monitoring pore-pressure changes in the Groningen gas field in the Netherlands using ghost reflections. To achieve this, we utilise numerical modelling to simulate scalar reflection data, deploying sources and receivers at the surface. To build up subsurface models for monitoring purposes, we perform an ultrasonic transmission laboratory experiment to measure S-wave velocities at different pore pressures. Applying SI by auto-correlation to the modelled datasets, we retrieve zero-offset ghost reflections. Using a correlation operator, we determine time differences between a baseline survey and monitoring surveys. To enhance the ability to detect small changes, we propose subsampling the ghost reflections before the correlation operator and using only virtual sources with a complete illumination of receivers. We demonstrate that the retrieved time differences between the ghost reflections exhibit variations corresponding to velocity changes inside the reservoir. This highlights the potential of ghost reflections as valuable indicators for monitoring even small changes. We also investigate the effect of the sources and receivers’ geometry and spacing and the number of virtual sources and receivers in retrieving ghost reflections with high interpretability resolution.

SummaryMaterial density remains poorly constrained in seismic imaging problems, yet knowledge of density would provide important insight into physical material properties for the interpretation of subsurface structures. We test ambient noise wavefield sensitivities to subsurface density contrasts through spatial and temporal wavefield gradients via Wave Equation Inversion (WEI), a form of seismic gradiometry. Synthetic results for 3D acoustic media suggest that it is possible to estimate relative density structure with WEI by using a full acoustic formulation for wave propagation and gradiometry. We show that imposing a constant density assumption on the medium can be detrimental to subsurface velocity images, whereas the full acoustic formulation assuming variable density improves our knowledge of both material properties. It allows us to estimate density as an additional material parameter, as well as to improve phase velocity estimates by accounting for approximations to the density structure. In 3D elastic media, severe approximations in the governing wave physics are necessary in order to invert for density using only an array of receivers on the free surface. It is then not straightforward to isolate the comparatively weak density signal from the influence of phase velocity using gradiometric WEI. However, by using receivers both at the surface and in the shallow subsurface we show that it is possible to estimate density using fully elastic volumetric WEI.

SummaryThe current crustal stress field is of key importance to understand geodynamic processes and to assess stability aspects during subsurface usage. To provide a 3D continuous description of the stress state, linear elastic forward geomechanical-numerical models are used. These models solve the equilibrium of forces between gravitational volume forces and surfaces forces imposed mainly by plate tectonics. The latter are responsible for the horizontal stress anisotropy and impose the inverse problem to estimate horizontal displacement boundary conditions that provide a fit best to horizontal stress magnitude data within the model volume. However, horizontal stress magnitude data have high uncertainties and they are sparse, clustered, and not necessarily representative for a larger rock volume. Even when Bayesian statistics are incorporated and additional stress information such as borehole failure observations or formation integrity test are used to further constrain the solution space, this approach may result in a low accuracy of the model results, i.e. the result is not correct. Here, we present an alternative approach that removes the dependence of the solution space based on stress magnitude data to avoid potential low accuracy. Initially, a solution space that contains all stress states that are physically reasonable is defined. Stress magnitude data and the additional stress information are then used in a Bayesian framework to evaluate which solutions are more likely than others. We first show and validate our approach with a generic truth model and then apply it to a case study of the Molasse foreland basin of the Alps in Southern Germany. The results show that the model's ability to predict a reliable stress state is increasing while the number of likely solutions may also increase, and that outlier of stress magnitude data can be identified. This alternative approach results in a substantial increase in computational speed as we perform most of the calculations analytically.

SummaryWe present a kinematic slip model and a simulation of the ensuing tsunami for the 2020 Mw 7.0 Néon Karlovásion (Samos, Eastern Aegean Sea) earthquake, generated from a joint inversion of high-rate GNSS, strong ground motion and InSAR data. From the inversion, we find that the source time function has a total duration of ∼20 s with three peaks at ∼4, 7.5 and 15 s corresponding to the development of three asperities. Most of the slip occurs at the west of the hypocenter and ends at the northwest down-dip edge. The peak slip is ∼3.3 m, and the inverted rake angles indicate predominantly normal faulting motion. Compared with previous studies, these slip patterns have essentially similar asperity location, rupture dimension and anti-correlation with aftershocks. Consistent with our study, most published papers show the source duration of ∼20 s with three episodes of increased moment releases. For the ensuing tsunami, the eight available gauge records indicate that the tsunami waves last ∼18-30 hours depending on location, and the response period of tsunami is ∼10-35 min. The initial waves in the observed records and synthetic simulations show good agreement, which indirectly validates the performance of the inverted slip model. However, the synthetic waveforms struggle to generate long-duration tsunami behavior in simulations. Our tests suggest that the resolution of the bathymetry may be a potential factor affecting the simulated tsunami duration and amplitude. It should be noted that the maximum wave height in the records may occur after the decay of synthetic wave amplitudes. This implies that the inability to model long-duration tsunamis could result in underestimation in future tsunami hazard assessments.

SummaryAmbient noise tomography is a well-established tomographic imaging technique but the effect that spatially variable noise sources have on the measurements remains challenging to account for. Full waveform ambient noise inversion has emerged recently as a promising solution but is computationally challenging since even distant noise sources can have an influence on the inter-station correlation functions and therefore requires a prohibitively large numerical domain, beyond that of the tomographic region of interest. We investigate a new strategy that allows us to reduce the simulation domain while still being able to account for distant contributions. To allow nearby numerical sources to account for distant true sources, we introduce correlated sources and generate a time-dependent effective source distribution at the boundary of a small region of interest that excites the correlation wavefield of a larger domain. In a series of 2D numerical simulations, we demonstrate that the proposed methodology with correlated sources is able to successfully represent a far-field source that is simultaneously present with nearby sources and the methodology also successfully results in a robustly estimated noise source distribution. Furthermore, we show how beamforming results can be used as prior information regarding the azimuthal variation of the ambient noise sources in helping determine the far-field noise distribution. These experiments provide insight into how to reduce the computational cost needed to perform full waveform ambient noise inversion, which is key to turning it into a viable tomographic technique. In addition, the presented experiments may help reduce source-induced bias in time-dependent monitoring applications.

SummarySeismic and electromagnetic explorations are two of the most successful geophysical applications for understanding the subsurface earth, and the joint interpretation of seismic and electromagnetic survey data can help to better characterize the rocks because they contain independent and complementary information about the rocks. However, the successfulness of the joint interpretation depends on the understanding of the correlations between the elastic and electrical rock properties and their influencing factors. Confining pressure is an important geological parameter that has been found to give rise to linear elastic-electrical correlations in sandstones. However, it is still poorly known about what controls the slopes of the pressure dependent linear correlations, even though slope is one of the most important parameter determining the linear correlation. We make artificial sandstones with controlled porosity and permeability, respectively, and measure their pressure dependent elastic (electrical resistivity) and electrical (P-wave velocity) properties simultaneously as well as porosity. We show that the slopes of the measured electrical resistivity versus P-wave velocity as an implicit function of confining pressure correlate positively with the compliant porosity in all the samples. The results not only reveal the petrophysical parameter that controls the slopes of the pressure dependent linear elastic-electrical correlations in sandstones, but also provide a basis for the discrimination of the slope-controlling parameter from the simultaneously measured elastic and electrical properties.

SummaryEarthquake hypocenters are routinely obtained by a common inversion problem of P- and S-phase arrivals observed on a seismological network. Improving our understanding of the uncertainties associated with the hypocentral parameters is crucial for reliable seismological analysis, understanding of tectonic processes, and assessing seismic hazards. However, current methods often overlook uncertainties in velocity models and variable trade-offs during inversion. Here, we propose to unravel the effects of the main sources of uncertainty in the location process using techniques derived from the framework of global sensitivity analysis. These techniques provide a quantification of the effects of selected variables on the variance of the earthquake location using an iterative model that challenges the inversion scheme. Specifically, we consider the main and combined effects of (1) variable network geometry, (2) the presence of errors in analyst observations and (3) errors in velocity parameters from a 1D velocity model. These multiple sources of uncertainty are described by a dozen of random variables in our model. Using a Monte Carlo sampling approach, we explore the model configurations and analyze the differences between the initial reference location and 100,000 resulting hypocentral locations. The GSA approach using Sobol's variance decomposition allows us to quantify the relative importance of our choice of variables. It highlights the critical importance of the velocity model approximation and provides a new, objective and quantitative insight into understanding the sources of uncertainty in the inversion process.

SummaryThe Gulf of Guinea exhibits a continuous emission of narrow-band and long-period signals (16, 26, and 27 seconds) on teleseismic records, yet the underlying excitation mechanism remains unclear. This study establishes a connection between these tremors and the vibration of thin, decoupled crustal plates at unexplored volcanoes in the gulf. We first formulate the damped plate oscillation equation, by incorporating the vibration of the thin surface crustal plate and magma flow in the subsurface sill. The findings reveal that a fundamental-mode vibration with a period of several dozen seconds can be induced by a crustal plate that is less than 1.0 km thick but extends over tens of kilometers in both length and width, given a subsurface sill depth exceeding 10.0 cm. The thin plate hypothesis also allows for excitation of a few overtone modes, but such waves in higher frequencies diminish over long distances, leaving only the monotonous fundamental-mode vibration at teleseismic stations. The long duration of Guinea tremors at each recurrence is attributed to the presence of low viscosity basaltic magma, which influences the damping factor. Direct wave loads at the shallow gulf serve as the primary vibration source, accounting for seasonal variations and recurring patterns. Sporadic energy bursts may also occur due to large storms. Radiation patterns of Guinea tremors are linked to the geometric structure of the thin plate. Our theoretical estimates of tremor spectra closely align with observed data, confirming the model’s accuracy in capturing reported Guinea tremor characteristics. This study provides valuable insights into the origins of VLP tremors at continental volcanoes.