Journal of Geophysical Research: Solid Earth最新文献

Establishing a quantitative framework to evaluate the spatiotemporal patterns of slow earthquakes and to detect their anomalous activities is essential for understanding diverse slip behaviors on plate boundaries and seismic hazard assessment. In this study, we focus on deep tectonic tremors, which are one manifestation of slow earthquakes and are detectable through seismological observations along the Nankai Trough. We develop a probabilistic model based on a multivariate Hawkes process to describe both the temporal and spatial characteristics of their activity. Our analysis shows that more than half of the tremors are attributable to interactions with neighboring regions, which underlines the importance of incorporating spatial interactions into the forecasting model. Along-dip and along-strike variations in background tremor seismicity and the effective durations of inter-tremor interactions revealed in our model are consistent with previous geophysical and geological observations and conceptual frameworks, including tremor migration, depth-dependent slip modes, partial overlap with slow slip events (SSEs), and along-strike variations in plate convergence rate. We further compare the model-predicted tremor activity with observations and quantify their differences in cumulative event counts using the Kolmogorov–Smirnov test to identify transient anomalies. The detected anomalies include both short-duration (∼0.1 days) and long-duration (∼100 days) activations and quiescences. Although their spatial extent is much smaller (25 km) than that of SSEs, half of the short-term anomalies partially correlate with geodetically detected short-term SSEs. These results demonstrate the potential of our approach to provide a robust framework for forecasting slow earthquake activity and detecting its changes.

The crystal structure of Earth's solid inner core is fundamental to understanding the chemical composition and dynamical evolution of the core. However, despite extensive research, the structure still remains controversial with competing hypotheses regarding the stability of various Fe phases (e.g., bcc, fcc, and hcp). In this paper, we review the studies on the crystal structure of Fe under inner core conditions, and find, in line with previous work, that the main challenges come from the small energy differences between these structures. This has led to a variety of different conclusions across varying theoretical methods and precision, including ab initio, force field and machine learning methods. To address this problem, we employ a Bain path thermodynamic integration approach to reach consistent conclusions among different methods; we find that bcc Fe is mechanically stable but thermodynamically less stable under inner core conditions. Using the energetics from the Bain path method as a benchmark, we establish the requirements for converging free energy calculations through a two-phase thermodynamic modeling approach. These calculations confirm that the hcp phase is the most stable, exhibiting the highest melting temperature regardless of the method used. This unified conclusion on the hcp phase as the stable crystal structure provides a robust foundation for future studies on Earth's core.

Intraplate volcanism has long been linked to deep mantle plumes. However, recent studies showed that intraplate magmatism can originate from transition zone dynamics, where lower-mantle plumes might be ponding, creating a Thermal Boundary Layer (TBL). Inspired by intraplate volcanoes in Eifel, Massif Central and Hainan that are distributed near tips of stagnant slabs imaged at transition zone depth, we hypothesize that subducted slabs might destabilize the TBL and trigger upper mantle plumes (secondary plumes), leading to intraplate volcanism. So far, the generation of such secondary plumes and the influence of slabs on plumes remain poorly understood. In this study, we perform 2D upper-mantle geodynamic models with a TBL imposed at 670 km depth interacting with a slab of an intra-oceanic subduction zone. The effects of various slab geometries (rollback, rollover and intermediate), TBL temperature and heating time are tested. Our models show that slabs of all geometries can destabilize the TBL, initiating secondary plumes ahead of and behind the slab. All plumes are deflected by the slab-induced mantle flow and a sinking slab may even suppress plumes beneath it. However, a higher TBL temperature and a longer pre-subduction heating duration may increase buoyancy flux of secondary plumes, making them more resistant to slab-driven flow. Under all conditions explored in this study, the strength of secondary plumes produced in our models is comparable to that of the Eifel plume. This paper elucidates slab-plume interaction and their impact on intraplate volcanism with applications to the Eifel, Massif Central and Hainan volcanic areas.

Accurate earthquake location is of fundamental importance for understanding seismogenic processes, revealing the Earth's interior structure, and mitigating seismic hazard. However, precisely determining the depth of an earthquake is often challenging due to the severe trade-off between focal depth and origin time, especially in the absence of nearby seismic stations. To address this challenge, we have developed an integrative procedure for reliably and efficiently identifying the sP depth phase in local and regional seismic records. After picking the traveltimes of first-arriving P, S waves and sP depth phases, we sequentially refine earthquake hypocenter (longitude, latitude and depth) and origin time within a Bayesian inversion framework. The efficacy of the proposed depth phase identification procedure and earthquake location method is validated through the analysis of small-to-moderate aftershocks that occurred within 2 months of the 2019 M_w 7.1 Ridgecrest earthquake. Our study shows that including depth phases can significantly reduce location uncertainty in depth by a factor of five. Moreover, the results achieved by jointly using first arrivals and depth phases are less dependent on the background velocity model, enabling more accurate location estimates for 86.6% of the examined earthquakes. In regions northwest of the mainshock nucleation area, the base of the seismogenic zone is located generally below 10 km, likely sandwiching a much shallower brittle-to-ductile transition zone (<4 km) beneath the Coso geothermal site. This locally abrupt change in rock rheology may modulate the rupture propagation of large earthquakes.

The mechanisms responsible for intracontinental basaltic volcanism are not well understood. The Cenozoic long-lived (∼30 Myr) and diffuse intraplate volcanism in central Mongolia is an ideal natural lab to address this issue. Here we present a high-resolution lithospheric 3-D shear-wave velocity model using ambient noise tomography with data mainly from two dense seismic arrays. Our model shows strong lithospheric heterogeneities beneath central Mongolia, correlating well with the occurrence of Cenozoic basaltic volcanism. Specifically, relatively thick, high-velocity lithospheric mantle is imaged beneath the central Hangai Dome and the Hövsgöl region where Precambrian basements have been suggested to exist, which likely represent relicts of old cratonic lithosphere. Step changes in lithospheric thickness formed at their peripheries due to heterogenous lithospheric thinning or modification likely caused by recent deep mantle upwelling. More interestingly, most basaltic volcanism in central Mongolia is located at or near these strong lateral gradients of lithospheric thickness, suggesting the important role of small-scale convection in their formation due to lithospheric thickness undulations. Taken together, the Cenozoic intraplate volcanism in central Mongolia was likely controlled by inherited lithospheric heterogeneities and mantle upwelling.

Imaging the Earth's thermochemical structure is crucial for understanding its dynamics and evolution. Moreover, the increased demand for critical minerals and geothermal energy driven by the energy transition has intensified the need for reliable subsurface models. Multi-Observable Thermochemical Tomography (MTT) is a simulation-based, probabilistic inversion platform designed to harness the combined sensitivities of multiple geophysical data sets and thermodynamic modeling. It produces internally consistent estimates of the Earth's interior as probability distributions, offering a powerful means for uncertainty quantification. Here, we present an updated MTT formalism and assess its benefits and limitations to image the thermochemical structure of the lithosphere-asthenosphere system. Individual and combined sensitivities of different observables to parameters of interest (e.g., temperature, composition, crustal architecture) are explored using challenging synthetic models. Our findings demonstrate that a judicious combination of observables can retrieve complex thermochemical structures relevant to greenfields exploration. We then apply MTT to study two cratonic regions of geological and economic significance. In the Superior Craton, we jointly invert receiver functions, gravity anomalies, gravity gradients, geoid anomalies, Rayleigh-wave dispersion curves, absolute elevation and surface heat flow. In the North Australian Craton, we incorporate new data from the AusArray and add teleseismic P- and S-phase travel times to the data sets. The imaged lithospheric architectures provide new insights into the tectonic evolution of these two regions and the physical meaning of geophysical signatures. Additionally, these models offer unique proxies to guide exploration efforts for clean energy and critical minerals and serve as reference models for future high-resolution studies.

Studying long-term geomagnetic field behavior is crucial for understanding Earth's evolution, as field variability reflects processes in the planet's deep interior. One key question concerns the relationship between field strength and polarity reversal frequency, particularly during the Cretaceous Normal Superchron (CNS), a prolonged interval without reversals. We present new paleomagnetic and paleointensity data from the Deccan Traps, emplaced shortly after the CNS potentially recording the geodynamo's transition back to a reversing state. Sixteen reliable paleointensity estimates were obtained from three sites and have Quality of Paleointensity (Q_PI) scores of seven to eight. To evaluate selection criteria, results were compared using SELCRIT2, Thellier Tool A, MI-CRIT.A1, and PICRIT03. SELCRIT2 proved too permissive, whereas MI-CRIT.A1 most effectively excluded potentially biased data. Site mean Virtual Dipole Moments decrease stratigraphically from 7.0 ± 0.8 × 10²² Am² at the base to 5.5 ± 0.4 × 10²² Am² at the top of our sampled section. These values are higher than prior ∼66 Ma estimates which meet Q_PI ≥ 3 criteria and are instead more consistent with data satisfying the stricter prioritized Q_PI subset (QAGE + QALT + QMD). Together with existing records and model observations, our results suggest that the geomagnetic field was weaker and less variable after the CNS, supporting a closer link between reversal frequency and intensity range than absolute strength alone. Nonetheless, even rigorously filtered data sets may retain biases, complicating interpretations of this enigmatic period. Our study underscores the need for stringent selection criteria in paleointensity research.

Salt tectonics at rifted margins involves intricate interactions between weak, viscous evaporite layers and brittle sedimentary rocks. Geophysical data and geological interpretation offer valuable insights into evaporite structure formation and the average translation rate of evaporite and sediment layers on time scales of several million years and more. However, shorter-term changes in evaporite translation velocity and their impact on deformation of evaporite and sediment cannot be directly observed in natural systems. Here, we employ 2D geodynamic models of lithosphere deformation, evaporite flow and surface processes. In particular, we consider a realistic, stress-dependent and thus highly non-linear rheology of evaporites, which allows for analyzing the interactions between gravitational loading, evaporite flow and sediment deformation in great detail. We find that the oceanward translation velocity of post-salt sediments evolves in a characteristic manner: first rapidly increasing to peak values during approximately 1 million years due to the evaporite's non-linear rheology, before slowing over tens of millions of years as the evaporite layer thins and welds onto the underlying syn-rift sediments. Peak translation velocity primarily depends on the degree of evaporite-related decoupling between pre- and post-salt strata, with the fastest (>20 mm/yr) translation occurring in models with low evaporite viscosity. Our models elucidate the formation of key salt tectonic structures: turtle anticlines in the upslope extensional domain, irregularly spaced collapsed diapirs in the midslope translational domain, and complex diapir structures in the downslope contractional domain. Finally, our models visualize how asymmetric minibasins in the translational and compressional domains interact with adjacent diapirs, forming highly upturned and overturned strata.

Magnetotelluric (MT) survey results from the Late Archean Manica greenstone belt, an extension of the Odzi-Mutare greenstone belt of the Zimbabwe Craton, are presented. A total of 33 MT stations were acquired on an irregular grid with an average station spacing of approximately 5 km. This data set represents the first MT survey in Mozambique. The results from the 3-D modeling indicate a conductive mid-crustal structure in the central part of the surveyed greenstone belt and the presence of narrow sub-vertical conductive structures connecting the mid-crustal conductor with shallow structures. These sub-vertical conductive structures are tentatively interpreted as marking the location of fluid pathways for mineralizing fluids associated with gold occurrences. The modeled mid-crustal conductor mapped in the Manica greenstone belt does not have a western continuation toward the adjacent Odzi-Mutare greenstone belt in Zimbabwe.

Understanding wave propagation in subsurface reservoirs is an important topic in exploration geophysics. Using machine learning (ML), this study aims to develop a hybrid modeling approach that uses data techniques while maintaining the reliability of poroelasticity theory. Simplified dynamic equations for seismic propagation in sandstone reservoirs are established in two steps: Biot-Rayleigh theory is established and then an optimization algorithm in ML is used to identify a simplified equation and calculate a local fluid flow term, which is responsible for wave attenuation, and some of the elastic constants and factors such as the volume ratio of inclusions. The effectiveness of the approach is first tested on synthetic data, and it is shown that almost the same dispersion and attenuation as the original model can be predicted. Data from experimental and borehole measurements are then considered. Examples show that with a few data points the wave velocity can be accurately predicted in different frequency ranges. Although the model has a certain extrapolation capability, the coverage of training data is still required. Finally, the approach is extended to perform porosity inversion. The proposed technique can be extended to reservoirs with different lithologies.