Studia Geophysica et Geodaetica最新文献

In this study, non-stationary iterative time-domain deconvolution (CNS-ITD) is investigated. The propagating wavelets are first estimated in several overlapping Gabor windows of the data. Matrix-vector operations in the time-domain are then performed by estimating a small number of columns of the wavelet matrix by interpolation within a sparse iterative estimation for the largest reflectivities. The iteration process is stopped when a minimum root mean square (RMS) residual or a maximum number of iterations is reached. Although initially formulated on the basis of work in earthquake seismology, CNS-ITD is a matching pursuit type of approach performed continuously in the time-domain for the non-stationary case. The results can then be convolved with a higher frequency wavelet in order to make the results stationary in time and to increase the resolution of the data. We first apply CNS-ITD to synthetic data with a time-varying attenuation, where the method successfully identifies the largest reflectors in the data. We then apply CNS-ITD to two observed shallow seismic datasets where improved resolution is obtained.

In this contribution, an iterative algorithm for variance-covariance component estimation based on the structured errors-in-variables (EIV) model is proposed. We introduce the variable projection principle and derive alternative formulae for the structured EIV model by applying Lagrange multipliers, which take the form of a least-squares solution and are easy to implement. Then, least-squares variance component estimation (LS-VCE) is applied to estimate different (co)variance components in a structured EIV model. The proposed algorithm includes the estimation of covariance components, which is not considered in other recently proposed approaches. Finally, the estimability of the (co)variance components of the EIV stochastic model is discussed in detail. The efficacy of the proposed algorithm is demonstrated through two applications: multiple linear regression and auto-regression, on simulated datasets or on a real dataset with some assumptions.

Seismic interpolation can provide complete data for some multichannel processing techniques such as time lapse imaging and wave equation migration. However, field seismic data often contains random noise and noisy data interpolation is a challenging task. A traditional method applies interpolation and denoising separately, but this needs two workflows. Simultaneous interpolation and denoising combines interpolation and denoising in one workflow and can also get acceptable results. Most existing interpolation methods can only recover missing traces but fail to attenuate noise in sampled traces. In this study, a novel thresholding strategy is proposed to remove the noise in the sampled traces and meanwhile recover missing traces during interpolation. For each iteration, the residual is multiplied by a weighting factor and then added to the iterative solution, after which the sum in the transformed domain is calculated using the thresholding operation to update the iterative solution. To ensure that the interpolation and denoising results are robust, the exponential method was chosen to reduce the threshold values in small quantities. The curvelet transform was used as sparse representation and three interpolation methods were chosen as benchmarks. Three numerical tests results proved the effectiveness of the proposed method on removing noise in the sampled traces when the minimum threshold values are correctly chosen.

Singular value decomposition (SVD) is a useful method for random noise suppression in seismic data processing. A structure-oriented SVD (SOSVD) approach which incorporates structure prediction to the SVD filter is effcient in attenuating noise except distorting seismic events at faults and crossing points. A modified SOSVD approach using a weighted stack, called structure-oriented weighted SVD (SOWSVD), is proposed. In this approach, the SVD filter is used to attenuate noise for prediction traces of a primitive trace which are produced via the plane-wave prediction. A weighting function related to local similarity and distance between each prediction trace and the primitive trace is applied to the denoised prediction traces stacking. Both synthetic and field data examples suggest the SOWSVD performs better than the SOSVD in both suppressing random noise and preserving the information of the discontinuities for seismic data with crossing events and faults.

The Caroline Islands are located in a broad zone near plate boundaries in southwestern Pacific. Accumulating evidence suggests that the hotspot origin alone cannot completely explain the formation of the Caroline Islands. To investigate the tectonic setting of their formation, we calculated the effective elastic thickness (T_e) of the lithosphere beneath the Caroline Islands from an analysis of bathymetry and free-air gravity anomaly data by the admittance method. A synthetic model based on the actual bathymetry data of the Caroline Islands was developed for the finite window size biasing correction. The results show that the T_e values of the Caroline Islands (4.5–11.5 km) are significantly lower than the T_e expected for a normal oceanic lithosphere (23–50 km), and that the T_e values can be approximated by the depth to the 150 ± 100°C isotherm. The low T_e values indicate that the strength of the lithosphere beneath the Caroline Islands has been weakened by geological process. The thermal anomalies related to the Ontong Java Plateau and the South Pacific Isotopic and Thermal Anomaly, and the lithospheric fractures induced by interaction of plates are probable causes of the lithospheric strength reduction of the Caroline Islands.

Imaging of small-scale heterogeneities is important for the geological exploration in complex environments. It requires a processing sequence tuned to high-resolution model building. Conventional methods which use refractions or reflections might face problems in resolving small-scale features since they are visually close to the resolution of the reflection images. Additional information or an unconventional technology, which supports the reflection imaging, is thus of great interest. An unconventional method based on seismic diffractions naturally complements specular reflection imaging. Diffracted waves represent a direct seismic response from small-scale subsurface heterogeneities, such as inclusions with a characteristic size of the prevailing wavelength, or discontinuities in geological interfaces, such as faults and fractures. We investigate the rule of diffracted part of the wavefield on velocity model building using a full-waveform inversion (FWI) example. In order to best acknowledge refracted and reflected parts of the wavefield in FWI, we chose a synthetic data example which mimics the ocean-bottom nodes acquisition survey as it provides almost perfect conditions for FWI of diving waves, a standard tool for high-resolution model building. We show, that FWI using diving waves produces a well-resolved anomaly. Including other part of the wavefield, reflected waves, further improves the resolution of the velocity anomaly but also leads to a gentle overfitting due to missing illumination from the very steep anomaly flanks. Considering diffracted events in FWI improves the model resolution even further resulting in a detailed velocity model and correctly imaged anomaly in both vertical and lateral directions.

The values of regional tidal parameters h₂, l₂ associated with the tidal variations of ground stations were estimated for the Polish Satellite Laser Ranging (SLR) station Borowiec using SLR data. The study is based on satellite observations taken by the global network of ground stations during the period from January 1, 1999 until January 1, 2019 for monthly orbital arcs of the satellites LAGEOS-1 and LAGEOS-2. The adjusted regional values for h₂ equalling 0.7308 ± 0.0008 and l₂ equalling 0.1226 ± 0.0003 are discussed and compared with the nominal values of h₂ and l₂ given in the the International Earth Rotation and Reference Systems Service (IERS) standards and with other estimations of these parameters. Furthermore, the influence of the tidal parameters changes on estimation of the Borowiec station coordinates in the ITRF2014 reference frame was investigated. The analysis was carried out in two variants. The first one consisted in the determination of the Borowiec station coordinates with the use of the nominal values of the tidal parameters: h₂ = 0.6078 and l₂ = 0.0847 (IERS recommended values). In the second one, the Borowiec station coordinates were determined using the local tidal parameters estimated in this paper (h₂ = 0.7308 ± 0.0008 and l₂ = 0.1226 ± 0.0003). The differences between X, Y ,Z for Variant 1 and Variant 2 are ?3.5, 3.3 and 4.2 mm, respectively.

Topographic effects on gravity field modeling are important for geodesy, geophysics and related geosciences. In this study we evaluate the gravitational effects of tesseroids in spherical coordinates, including the gravitational potential (GP), gravity vector (GV), gravity gradient tensor (GGT) and especially the gravitational curvatures (GC). With the adaptive discretization stack-based algorithm by Gauss-Legendre quadrature approach, the optimized distance-size ratio values (D) of the GC components are analyzed. Numerical experiments demonstrate that the difference percentage values of the GC components (e.g., V_xxz, V_yyz and V_zzz) are larger at the range of D ∈ [0; 10] compared to those of the GP, GV and GGT components (i.e., V, V_z, V_zz). Different distance-size ratio values D = 6, 7, 14, 30, 35, 41 and 50 for the GC component V_zzz are recommended to reach the 0.1% threshold error at corresponding computational heights 260, 150, 50, 10, 8, 6 and 4 km. Moreover, the forward modeling for the gravitational effects up to GC of tesseroids based on the ETOPO1 model in China is investigated. The GC functionals could help to extend the knowledges of interior structures of the Earth and other planetary objects.

The gravity database for the IAG African Geoid Project contains significantly large data gaps. These large data gaps affect the interpolation precision of the reduced gravity anomalies needed for the determination of the gravimetric geoid for Africa. Our aim is to develop a suitable interpolation technique that can be used for a proper gravity interpolation within large data gaps. A gap of 10° × 5° in the latitude and longitude directions, respectively, located at the high lands of Ethiopia has been artificially created within the gravity data set for Africa. The rest of the data set has been used to interpolate the gravity values at the gap points; then a comparison between the interpolated and the actual data values at the artificial data gap has been carried-out to determine the accuracy of the used interpolation technique. The unequal weight least-squares prediction (with the optimum curvature parameter at the origin) with an underlying grid at the gap areas computed by the satellite-only GO CONS GCF 2 DIR R5 model till degree and order 300, has been proposed as the developed interpolation approach. For comparison purpose, the Kriging interpolation technique has also been tested. Both the classical residual terrain modeling reduction and the window technique, suggested earlier by the authors to get rid of the double consideration of the topographic-isostatic masses within the data window in the framework of the remove-restore technique, have been used for the reduction process. A comparison between the data and interpolated values of the gravity at the gap points has been carried out. The results show that the developed interpolation technique gives better interpolation accuracy at the artificial data gap.

We examine the potential of magnetic susceptibility measurements to discriminate different soil drainage classes in the Gandoman region, central Iran. Four soil drainage classes, comprising poorly drained (PD), somewhat poorly drained (SPD), moderately well drained (MWD) and well drained (WD), were identified, and a total number of 48 soil profiles were excavated and studied. The soil samples were collected from all studied profiles from the genetic horizons individually. Magnetic susceptibility was measured at both low (0.46 kHz) and high (4.6 kHz) frequencies. The crystallized and amorphous iron forms were also measured using citrate-bicarbonate-dithionite solution and oxalate-ammonium extracts, respectively. The highest magnetic susceptibility was observed in WD soils, whereas the lowest susceptibility was observed in PD soils. The results of the predictor models developed by discriminate analysis showed that the use of magnetic susceptibility and iron forms could correctly predict about 90.9, 78.6, 85.7 and 88.9% of all profiles in WD, MWD, SPD and PD classes, respectively. Overall, the results indicate that magnetic susceptibility could be applied as a marker for the discrimination of drainage classes in the study area. Magnetic susceptibility is thus a quickly accessible and low-cost indicator for soil drainage classes for landownerships and subsequent analyses.