Geophysical Journal International

SummaryOn March 18, 2021 an earthquake of magnitude Mw=6.0 occurred offshore the Algerian coasts and generated a tsunami with offshore amplitudes smaller than a few millimetres crossing the western Mediterranean Sea. The objective of this study is threefold: first, to determine whether seismic sources calculated in the context of tsunami early warning are relevant; second, to determine whether tsunami simulations are able to reproduce tide-gauge observations; and third, to define the sensitivity of simulations to the grid resolutions and tsunami parameters.In the Mediterranean Sea, a very small number of available coastal tide gauges recorded the tsunami. Among them, a few French tide gauge stations recorded water waves with amplitudes smaller than a few centimetres and with periods ranging from five to twenty minutes associated to harbour or bay resonances.Numerical simulations of the tsunami are performed by the operational code Taitoko for seven different source fault models. Three of them allow for a rapid source detection and characterization in the framework of tsunami warning at CENALT (Centre National d'Alerte aux Tsunamis, France). The integrated code Taitoko uses a system of multiple nested grids. Standard Boussinesq equations are solved in the Mediterranean grid, whereas nonlinear shallow water equations are solved in coastal and harbour grids with 25 and 5 m resolutions, respectively. Whatever the fault model, the observed time series of water heights are reproduced satisfactorily both in phase and amplitude by the model at Nice and Monaco but poorly at Port Mahon (Minorca) and Toulon.

SummaryDistributed acoustic sensing (DAS) is a relatively new technology for recording the propagation of seismic waves, with promising applications in both engineering and geophysics. DAS's ability to simultaneously collect high spatial resolution waveforms over long arrays suggests that it is well-suited for near-surface imaging applications such as 2D MASW (multichannel analysis of surface waves), which require, at a minimum, long, linear arrays of single-component receivers. The 2D MASW method uses a large number of sensor sub-arrays deployed along a linear alignment to produce 1D shear-wave velocity (VS) profiles beneath each sub-array. The 1D VS profiles are then combined to form a pseudo-2D VS image beneath the entire linear alignment that can be used for the purpose of identifying and characterizing lateral variations in subsurface layering. Traditionally, 2D MASW is conducted using arrays consisting of either 24 or 48 geophones. While additional receivers could easily be incorporated into the testing configuration, it is rare for researchers and practitioners to have access to greater numbers of seismographs and geophones. When a limited number of geophones are available for deployment, there is a need to pre-determine the geophone spacing and sub-array length prior to field data acquisition. Studies examining how the choice of sub-array geometry impacts the resulting pseudo-2D VS cross-sections have been largely limited to synthetic data. In response, this study utilizes DAS data to examine the effects of using various sub-array lengths by comparing pseudo-2D VS cross-sections derived from active-source waveforms collected at a well-characterized field site. DAS is particularly useful for 2D MASW applications because the sub-array geometry does not need to be determined prior to field data acquisition. We organize the DAS waveforms into multiple sets of overlapping MASW sub-arrays of differing lengths, ranging from 11 m to 47 m, along the same alignment, allowing for direct comparison of the derived pseudo-2D VS results at the site. We show that the length of the individual MASW sub-arrays has a significant effect on the resulting VS cross-sections, including the resolved location of a strong impedance contrasts at our study site, and evaluate the results relative to ground truth from invasive testing. Our results suggest that the choice of sub-array length is important and should be carefully chosen to meet project-specific goals. Furthermore, analysts may consider using multiple sub-array geometries during the data processing stage, as is made possible by DAS, to properly evaluate the uncertainty of 2D MASW results. This study demonstrates the potential of using DAS to collect data for 2D MASW in a manner that is efficient and flexible, and can be easily scaled up for use with very long arrays.

SummaryNatural fractures play a significant role in oil and gas reservoirs. Accurate predictions of fracture parameters are vital in reservoir prediction and oil and gas development. The birefringent phenomenon of shear waves in fractured media makes shear wave splitting (SWS) analysis an important tool in formulating fracture predictions. The traditional SWS analysis method is based on an orthogonal assumption of fast and slow shear waves. However, in an orthotropic medium composed of a background vertical transversely isotropic medium and a set of vertical fractures, fast and slow shear waves are not necessarily orthogonal. This causes the traditional SWS analysis method to fail. To solve this problem, we proposed an SWS analysis algorithm with a non-orthogonal assumption of fast and slow shear waves in this study. First, we introduced a parameter (difference angle) to characterise the angle between slow shear waves and the normal polarisation directions of the fast shear waves. Subsequently, based on the traditional two-parameter scanning algorithm, a parameter was added to facilitate three-parameter scanning. In addition, we derived an expression for the two-parameter scanning objective function using the non-orthogonal assumption. Two-parameter scanning can accurately extract fast and slow wave time delay data, but it cannot determine an accurate fast shear wave polarisation direction. Therefore, we optimised the three-parameter scanning algorithm as follows: first, we used two-parameter scanning to obtain the fast and slow wave time delays and then performed further scanning to determine the polarisation direction of the fast shear wave and difference angle. The optimisation algorithm significantly improved the computational efficiency. Subsequently, we tested the accuracy of this method using synthetic single-trace and three-component vertical seismic profile data. We demonstrated the implementation process of the three-parameter scanning method using actual data, separated fast and slow shear waves, and predicted fracture parameters. The final fracture parameters were verified.

SummaryAlthough ambient noise interferometry has been extensively utilized for seismic velocity tomography, its application in retrieving attenuation remains limited. This study presents a comprehensive workflow for extracting Rayleigh wave amplitude and attenuation from ambient noise, which consists of three phases: (1) retrieval of empirical Green's Functions (EGFs), (2) selection and correction of amplitude measurements, and (3) inversion of attenuation, site amplification, and noise intensity terms. Throughout these processes, an ‘asynchronous’ temporal flattening method is employed to generate high-quality EGFs while preserving relative amplitudes between stations. Additionally, a novel “t-symmetry” criterion is proposed for data selection along with the signal-to-noise ratio. Furthermore, 2-D sensitivity kernels are utilized to estimate the focusing/defocusing effect, which is then corrected in amplitude measurements. These procedures are designed to deliver reliable attenuation measurements while maintaining flexibility and automation. To validate the effectiveness of the proposed noise-based attenuation tomography approach, we apply it to a linear array, NCISP-6, located in NE China. The obtained results correlate reasonably well with known geological structures. Specifically, at short periods, high attenuation anomalies delineate the location of major sedimentary basins and faults; while at longer periods, a notable rapid increase of attenuation is observed beneath the Moho discontinuity. Given that attenuation measurements are more sensitive to porosity, defect concentration, temperature, melt, and volatile ratio than seismic velocities, noise-based attenuation tomography provides important additional constraints for exploring the crustal and upper mantle structures.

SummaryThe Grüneisen parameter is an important parameter for the thermal state and evolution of the core, but its uncertainties and their implications are sometimes overlooked . Several formalisms using different parameters values have been used in different studies, making comparison between studies difficult. In this paper, we use previously published datasets to test the sensitivity of modeling the thermal state of the early core to the different formalisms and parameter values used to describe the evolution of the Grüneisen parameter with density. The temperature of the core obtained in our models is less sensitive to the uncertainties of the parameters used in Al'Tshuler et al. (1987) formalism than the uncertainties of the parameters used in Anderson (1967) formalism.

SummaryThe northern Chile Triple Junction (CTJ) is characterized by the ongoing subduction of the Nazca plate beneath the South American plate. The geological structures within the subduction zone undergo complex changes, resulting in significant tectonic activities and intense seismicity along the western margin of South America. Based on the Gravity Recovery and Climate Experiment (GRACE) data and earthquake catalogues, this study selects the northern CTJ area (25°S-40°S, 75°W-65°W) as the research object, adopts the mathematical methods of Independent Component Analysis (ICA) and Principal Component Analysis (PCA) to separate the earthquake-related signals within the GRACE data, and fits the changes of seismic b-values through the frequency-magnitude relationship. The characteristics of gravity changes before and after seismic events, the seismic activity parameter b-values, and the relationship between the gravity signals and b-values are discussed. The results show that mathematical methods can effectively extract seismic-related gravity components from the GRACE data. ICA, compared to PCA, provides better results in capturing the temporal variations associated with b-value time series, which exhibit good consistency in long-term trend changes. The average change of b-values in the study area is 0.66 ± 0.003, fluctuating over time. Generally, prior to larger seismic events, b-values tend to decrease. Along the western margin of South America, b-values are low; this aligns with the active tectonic activities between subducting plates. Additionally, a certain correlation between b-values and gravity changes is observed, but due to the influence of tectonic activities, the correspondence between b-values and gravity anomalies may not be consistent across different areas. The b-value is highly consistent with the strain rate model. Low b-values correspond to high strain rates along the western edge of South America, which is in line with the tectonic characteristics of frequent seismic activity in this area. A gradual concentration of gravity anomalies before major earthquakes is observed, accompanied by the gradual accumulation of smaller seismic events. Meanwhile, several months before the two major earthquakes, the spatial distribution of gravity appears to be similar to the co-seismic signals, but the nature of its generation remains to be explored. These methods and results not only add to the applications of GRACE in seismic studies but also raise questions for further exploration.

SummaryWe propose a new method to obtain 3-D shear wave velocity structures for regions with undulating topography based on surface-wave dispersion data. In our method, we assume that surface waves propagate along a curved free surface, and the dispersion effects of these waves can be modeled as a frequency-dependent ray-tracing problem. We use the shortest path method (SPM) to address off-great-circle propagation arising from inhomogeneous elastic parameters and topographic variations. We then apply our method to both synthetic and real data inversions and demonstrate that ignoring topographic effects may significantly distort the inverted images. Finally, we analyzed the accuracy of our method and provided a rule-of-thumb principle to quantitatively assess the need to account for topographic effects in surface-wave tomography for a region.

SummaryA Bayesian linear regression to determine the bias in the Nafe-Drake relationship between compressional velocity and density provides an improved model for the density structure of Kīlauea volcano, Hawaiʻi. In previous work, we combined the results of seismic tomography with the Nafe-Drake relationship between compressional velocity and density to explain the large values of gravity disturbances overlying the summits and rift zones of the island's volcanoes. These results were used to determine mechanisms for gravitational instability of the island flanks. Here we use laboratory measurements of the relationship of velocity and density for a wide range of Hawaiʻi island rocks as a prior in a Bayesian regression, with seismic tomography, to refine the 3D density structure for Kīlauea volcano. This refined structure shows dense bodies (3220 kg/m3) between 5 and 8 km below sea level that underly regions of magma storage, found from geodetic and geophysical studies, beneath the summit and East Rift Zone of Kīlauea volcano. Above these bodies, density iso-surfaces surround and cradle sources of pressure change determined from geodetic models, both at the summit and along the East Rift Zone. Continued subsidence of the summit following the 2018 eruption is aligned with a bowl-shaped density structure, formed primarily by density isosurfaces between 2800 and 2900 kg/m3 at 4 to 6 km depth. These surfaces underly the ∼3 km depth at which dike injection initiates, are largely aseismic, and from their density values are inferred to contain high concentrations of olivine. Taken together, these density structures are consistent with an olivine-rich mush with variable porosity that increases in density with depth and provides a mechanism to form olivine cumulates both at the summit and along the rift zones. This structural framework for Kīlauea volcano is consistent with melt and mush transport occurring over a large range of depths to accommodate the growth and spreading of the volcano.

SummaryFull waveform inversion has emerged as the state-of-the art high resolution seismic imaging technique, both in seismology for global and regional scale imaging and in the industry for exploration purposes. While gaining in popularity, full waveform inversion, at an operational level, remains a heavy computational process involving the repeated solution of large-scale 3D wave propagation problems. For this reason it is a common practice to focus the interpretation of the results on the final estimated model. This is forgetting full waveform inversion is an ill-posed inverse problem in a high dimensional space for which the solution is intrinsically non-unique. This is the reason why being able to qualify and quantify the uncertainty attached to a model estimated by full waveform inversion is key. To this end, we propose to extend at an operational level the concepts introduced in a previous study related to the coupling between ensemble Kalman filters and full waveform inversion. These concepts had been developed for 2D frequency-domain full waveform inversion. We extend it here to the case of 3D time-domain full waveform inversion, relying on a source subsampling strategy to assimilate progressively the data within the Kalman filter. We apply our strategy to an ocean bottom cable field dataset from the North Sea to illustrate its feasibility. We explore the convergence of the filter in terms of number of elements, and extract variance and covariance information showing which part of the model are well constrained and which are not. Analyzing the variance helps to gain insight on how well the final estimated model is constrained by the whole full waveform inversion workflow. The variance maps appears as the superposition of a smooth trend related to the geometrical spreading and a high resolution trend related to reflectors. Mapping lines of the covariance (or correlation matrix) to the model space helps to gain insight on the local resolution. Through a wave propagation analysis, we are also able to relate variance peaks in the model space to variance peaks in the data space. Compared to other posterior-covariance approximation scheme, our combination between Ensemble Kalman filter and full waveform inversion is intrinsically scalable, making it a good candidate for exploiting the recent exascale high performance computing machines.

SummaryIn petrophysics, physical rock properties are typically established through laboratory measurements of individual samples. These measurements predominantly relate to the specific sample and can be challenging to associate with the rock as a whole since the physical attributes are heavily reliant on the microstructure, which can vary significantly in different areas. Thus, the obtained values have limited applicability to the entirety of the original rock mass. To examine the dependence of petrophysical measurements based on the variable microstructure, we generate sets of random 2D microstructure representations for a sample, taking into account macroscopic parameters such as porosity and mean grain size. For each microstructure produced, we assess the electrical conductivity and evaluate how it is dependent on the microstructure’s variability. The developed workflow including microstructure modelling, finite element simulation of electrical conductivity as well as statistical and petrophysical evaluation of the results is presented. We show that the methodology can adequately mimic the physical behaviour of real rocks, showing consistent emulation of the dependence of electrical conductivity on connected porosity according to Archie’s law across different types of pore space (micro-fracture, inter-granular, and vuggy, oomoldic pore space). Furthermore, properties such as the internal surface area and its fractal dimension as well as the electrical tortuosity are accessible for the random microstructures and show reasonable behaviour. Finally, the possibilities, challenges and meshing strategies for extending the methodology to 3D microstructures are discussed.

SummaryThe reduction of effective normal stress during earthquake slip due to thermal pressurization of fault zone pore fluids is a significant fault weakening mechanism. Explicit incorporation of this process into frictional fault models involves solving the diffusion equations for fluid pressure and temperature outside the fault at each time step, which significantly increases the computational complexity. Here, we propose a proxy for thermal pressurization implemented through a modification of the rate-and-state friction law. This approach is designed to emulate the fault weakening and the relationship between breakdown energy and slip resulting from thermal pressurization and is appropriate for fully-dynamic simulations of multiple earthquake cycles. It preserves the computational efficiency of conventional rate-and-state friction models, which in turn can enable systematic studies to advance our understanding of the effects of fault weakening on earthquake mechanics. In 2.5D simulations of pulse-like ruptures on faults with finite seismogenic width, based on our thermal pressurization proxy, we find that the spatial distribution of slip velocity near the rupture front is consistent with the conventional square-root singularity, despite continued slip-weakening within the pulse, once the rupture has propagated a distance larger than the rupture width. An unconventional singularity appears only at shorter rupture distances. We further derive and verify numerically a theoretical estimate of the breakdown energy dissipated by our implementation of thermal pressurization. These results support the use of fracture mechanics theory to understand the propagation and arrest of very large earthquakes.

SummaryThe Alaska-Aleutian subduction zone represents an ideal location to study dynamics within a mantle wedge. The subduction system spans several thousand kilometers, is characterized by a slab edge, and has ample seismicity. Additionally, the majority of islands along the arc house broadband seismic instruments. We examine shear wave splitting of local-S phases originating along the length of the subduction zone. We have dense measurement spacing in two regions, the central Aleutians and beneath Alaska. Beneath Alaska, we observe a rotation in fast splitting directions near the edge of the subducting slab. Fast directions change from roughly trench perpendicular away from the slab edge to trench parallel near the boundary. This is indicative of toroidal flow around the edge of the subducting Alaska slab. In the central Aleutians, local-S splitting is primarily oriented parallel to, or oblique to, the strike of the trench. The local-S measurements, however, exhibit a depth dependence where deeper events show more consistently trench parallel directions indicating prevalent trench parallel mantle flow. Our local-S shear wave splitting results suggest trench parallel orientation are likely present along much of the subduction zone excited by the slab edge, but that additional complexities exist along strike.

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.