Geophysical Journal International

SummaryWhen highly viscous fluids are present in a rock medium, the viscous effect of such fluids cannot be neglected in the propagation of elastic waves. In this paper, a fractional thermoporoelastic theory is newly proposed, which is a further improvement of the two-temperature generalized thermoporoelastic theory. Firstly, by introducing the Kelvin-Voigt model into the stress-strain constitutive equation, the viscous effect of highly viscous fluids is considered. Then, fractional derivatives are introduced into the heat conduction equations of the solid and fluid phase to consider the anomalous heat conduction caused by the viscous effect in rock media. Plane wave analysis method is adopted to obtain the phase velocity and attenuation factor of four longitudinal waves (P1, P2, T1, T2). Numerical results show that the introduction of fluid viscosity leads to the appearance of new relaxation peaks in the P wave at high frequencies, and the introduction of fractional derivatives causes a decrease in the phase velocity and attenuation factor of T waves. The results provide a reference for further research on the wave propagation in rock media containing highly viscous fluids.

SummaryInduced polarization (IP) effects in airborne electromagnetic (AEM) surveys have commonly been investigated in helicopter-borne systems, leaving both a bibliographic and application gap for fixed-wing configurations. This gap partly reflects the large relative number of helicopter compared to fixed wing AEM systems, but also the geometric complexity of fixed wing platforms. In these platforms, nine geometric parameters come into play: the pitch, roll, and yaw of both transmitter and receiver, plus the three-axis offsets between the coils. Shifts in these factors can distort the measured data in ways that aren’t uniquely attributable, making it hard to pinpoint whether negative recordings truly arise from IP or from geometry-related effects. The non-fixed geometry also complicates removal of the primary field, often requiring iterative processing steps that may suppress or alter spectral content linked to IP. With advances in airborne IP understanding from helicopter-borne systems, revisiting fixed-wing platforms is both timely and necessary. Part A of this two-part study addresses this issue using the TEMPEST™ fixed-wing system connecting numerical modelling with field evidence. A suite of synthetic two-layer models with variable resistivity and chargeability parameters was developed to evaluate the system’s sensitivity to polarizable structures. The experiments demonstrate that IP effects, including negative secondary field responses, can be reliably detected in fixed-wing AEM data, both in X and Z magnetic field components. The capacity of these systems to detect IP phenomena is, however, strongly dependent on the electrical conductance of the environment. For instance, both fixed-wing and helicopter-borne systems, elevated near-surface conductance enhances the amplitude of purely electromagnetic induction currents, which in turn can dominate the recorded response and obscure the comparatively weaker polarization currents. More in general, IP detectability depends on the strength of the EM response generated by induction currents flowing elsewhere, which can dominate the small reverse current flow from a polarizable target. This highlights the critical role of near-surface conductivity in controlling the expression of IP responses and underscores the need to carefully account for these factors when interpreting survey data. The synthetic results are then connected with field-scale observations from a subset of the AusAEM dataset, over 470 000 line-km of TEMPESTTM data, where negative responses align with areas of low shallow conductance, confirming the simulation results. These finding open the way to the Part B of this study, where TEMPESTTM data are inverted taking into account IP and compared with helicopter-borne results and geological information.

SummaryAcoustic signals can couple to the ground, providing an opportunity to use seismic stations to investigate airborne sources. The study of Bishop et al. (2022) used wavefield simulations in a fluid-solid medium to quantify the role of topography on the seismic (ground) recordings of a monopole source in the air. We build upon this study by linking wavefield forward modeling with the source estimation code MTUQ, which can accommodate point forces or moment tensors in a solid medium, as well as sources in the air (or water) if they are enabled by the forward-modeling solver. We perform a series of synthetic numerical experiments to demonstrate that a dipole airborne source can be estimated using ground-based receivers, even within the presence of realistic topography. We investigate the influence of receiver coverage, topography, and assumed source location on the estimated results. The established capabilities raise the prospects for future efforts to estimate dipole sources in 3D models that include heterogeneity in the air and the earth in addition to topography.

AbstractSeismic simulation is fundamental for understanding earthquake physics and mitigating seismic hazards, but accurate seismic modeling requires fine computational grids, imposing severe memory and computational challenges. Traditional modeling solvers, relying on single-precision floating-point 32-bit (FP32) and scalar register-based computation, suffer from excessive memory consumption, low memory access efficiency, and limited computational efficiency. Compared with FP32, half-precision floating-point 16-bit (FP16) reduces memory consumption by 50% and improves memory access efficiency; relative to scalar registers, ARM’s Scalable Vector Extension (SVE) registers provide vectorized single-instruction multiple-data (SIMD) capabilities, significantly accelerating computation. However, leveraging the advantages of FP16 and SVE involves challenges such as FP16 overflow/underflow, SVE stencil adaptation, and SVE data misalignment from FP16 storage with FP32 arithmetic. Therefore, this study proposes three approaches on the ARM architecture: FP16-based, SVE-accelerated, and FP16-SVE hybrid; each is designed to tackle the respective challenges while exploiting FP16 memory efficiency and SVE computational acceleration. Correspondingly, the three solvers are implemented, validated, and benchmarked on both hypothetical models and real-world earthquake scenarios. The results of these solvers show near-perfect agreement with the reference solver, confirming their accuracy across diverse seismic scenarios. Moreover, the FP16-SVE hybrid solver halved memory usage and achieved up to 3× computational speedup, delivering more than 2.3× acceleration in the real-world earthquake simulation. The gains in high efficiency of memory and computation highlight the capability of the FP16-SVE hybrid solver to support large-scale, real-time seismic simulations and efficient earthquake hazard assessment on ARM platforms.

AbstractSurface waves such as Rayleigh, Love and Scholte waves can exhibit dispersion, i.e., variations in phase velocity with wavelength as a function of frequency. This property enables the inversion of 1D models of seismic velocity and density in the subsurface. Conventional deterministic and stochastic inversion schemes are widely applied to surface wave data but face two main challenges. The first is the identification of dispersion curves for fundamental and higher modes on wavefield-transformed images, which is often done manually. The second is the quantification of uncertainty, which can be computationally expensive in stochastic approaches or limited to data-propagated uncertainty in deterministic inversions. Our objectives are to (1) eliminate the need for manual or automatic dispersion curve picking, and (2) directly infer ensembles of 1D velocity models - and their associated uncertainties - from the full velocity spectrum, i.e., the complete dispersion image containing all modes. To this end, we employ Bayesian Evidential Learning, a predictive framework that reproduces experimental data from prior information while allowing prior falsification. In our application, ensembles of prior Earth models are sampled to predict 1D subsurface structures in terms of seismic velocity and, where applicable, attenuation from near-surface seismic wave data. This approach bypasses traditional inversion schemes and provides a computationally efficient tool for uncertainty quantification.

SummaryRepeating earthquakes are believed to result from recurring ruptures of a single asperity, driven by surrounding aseismic creep. However, their occurrence and behavior in intraplate regions remain poorly understood. This study investigates the repeating earthquakes in the Gyeryongsan region of the Korean Peninsula, a tectonically stable intraplate region, following the 2008 Mw 3.56 earthquake. We augmented the earthquake catalogue from 2007 to 2022 using template matching and identified one repeating earthquake family comprising ten events with irregular recurrence intervals. The repeating earthquakes, with a median magnitude of Mw 1.22, occurred within the rupture area of the Mw 3.56 mainshock, beginning in late 2010 and subsequently recurring intermittently between 2011 and 2019. Stress drops of nearby earthquakes increased gradually from 0.3-0.9 MPa to 8.6 MPa over a decade, indicating a fault strength recovery period substantially longer than that typically observed at plate boundaries. We interpret that the earthquakes occurred within a damaged fault zone, reflecting extremely low loading rates in the intraplate region. Our study provides insights into earthquake behaviour within intraplate damaged fault zones and documents a rare case of a repeating earthquake family that persisted over ∼12 years.