Surveys in Geophysics最新文献

Ground roll could seriously mask the useful reflection signals and decrease the signal-to-noise ratio (S/N) of seismic data, thereby affecting the subsequent seismic data processing. It is challenging for traditional methods to effectively extract high-fidelity reflection signals when ground roll noise and low-frequency reflection signals overlap in the frequency domain. We propose a fully convolutional framework with dense connections to attenuate ground roll (GRDNet) in land seismic data. GRDNet mainly consists of four blocks, which are convolutional, dense, transition down, and transition up blocks. The dense block consists of several convolution blocks to extract the waveform features of the seismic data. The short-long connection in the dense block and the skip connection in the encoder-decoder not only reuses the features extracted by the previous layer but also adds constraints other than the loss function to each convolution block. The well-trained network is tested on one synthetic data and two real land seismic datasets containing strong ground roll with linear and hyperbolic moveouts, respectively. Three traditional and two state-of-the-art deep learning (DL) methods are used as benchmarks to compare denoising performance with GRDNet. The testing results show that the proposed method can effectively attenuate the ground roll in seismic data and preserve useful reflection signals.

We study the anelastic properties (attenuation and velocity dispersion) of surface waves at an interface between a finite water layer and a porous medium described by Biot theory including the frequency-dependent effects due to mesoscopic flow. A closed-form dispersion equation is derived, based on potential functions and open and sealed boundary conditions (BC) at the interface. The analysis indicates the existence of high-order surface modes for both BCs and a slow true surface mode only for sealed BC. The formulation reduces to two particular cases in the absence of water and with infinite-thickness water layer, with the presence of pseudo-versions of Rayleigh and Stoneley waves. The mesoscopic flow affects the propagation of all the pseudo-surface waves, causing significant velocity dispersion and attenuation, whereas the effect of the BC is mainly evident at high frequencies, due to the presence of the slow Biot wave. The mesoscopic-flow peak moves to low frequencies as the thickness of the water layer increases. In all cases, the true surface wave resembles the slow P2 wave, and is hardly affected by the flow.

Integrated geophysical analysis using different methods along with a priori information from wells, is a proven approach to investigate the geology and the petro-physical characteristics of subsoil. We collected seismic and geoelectric data in an area located on the Adriatic coast in North-Eastern Italy, aimed at characterizing the quaternary sediments and the shallow geological structures. Compressional and shear-wave data provided information about geometry and velocity of the quaternary sedimentary succession, while geoelectric data provided information about the resistivity in the shallower formation, which strongly depends on the presence of groundwater (brine) and on its salinity. Clustering analysis allowed us to subdivide the study area into subdomains showing similar values of resistivity and compressional- and shear-wave velocity, enabling for a better interpretation of the processed seismic sections. Then, we calculated the petro-physical properties of the investigated sediments, i.e., brine saturation and resistivity, porosity, and clay content, for each cluster. This inverse problem involves rock-physics theories and an optimization algorithm based on the simulated annealing global-search method. The results, validated using borehole stratigraphy, provided information about the salty water wedge intrusion.

Based on a brief review of forward algorithms for the computation of topographic gravitational and magnetic effects, including spatial, spectral and hybrid-domain algorithms working in either Cartesian or spherical coordinate systems, we introduce a new algorithm, namely the CP-FFT algorithm, for fast computation of terrain-induced gravitational and magnetic effects on arbitrary undulating surfaces. The CP-FFT algorithm, working in the hybrid spatial-spectral domain, is based on a combination of CANDECOMP/PARAFAC (CP) tensor decomposition of gravitational integral kernels and 2D Fast Fourier Transform (FFT) evaluation of discrete convolutions. By replacing the binomial expansion in classical FFT-based terrain correction algorithms using CP decomposition, convergence of the outer-zone computation can be achieved with significantly reduced inner-zone radius. Additionally, a Gaussian quadrature mass line model is introduced to accelerate the computation of the inner zone effect. We validate our algorithm by computing the gravitational potential, the gravitational vector, the gravity gradient tensor, and magnetic fields caused by densely-sampled topographic and bathymetric digital elevation models of selected mountainous areas around the globe. Both constant and variable density/magnetization models, with computation surfaces on, above and below the topography are considered. Comparisons between our new method and space-domain rigorous solutions show that with modeling errors well below existing instrumentation error levels, the calculation speed is accelerated thousands of times in all numerical tests. We release a set of open-source code written in MATLAB language to meet the needs of geodesists and geophysicists in related fields to carry out more efficiently topographic modeling in Cartesian coordinates under planar approximation.

The launch of gravity-dedicated satellite missions at the beginning of the new millennium led to an accuracy improvement of global Earth gravity field models (GGMs). One of these missions was the Gravity field and steady-state Ocean Circulation Explorer (GOCE) launched in 2009. As the first European Space Agency’s Earth Explorer Mission, the satellite carried a novel instrument, a 3-D gradiometer, which allowed measurement of the second-order directional derivatives of the gravitational potential (gravitational gradients) with a uniform quality and a near-global coverage. The main mission goal was to determine the static Earth’s gravity field with the ambitious precision of 1-2 cm in terms of geoid heights and 1 mGal in terms of gravity anomalies for spatial resolution of 100 km (half wavelength at the equator). More than three years of the outstanding measurements resulted in three levels of data products (Level 0, Level 1b and Level 2), six releases of GGMs, and several global grids of gravitational gradients. The grids, which represent a step between gravitational gradients measured directly along the GOCE orbit and those represented by GGMs, found their usage mainly in geophysical applications. In this contribution, we validate the official Level 2 product GRD_SPW_2 using height anomalies over two test areas located in central and northern Europe (Czechia/Slovakia and Norway). A mathematical model based on the least-squares spectral weighting is employed with corresponding spectral weights estimated for validation of gravitational gradient grids. This model continues gravitational gradients from the mean orbital altitude of GOCE down to the irregular Earth’s surface (not to a sphere) and transforms them to height anomalies in one computational step. Analytical downward continuation errors of the model are estimated using a closed-loop test. Prior to the comparison of height anomalies estimated from gravitational gradients with their reference values derived from Global Navigation Satellite Systems (GNSS)/levelling over the two test areas, the gravitational gradients and reference data are corrected for all systematic effects such as the tide system conversion. Moreover, the high-frequency part of the gravitational signal is estimated and subtracted from reference data as it is attenuated in the gravitational gradients measured by GOCE. A relative improvement between the release 6 and release 2 gradient grids reaches 48(%) in terms of height anomalies in Czechia/Slovakia. The relative improvement in Norway is even more significant and reaches 55(%). The release 6 of the official Level 2 product GRD_SPW_2 gained the absolute accuracy with the standard deviation of 8.7 cm over Czechia/Slovakia and 9.3 cm over Norway.

Shallow-seismic full-waveform inversion (FWI) provides an effective way for the accurate reconstruction of near-surface models. The common 2D shallow-seismic FWI inverts either individual Rayleigh or Love waves, and the joint FWI of Rayleigh and Love waves can further improve the reliability of the result. Conventionally, FWI is formulated as a single-objective inverse problem and is solved with deterministic optimization algorithms. It suffers from a relatively high level of ill-posedness and high computational cost, which are two of the main problems that FWI faces. Recently, a random-objective waveform inversion (ROWI) method is proposed to mitigate these problems. ROWI reformulates waveform inversion as a multi-objective inverse problem and solves it with a stochastic optimization algorithm. The multi-objective framework and the stochastic nature provide ROWI relatively high freedom in searching for the optimal model and therefore improve its robustness against the poor initial model. In this paper, we perform a comprehensive comparison between the performance of shallow-seismic FWI and ROWI for the reconstruction of near-surface models. We compare their performance in the scenario of individual inversion of Rayleigh wave, individual inversion of Love wave, and joint inversion of both wave types. Besides, we also compare their effectiveness when using good and poor initial models. Synthetic examples of a highly heterogeneous model show that ROWI is more efficient and more robust than FWI in both individual and joint inversions. The individual ROWI of Love wave can reconstruct the model more efficiently than Rayleigh wave if a good initial model is available, and the other way around if a poor initial model is provided. The joint inversion, in both FWI and ROWI, outperforms the individual inversion of a single wave type. In both individual and joint inversions, ROWI is more efficient in reducing model error and more robust against the poor initial model than FWI. We also compare the performance of ROWI and FWI by using field data sets acquired in Rheinstetten, Germany. The results show that when a good initial model is available, both FWI and ROWI can nicely reconstruct the main structure of the subsurface model. The validity of the reconstructed model is proved by comparing it to a migrated ground-penetrating radar profile. ROWI can consistently reconstruct the model to a good level even when using a poor initial model, while the individual and joint FWIs fail to work when the initial model is poor. It confirms the relatively higher efficiency and robustness of ROWI than FWI in the reconstruction of near-surface models.

Modelling the response of seismic wavefields to sharp lateral variations in crustal discontinuities is essential for seismic tomography application and path effects correction in earthquake source characterization. This is particularly relevant when wavefields cross back-arc oceanic basins, i.e. mixed continental-oceanic settings. High-frequency (>0.05 Hz) seismic waves resonate and get absorbed across these settings due to a shallow Moho, crustal heterogeneities, and energy leakage. Here, we provide the first high-frequency wave-equation model of full seismograms propagating through realistic 3D back-arc basins. Inversion by parameters trial based on correlation analyses identifies P-, S- and coda-wave as attributes able to estimate jointly 3D Moho variations, sediment thickness, and earthquake source characteristics using data from a single regional earthquake. We use as data waveforms produced by the Accumoli earthquake (Central Italy, 2016), propagating across the Southern Tyrrhenian basin and recorded across Southern Italy. The best model comprises a deep Moho ((sim)18 km) in the middle of the basin and a crustal pinch with the continental crust in Sicily. The deep Moho corresponds to the Issel Bridge, a portion of continental crust trapped between the Vavilov and Marsili volcanic centres. The Accumoli earthquake is optimally described at a depth of 7.3 km using a boxcar with rise time of 6 s. Our results show that the early S-wave coda comprises trapped and reverberating phases sensitive to crustal interfaces. Forward modelling these waves is computationally expensive; however, adding these attributes to tomographic procedures allows modelling both source and structural parameters across oceanic basins.