Geophysical Journal International

SummaryModelling and inversion of controlled-source electromagnetic data requires elaborate numerical tools. The major challenge is the high computational cost of computing solutions to numerous forward problems (for the forward responses as well as the sensitivity matrix). Forward modelling is accomplished using either a direct or an iterative solver. Current modelling suites predominantly employ direct solution methods in the forward operator since multiple solutions are easily accessible using inexpensive and quick forward-backward substitution after an initial resource-demanding matrix factorisation step. Iterative techniques, on the other hand, require little resources for single forward solutions, and are yet very time consuming if solutions for many right-hand sides are to be computed. Evaluations of different solution techniques for modelling and inverse problems are only sparsely investigated. In light of this, we integrated an iterative solver as alternative in the forward and and inversion operators of the open-source software custEM and pyGIMLi. In particular, we implemented a two-level iterative scheme where the outer solver employs a generalised conjugate residual algorithm preconditioned with a highly efficient block-based preconditioner for square blocks. The inner-level solver is either of the same type as the outer solver, but preconditioned with the auxiliary-space Maxwell preconditioner, or may alternatively be a direct solver. In this paper, we evaluate the described iterative forward operator for forward modelling tasks for the Marlim R3D model for a single as well as numerous right-hand side vectors and compare the performance to the direct solver MUMPS. We further investigate the solver’s applicability on small and medium-sized computing platforms. We then examine the iterative solver for inversions of synthetic land-based and semi-airborne data in terms of computational requirements. Our results demonstrate that forward modelling tasks are best performed using an iterative approach for single source problems. Moreover, simulations of large and complex problems are accessible on even on small computing platforms such as laptops in very reasonable time. For inversions, the iterative forward operator, in particular the mixed iterative-direct-based one, performs equally well in terms of time as the direct one while reducing the memory demands for the computations of the forward responses and the data sensitivities.

SummaryIn a region of complex geology, we examine the influence of spatial resolution of conductivity models on Geomagnetically Induced Currents (GICs) estimations. We focus on the southern region of Portugal mainland, for which magnetotelluric (MT) sounding measurements have been obtained with lower noise from human activity. Using two conductivity models inverted from sets of MT soundings with different sampling distance, we look for an interpretation of the differences in GIC estimations at substation grounding resistances. We make use of two different proxies, the Local Effective Field (LEF) and the Regional Electromotive Source (RES), built from the electric induced field at each substation site and the sum of electromotive forces along all transmission lines connected to that substation, respectively. We compare different time signals associated to GICs using a parameter that combines Pearson correlation and linear regression slope, the Correlation Regression Coefficient (CRC). Our main conclusion is that spatially detailed information on lateral heterogeneities of the conductivity associated to complex geology is crucial for a rigorous assessment of GIC hazard, leading to relative differences in GIC standard deviation and in GIC peak values that can amount to more than 100% in certain cases. Additionally, using LEF and RES, we emphasise the non-locality of GIC drivers and bring new input concerning the choice of proxies used to monitor and forecast this kind of hazard.

SummaryThe Scandinavian Peninsula and its vicinity comprise highly tectonically diverse blocks, including the Baltic Shield, the continental margin, and the North Sea Basin. The crustal rheology is a critical constraint to understanding the tectonic evolution in this region. Based on 19 416 Lg waveforms from 233 earthquakes and 560 broadband digital stations, using an inversion method combining both single- and two-station ray paths, we constructed a broadband (0.05 and 10.0 Hz) Lg wave attenuation model in the study region, with the resolution approaches to 110 km (∼1°) or higher in areas with dense ray path coverages. The QLg distributions correlate well with regional geological features. The Baltic Shield exhibits the highest QLg, consistent with its thick Precambrian crust and high rheological rigidity developed through Archean Svecofennian orogeny. In contrast, passive margins with crustal thinning, magmatic modification, and thick sedimentary sequences exhibit strong attenuation, reflecting a reduction in rheological strength resulting from interactions with mantle plumes and extensional tectonics. The North Sea Basin exhibits the lowest QLg values and the presence of hydrocarbon-bearing sediments. The extremely high QLg distribution reveals the ancient cratonic core of the Baltic Shield, particularly in areas where the surface rock dating sample cannot be collected due to seawater coverage.

SummaryWe analysed infrasound waves associated with the Gyeongju earthquake (ML 5.8) that occurred on September 12, 2016, in the southeastern Korean Peninsula. For infrasound wave detection, the Progressive Multi-channel Correlation method was applied to the infrasound dataset recorded at 7 arrays operating in South Korea at epicentral distances ranging from 178 to 472 km. Based on the back-projection method constrained by array-dependent celerity and azimuth deviation models, the source regions were identified in both the epicentral and nonepicentral regions. Remarkably, the nonepicentral secondary sources of this earthquake were located in regions with shallow water depths: i) the western coastal area in the Yellow Sea and ii) the shallow ocean basin and bank in the East Sea. The location results obtained from the earthquake could be corroborated through its foreshock (ML 5.1), yielding location results consistent with those of the mainshock. The generation of infrasound waves over shallow water depths was fortuitously validated by direct recordings of dominant single-frequency (∼0.3 Hz) infrasound waves at close range via temporary sensors near the ocean basin and bank. We interpreted that low-frequency infrasound signals could be generated from interactions among the ocean floor, shallow seawater, and atmosphere. We performed numerical simulations of seismoacoustic fields to predict ground motions on the seafloor and acoustic transmission efficiency between the water and air interface. The simulations quantified the energy transfer through different media and clarified our observational results. We found that because this solid Earth‒water‒atmosphere coupled air wave has a relatively low frequency (∼0.3 Hz), it can survive propagation over long distances compared with high-frequency infrasound waves generated in inland and mountain regions. In this study, we extend our understanding of water‒atmosphere coupling and the monitoring framework for earthquake-associated nonepicentral infrasound waves, encompassing not only inland ground shaking but also shallow sea regions located far from the epicentre.

SUMMARYIn recent years, machine learning (ML) techniques have emerged as a powerful tool in seismology, enabling the detection of small-magnitude seismic events that typically go unnoticed by traditional methods. Here, we apply ML-based methods to improve the characterization of normal fault systems and aftershock activity in the Central Apennines, using data from the 2009 L'Aquila seismic sequence. By processing data from both permanent and temporary seismic stations, we identified approximately 191 000 events—with a local magnitude range of -1.83 and 5.96, recorded during January-December 2009—nearly ten times more than the standard catalog maintained by INGV. These events were relocated using a combination of absolute and relative location techniques, resulting in a high-resolution catalog of 148 000 earthquakes. This catalog is distinguished by an increased number of S-wave pickings, which significantly reduces localization errors and enhances the accuracy of fault geometry reconstruction. Compared to an existing semi-automatic catalog, we observe a full recovery of seismic events, and a significant improvement of new events identified and well-located by the ML-approach, with a marked increase in the quality and quantity of P- and S-wave arrivals. The refined seismic catalog not only provides a more detailed and accurate definition of the fault architecture but also offers new insights into the distribution of aftershocks, unrolling the complex pattern of faulting that normally remains masked during standard analyses. This work highlights the potential of ML methods in advancing our understanding of complex fault systems and seismic sequences.

AbstractProgressively denser mapping of ocean-floor magnetization has led to detailed reconstructions of past plate motions in the Cenozoic. These reconstructions often reveal rapid kinematic changes that provide crucial information for identifying geodynamic mechanisms that may have caused them, and for quantifying force budgets upon plates. In parallel to these advances, the notion of thin, low-viscosity asthenosphere beneath tectonic plates that facilitates their motions has emerged and consolidated. This weak, mobile layer promotes the formation of the pressure-driven Poiseuille flow that, in turn, generates basal shearing upon plates. In addition, it can be linked to dynamic topography variations due to pulsing plume activity. In this study, we use publicly available finite-rotation compilations of the North American plate (NA) to investigate its kinematic history since Oligocene time. After removing data that are possibly impacted by significant noise, we find that NA experienced a westward speedup near 27 Ma. Next, we explore the role that asthenospheric Poiseuille-type flow caused by increased Canary plume activity may have had in generating this kinematic change. Such plume activity is inferred from the combination of anomalously shallow residual bathymetry and records of past ocean-floor magmatism offshore northwestern Africa. We compare estimates of torque variation upon NA that are (i) required to explain the reconstructed kinematic change, and (ii) predicted by the Poiseuille-type flow associated with the Canary plume activity. Our results indicate that these two torque-variations estimates are in agreement with each other, both in terms of direction and magnitude. This inference suggests that the increased Canary plume activity is a geodynamically-plausible process to explain the Oligocene plate-motion change of NA.

SummarySeismic traveltime tomography represents a popular and useful tool for unravelling the structure of the subsurface across the scales. In this work we address the case where the forward model is represented by the eikonal equation and derive a formalism to solve the inverse problem where gradients are calculated efficiently using the discrete adjoint state method. Our approach provides gradients with respect to both velocity structure and source locations, allowing us to perform a consistent joint inversion. The forward problem is solved using a second-order fast-marching method, which provides a strategy to efficiently solve the adjoint problem. We allow for arbitrary positions of both sources and receivers and for a refined grid around the source region to reduce errors in computed traveltimes. We show how gradients computed using the discrete adjoint method can be employed to perform either deterministic inversion, i.e., solving an optimization problem, or for a probabilistic (Bayesian) approach, i.e., obtaining a posterior probability density function. We show applications of our methodology on a set of synthetic examples both in 2D and 3D using the L-BFGS algorithm for the deterministic case and the Hamiltonian Monte Carlo algorithm for the probabilistic case.