Geophysical Journal International

SummaryExpanding the lower-frequency band of seismic energy sources, particularly below 2.0 Hz, is crucial for improving the stability and effectiveness of full waveform inversion (FWI). Conventional active sources including airguns are ineffective at generating low-frequency wavefields, while ambient seismic wavefields, driven by natural energy sources such as ocean waves, offer a promising alternative. Effectively using ambient wavefield energy for seismic imaging or inversion analyses, though, requires understanding key physical control factors contributing to observations - including ambient source mechanisms and distribution, ocean-bottom bathymetry, and Earth model heterogeneity - which influence wave-mode excitation and partitioning, particularly in the context of ocean-bottom ambient seismology interferometry. This study presents a modeling framework for simulating cross-correlation wavefields generated by ambient seismic sources for dense ocean-bottom sensor arrays within a coupled acoustic-elastic system, without relying on Green’s function retrieval assumptions. We model velocity and pressure cross-correlation wavefields to explore the effects of ocean-bottom velocity structure, ambient source distributions, and bathymetric variations on seismic wave excitation and propagation in the low (0.01-2.00 Hz) frequency band. Our results show that the distribution of ambient energy source locations, whether at the seabed or sea surface, significantly affects excited wave-mode characteristics. Love waves are particularly evident in the presence of substantial lateral and vertical bathymetric variations and heterogeneous Earth structure. The distribution of azimuthal ambient energy sources also influences Love-wave excitation, with the most prominent waves observed in the direction of the highest source concentration. Additionally, different particle velocity component and pressure virtual shot gathers exhibit varying sensitivity to surface waves. This work improves the understanding of low-frequency ambient seismic wavefields in ocean environments, with potential applications in long-wavelength structural imaging and elastic velocity model estimation from FWI analysis.

SummaryPredicting seafloor topography (ST) from altimetry-derived gravity data is an effective method for obtaining ST in sea areas with sparse bathymetry. Classical ST inversion methods primarily utilize gravity anomaly, whereas vertical deflection (VD)—a fundamental product of altimetry that exhibits greater sensitivity to high-frequency ST is infrequently employed. We propose an iterative method for optimization to predict ST using VD in the spatial domain, which addresses the major problem—high nonlinearity between VD and ST. It considers the Airy-isostatic compensation and removes the non-topographic components while preserving short-wavelength signals. Our method predicts the optimal ST by iteratively minimizing the squared 2-norm of the weighted residual vector between the forward-modelled and observed VD. A synthetic test conducted in a part of the South China Sea preliminarily validates the method’s effectiveness. A real-data experiment in the Arctic Ocean shows that the root-mean-square (RMS) of differences between the ST_VD model constructed using our method and checkpoints is 110.43 m, representing improvements of 6.45, 18.85, and 13.95 per cent over the topo_27.1, ETOPO1, and IBCAO V3, respectively. Accuracy verification in different depth ranges and profile analysis indicate that ST_VD exhibits significant advantages in shallow depth (≤2,000 m), while it is relatively inferior in deep depth (>2,000 m). Radial power spectra reveal that ST_VD possesses higher energy at short wavelengths (less than ∼10 km), and its energy at intermediate-long wavelengths is consistent with the comparison models. The results demonstrate our method can effectively recover detailed ST in shallow areas and enhance the short-wavelength ST.

SummaryMagnetite-apatite (MtAp) deposits have attracted considerable attention due to their complex genesis and economic importance. These deposits are rich in magnetite ore and can bear significant rare-earth elements, but their exact formation mechanisms remain controversial. This study aims to understand the formation processes of MtAp deposits by investigating the role of iron-rich magmatic liquids. Focusing on the El Laco deposit, northern Chile, we follow the hypothesis that iron-rich liquids separate from silicate magma through liquid immiscibility. Building on previous research, this study employs a three-phase one-dimensional (1D) mechanical model to simulate the separation and accumulation of immiscible iron-rich melts within increasingly crystalline magma. The model reproduces the previously suggested transition from isolated droplet settling to an interconnected drainage network and quantifies the relative efficiency of both modes of phase separation. Using scaling analysis, we define porous, mush, and suspension flow regimes and construct a regime diagram for three-phase flow. The results indicate that the separation efficiency of immiscible iron-rich melts is maximised in the mush flow regime at intermediate crystallinity. The model-derived accumulation rate of iron-rich melts can be used to estimate the time required to form magnetite deposits of a given scale. Our findings support the physical viability of the liquid immiscibility hypothesis for the genesis of MtAp deposits, offering new insights into the mechanical efficiency of melt separation and contributing to a broader understanding of the formation mechanisms of other valuable deposits that have been linked to immiscible melts.