Surveys in Geophysics最新文献

The potential of blended seismic acquisition to improve acquisition efficiency and cut acquisition costs is still open, particularly with efficient deblending algorithms to provide accurate deblended data for subsequent processing procedures. In recent years, deep learning algorithms, particularly supervised algorithms, have drawn much attention over conventional deblending algorithms due to their ability to nonlinearly characterize seismic data and achieve more accurate deblended results. Supervised algorithms require large amounts of labeled data for training, yet accurate labels are rarely accessible in field cases. We present a self-supervised multistep deblending framework that does not require clean labels and can characterize the decreasing blending noise level quantitatively in a flexible multistep manner. To achieve this, we leverage the coherence similarity of the common shot gathers (CSGs) and the common receiver gathers (CRGs) after pseudo-deblending. The CSGs are used to construct the training data adaptively, where the raw CSGs are regarded as the label with the corresponding artificially pseudo-deblended data as the initial training input. We employ different networks to quantitatively characterize decreasing blending noise levels in multiple steps for accurate deblending with the help of a blending noise estimation–subtraction strategy. The training of one network can be efficiently initialized by transfer learning from the optimized parameters of the previous network. The optimized parameters trained on CSGs are used to deblend all CRGs of the raw pseudo-deblended data in a multistep manner. Tests on synthetic and field data validate the proposed self-supervised multistep deblending algorithm, which outperforms the multilevel blending noise strategy.

Earth/rock-fill dams and embankments are the main water retaining structures in hydraulic projects, and they can effectively resist floods and are of great significance for protecting people's lives and property. Leakage is a common problem in these structures. Investigation activities, including geotechnical, geoelectric, and tracing methods, are required to locate the leakage path and provide a basis for risk mitigation and reinforcement. These three methods provide information on different leakage characteristics, uncertainties, and spatiotemporal distributions. This work first introduces the micro-mechanism of internal erosion and then, provides a site case base for leakage investigation of earth/rock-fill dams and embankments from all over the world. For each investigation method, the basic principle, investigation process, data interpretation, and future potential are summarized. It should be emphasized that geotechnical, geoelectric, and tracing methods are placed on an equal level to assist dam managers and researchers in selecting the most appropriate method to assess dam leakage against specific geological backgrounds and structural types. Finally, the advantages, disadvantages, and applicable conditions of each investigation method are compared. The role of surface investigation methods and internal investigation methods in different stages of leakage is explained. The application of combined methods is discussed at four levels, and a new combined method is proposed.

Two computational strategies for the evaluation of the spherical harmonic coefficients of the gravitational potential due to a generally shaped homogeneous polyhedral source are examined in detail. The techniques are implemented numerically for the known asteroid shape models of Eros and Didymos. The aim of the investigation is to quantify specific numerical aspects of the two algorithms, such as the accuracy of the techniques compared to a closed analytical solution for varying distance between source and computation point, the band-limited spectral analysis of the obtained spherical harmonic models and the convergence behavior of the corresponding series expansion in the vicinity of the characteristic Brillouin sphere. From a computational point of view, the line integral approach demands approximately three times the CPU time of Werner’s method. The two sets of spherical harmonic coefficients are 100% correlated up to degree 45 for Eros and up to degree 49 for Didymos. Approaching degree 100, the correlation by degree decreases by 0.0004% for Eros and by 0.004% for Didymos, the corresponding values for the correlation by order being 0.0002% and 0.304%. Inside the Brillouin sphere and approaching its boundary, the numerical agreement of the gravitational potential between the line integral method and the analytical solution is at the 1E-4 level, while with Werner’s approach at the 1E-7 level. At a distance of 33.5 km outside the Brillouin sphere for Eros and 2.2 km for Didymos, both methods are identical, reaching an agreement level with the analytical solution of 1E-11 level for Eros and 1E-14 for Didymos. In terms of spherical harmonic representation, the series defined by the line integral approach converges faster to the analytical value for the gravitational potential by 4 degrees.

The paper summarizes the issues related to relationships between the PC index and magnetic disturbances: threshold level of the PC index required for the disturbances beginning, delay time in response of magnetic substorms and storms to the PC index growth, relation of PC index to magnetospheric field-aligned currents in course of substorm, different types of magnetic substorms (isolated, expanded, delayed, sawtooth) and magnetic storms (classic, pulsed and composite) and their relation to different regularities in the PC index alterations, linear dependence of the substorm and storm intensities on value of the preceding of PC index, special features of magnetic activity in the winter and summer polar caps, variations of PC index and magnetic disturbances in course of the 23/24 solar activity cycles. New aspects that have arisen due to the PC index application are concerned with the threshold-dependent mode of the substorm development and regular repeateness of sawtooth substorms occurring under conditions of steady powerful E_KL field. The experimental results examined in the paper are indicative that the PC index serves as an indicator of the solar wind energy which comes in the magnetosphere and then realizes in the form of magnetosphere disturbances. This paper follows the review of Troshichev (Front Astron Space Sci 9:1069470, 2022), where the relationships between the solar wind electric field E_KL and PC index have been examined.

The global seasonal cycle of energy in Earth’s climate system is quantified using observations and reanalyses. After removing long-term trends, net energy entering and exiting the climate system at the top of the atmosphere (TOA) should agree with the sum of energy entering and exiting the ocean, atmosphere, land, and ice over the course of an average year. Achieving such a balanced budget with observations has been challenging. Disagreements have been attributed previously to sparse observations in the high-latitude oceans. However, limiting the local vertical integration of new global ocean heat content estimates to the depth to which seasonal heat energy is stored, rather than integrating to 2000 m everywhere as done previously, allows closure of the global seasonal energy budget within statistical uncertainties. The seasonal cycle of energy storage is largest in the ocean, peaking in April because ocean area is largest in the Southern Hemisphere and the ocean’s thermal inertia causes a lag with respect to the austral summer solstice. Seasonal cycles in energy storage in the atmosphere and land are smaller, but peak in July and September, respectively, because there is more land in the Northern Hemisphere, and the land has more thermal inertia than the atmosphere. Global seasonal energy storage by ice is small, so the atmosphere and land partially offset ocean energy storage in the global integral, with their sum matching time-integrated net global TOA energy fluxes over the seasonal cycle within uncertainties, and both peaking in April.

This review paper addresses the development of numerical modeling of electromagnetic fields in geophysics with a focus on recent finite element simulation. It discusses ways of estimating errors of our solutions for a perfectly matched modeling domain and the problems that arise from its insufficient representation. After a brief outline of early methods and modeling approaches, the paper mainly discusses the capabilities of the finite element method formulated on unstructured grids and the advantages of local h-refinement allowing for both a flexible and largely accurate representation of the geometries of the multi-scale geomaterial and an accurate evaluation of the underlying functions representing the physical fields. In summary, the accuracy of the solution depends on the geometric mapping, the choice of the mathematical model, and the spatial discretization. Although the available error estimators do not necessarily provide reliable error bounds for our complex geomodels, they are still useful to guide grid refinement. Therefore, an overview of the most common a posteriori error estimators is given. It will be shown that the sensitivity is the most important function in both guiding the geometric mapping and the local refinement.