Studia Geophysica et Geodaetica最新文献

Paleomagnetism relies4 on stable remanent magnetizations held in rocks to reconstruct the ancient geomagnetic field direction and intensity. However, rocks may carry secondary overprints that obscure or completely destroy the original signal. To study the stability of the magnetic vector(s), laboratories routinely apply static alternating field demagnetization along three orthogonal axes (AFD₃), which is fast, non-destructive, and easy to automate. Here, we present a multiparticle model that shows AFD₃ can deviate the natural remanent magnetization (NRM). Deviations can be avoided when fulfilling two conditions: (i) the NRM was acquired in a weak field where magnetization intensity varies linearly with field strength, and (ii) the sample is magnetically isotropic. The first condition is generally satisfied for rocks holding thermal or detrital remanent magnetizations, but not those affected by an isothermal remanence (e.g., lightning), even though AFD₃ is often used to remove them. In rocks with an anisotropic particle orientation distribution, stepwise AFD₃ progressively removes different coercivity subpopulations as a function of grain orientation so the effective remanence anisotropy of the surviving carriers changes during demagnetization. The anisotropy-driven deflection therefore evolves with AF step, producing curvilinear demagnetization trajectories. Our theoretical results argue for caution when applying AFD₃ to anisotropic samples or those with isothermal overprints. Undesired NRM rotation can be avoided by tumble demagnetization or mitigated by increasing the number of alternating field axis orientations.

The anisotropy of anhysteretic remanent magnetization (AARM) provides a powerful, nondestructive means of assessing magnetic fabrics. It is widely applied to infer strain and emplacement conditions in sedimentary, volcanic, and intrusive rocks. AARM is generally represented by a symmetric second-rank tensor describing its orientation, strength, and shape. AARM, however, departs from a tensorial shape when the number of grains carrying each directionally imparted anhysteretic remanence (ARM) varies with ARM orientation – a condition that arises when the alternating field (AF) over which the ARM is imparted does not fully activate the sample. Experimental data from a highly anisotropic ignimbrite sample, together with multiparticle modeling, show that such partial activation produces non-tensorial AARMs. Although this behavior complicates tensor analysis, non-tensorial AARM can reveal superimposed fabrics, provided that users can apply AF and ARM in a broad range of orientations. This article presents theoretical models that demonstrate non-tensorial behavior and explains how to utilize these properties to discern superimposed fabrics in natural samples.

The mechanism of formation of volcanic bombs is not well-understood at present. Although several alternative models have been proposed, it is difficult to assess them due to the lack of quantitative indicators. Measurement of the anisotropy of magnetic susceptibility (AMS) of different bomb morphologies might provide an useful quantitative reference frame upon which such models can be mutually compared. In this work, we present the results of the measurement of the AMS of six different bomb morphologies. The results show that similar macroscopic morphological types can be achieved by more than one mechanism of deformation, but the internal structure of each bomb retains clues concerning the different mechanisms of deformation that acted upon it before its effective solidification. Bombs of small size may have experienced complex sequences of deformation that are superimposed in different layers of the bomb, but such complexity is not necessarily observed in bombs of larger size, as the latter do not necessarily experienced more complex sequences of deformation events. Furthermore, the breadcrust texture of a bomb may not reflect gas expansion that influenced the entire volume of the bomb, but can be related only with a superficial layer and the flattening of a bomb may be due to rotation effects around an axis, which may be defined by an embedded object. Although the diversity of AMS signals is large, it is considered that this tool provides valuable information that can help us to better understand the mechanism of formation of this type of pyroclastic products.

One of the great challenges that the IAG Sub-Commission on gravity and geoid in Africa faces is the significantly large gravity data gaps. Simple interpolation of the gravity data does not add new information at the large data gaps. In the present study, new and independent signal information is implemented by using the laterally varying density that influences the gravity signal. Consequently, the global crustal density model UNB TopoDens was introduced as an additional source of information covering the whole area of the continent of Africa. This new independent information, entering the process of generating and updating the African gravity data base, has variable laterally varying density values available as a 30″ × 30″ grid. It has been employed in the framework of the non-ambiguous window remove-restore technique, which produces well smoothed reduced anomalies which minimize the interpolation errors. The lateral crustal density model (CDM) assigns extensive water areas with a density value which is equal to 1000 k gm⁻³, and the oceans with density equal to zero. These values are overruled with valid values in order to correctly compute the impact of topographic masses in the window remove-compute-restore (wRCR) technique. Accordingly, a density model compatible with the computation of the effect of topographic masses within the window remove-restore technique has been developed. A set of Digital Density Models is needed for the computation of the effect of the topographic masses. This has been achieved by the block average operator technique. The impact of the variable density by using a lateral density model compared to the traditional use of a constant density value is discussed in detail. The results proved that the variable crustal density has a significant effect on the interpolated gravity at the large terrestrial gravity data gaps over Africa.

The accurate interpretation of magnetic anomaly data relies heavily on knowledge of the total magnetization direction of subsurface sources. Particularly when strong remanent magnetization is present, assessing the total magnetization direction is crucial for interpreting magnetic anomalies. However, magnetic field observations are prone to various noises. This study aims to enhance the accuracy of magnetization direction determination by leveraging transformed fields that are less sensitive to noises. Our primary goal is to develop a robust method to estimate the magnetization direction, especially when dealing with complex magnetic anomalies. We propose a method for determining magnetization direction by exploiting the correlation between the pseudo-gravity (PG) field (which we demonstrate is less affected by noises) and the Normalized Source Strength (NSS). This involves searching for the NSS field derived from the observed magnetic field data and the PG fields computed from a range of assumed magnetization directions. The proposed method is validated through both synthetic modeling experiments and real data applications. The results demonstrate the robustness of the method in handling diverse anomaly geometries, including cases with mutual interference and random noises. Furthermore, it effectively mitigates the influence of remanent magnetization. The experiment on sphere source with 5%, 10%, and 20% random noises showed that our method yields significantly lower errors in estimating magnetization direction than previous approach. The mean errors for inclination and declination are 0.29°, 1.22°, 2.45° and 0.44°, 0.84°, 1.92°, respectively. Consequently, our approach, utilizing the NSS field and the PG field, offers an effective tool for estimating magnetization directions.

The Chicxulub impact ∼66 Ma ago formed a large basin on the Yucatán platform, filled by sediments that provide a record of carbonate deposition, sea level and climate changes in the Gulf of Mexico. We study the post-impact sequence drilled in the Yaxcopoil-1 borehole in the crater terrace zone. The post-impact section is 792 m thick, overlying the impactites and Cretaceous carbonates. Section analyzed is between 400 and 792 m, formed by twelve units of limestones, dolomites, argillaceous/silicified limestones and calcarenites. Carbonates show cross-lamination, flow-currents, parallel lamination, cyclic graded bedding and styolitic structures. Study is based on core analyses, logging, petrography, digital scanned images, magnetic properties and X-ray diffraction and X-ray fluorescence geochemistry. The basal units U1–U4 represent low-energy deep bathyal environments and fine-grained facies varying from mudstone to wackestone. Sediment deposits, reworked and transported from the platform and crater rim, show textural and grain size changes from grainstone to packstone. Geochemical and magnetic susceptibility logs record effects of hydrothermal alteration, with secondary mineral assemblages. The SiO₂ and CaO contents display wide ranges, negatively correlated. Fe₂O₃, TiO₂, Al₂O₃ and K₂O oxides show similar patterns downhole. The Sr and MgO show a positive correlation, except for the basal sediments. Paleocene units U1–U3 show increasing density, increasing seismic velocity and upward decreasing porosity. Upper units U5–U12 are characterized by laminated black shales and marls with microfacies varying from wackestone to packstone, with planktic and benthic foraminifera and bioclasts. Unit U9 shows low density and seismic velocity and increased porosity. Depositional environments vary from low-energy deep bathyal inside the basin to shallow neritic outside the crater rim. Sediments of the internal carbonate ramp to external neritic environments record sea level changes and platform subsidence/uplift.

Marine gravity gradient data, which provide high-precision, multi-component observations, are crucial for detecting subtle variations in oceanic geological structures. This information has profound implications for geological exploration, seabed resource assessment, and seismological research. Typically, satellite altimetry is mainly employed to obtain marine gravity field information. In our study, we proposed a strategy that integrates the deflection of the vertical (DOV), derived from satellite altimetry data, with Fast Fourier Transform (FFT) technology to compute the full tensor of the ocean’s gravity gradient. Initially, the DOV components were estimated using the least squares method from the geoid gradient. Subsequently, the vertical gravity gradient anomaly on the ocean surface was determined utilizing the DOV components. Finally, the remaining five gravity gradient tensor components were derived from the vertical gravity gradient anomaly using FFT techniques. In our experiments, we applied the proposed strategy to SWOT and CryoSat-2 observations. The Scripps Institution of Oceanography model was employed to validate the vertical gravity gradient component, while the results for the full tensor of gravity gradient were verified using the CUGB2023GRAD model. The experimental results validate the processing strategy proposed in this study, demonstrating its effective applicability within the local planar coordinate system.

In this contribution, we use all three components of the gravity vector observations to compute a regional geoid and demonstrate the advantages of using the horizontal components alongside the vertical component. We apply the one-step integration method within the remove-compute-restore framework; where the long-wavelength part of the geoid is recovered from Earth’s gravitational models while the harmonicity of the computational space is ensured by removing the topographic effects. We create a system of linear equations using a discretized form of the one-step integration method and use the Tikhonov technique to deal with the numerical instability due to its implicit downward continuation and to determine the geoid at higher resolution, e.g., 1 ′ × 1′. We propose a novel method to estimate the Tikhonov regularization parameter using the discrepancy principal and a stable solution of the geoid at lower resolution, e.g., 3′ × 3′. The results reported are based on real airborne gravity vector observations collected over Colorado, USA. The scattered observations at flight level are directly inverted to the disturbing potential at grid points on the reference ellipsoid, where geoid heights are then computed using Bruns formula. We evaluate the external accuracy of the geoid by comparing it with GNSS/levelling data and estimate the location-based internal uncertainties (error) of the geoid heights through formal error propagation. As part of this contribution, the airborne gravity vector data used in this study are also available for research purposes upon request to the corresponding author.

Most methods for processing seismological data require a suitable velocity model characteristic for the given region being defined. This is also the case of the Reykjanes Peninsula in SW Iceland, where the REYKJANET seismic network was built to monitor local seismicity in the rift zone. At present, four previously published 1D velocity models (SIL, BRA, TRY and VOG) can potentially be used, prompting us to determine which one is the best. In order to address this issue, we arranged a contest in which all four 1D models and one additional 3D model (T3D) were entered. Uniform methodology for classifying the models was applied and included an analysis of: (i) post-1ocalization travel-time residuals, (ii) residuals of the P-wave first-motion incidence angle and (iii) model-predicted and measured Rayleigh-wave dispersion. We discovered that no single model was unequivocally the most optimal, as the differences between them proved rather minor. A common shortcoming of all the models is the bias of the P-wave first motion incidence angle residuals, which may be a general problem for methods working with P-wave amplitudes (e.g., moment tensor solutions). The VOG model was selected with a weak preference. Finally, we propose a simple method for modifying any of the 1D models by adding a station-dependent surface layer with a vertical velocity gradient. This way, a pseudo-3D model is generated which is fully competitive with a true 3D model while retaining the simplicity of 1D ray tracing. The efficiency of this correction was demonstrated using the VOG model. The corrected VOG model provides post-1ocalization residuals comparable with the true 3D model T3D, has zero bias in predicting the P-wave first-motion incidence angles, and agrees acceptably in predicting the Rayleigh-wave phase-velocity known from other sources. While calculations with a 3D model can be clumsy, the proposed pseudo-3D model is defined by few parameters and is very easy to use. Its applicability is limited to earthquake sources deeper than the deepest lower limit of the topmost layer below the stations.

Staggered-grid finite-difference (SGFD) approaches are universally applied to discretize different seismic-wave equations during wavefield extrapolation. However, the traditional SGFDs may encounter numerical dispersion error and instability owing to the limited approximation accuracy. To increase the simulated accuracy, we develop an optimized SGFD with high-order accuracy based on the orthogonal-octahedral operator for 3D scalar-wave modeling. Compared with the standard orthogonal-octahedral approach, the modified approach has smaller computing cost because we reduce the SGFD stencil. In addition, the corresponding time-space domain dispersion relation is beneficial to generate the least-square-based optimized high-order SGFD coefficients. Dispersion and stability comparsions show that the developed algorithm has better performance than the classical methods. Several simulated experiments verify that the proposed scheme can significantly suppress numerical dispersion in time and space domain and effectively improve the simulated accuracy and efficiency. In conclusion, the developed scheme can provide a reliable wavefield extrapolation tool for seismic imaging and inversion.