Acta Geodaetica et Geophysica最新文献

The interpretation of the CHAMP and Swarm-A satellites magnetic anomalies is discussed. The vertical gradient of the Swarm-A anomalies is presented. The vertical gradient shows in detail the magnetic sources. The inversion of the CHAMP magnetic anomalies is also presented. The inversion shows the parameters of the selected forward model. The inversion is solved by numerical procedures: the nonlinear Simplex and Simulated Annealing methods. Possible origin of upper crust magnetization is summarized. The calculation of the error propagation is estimated.

The results obtained through GRACE/GRACE Follow-On spherical harmonic coefficient model exhibit noticeable north–south strip noise. While applying low-pass filtering along the latitude circle direction can effectively eliminate the north–south strip error, it unavoidably introduces east–west strip noise. This paper introduces a method that utilizes the cosine function to determine the cutoff frequency for the low-pass filtering in the latitude direction. Additionally, a low-pass filtering step is added in the meridian circle direction. This combined approach successfully mitigates the north–south strip error and simultaneously suppresses the east–west strip noise. The analysis results highlight the improvement in signal to noise ratio of global surface quality anomaly estimation achieved by utilizing the cosine function to determine the cutoff frequency. The use of data from five institutions reveals that the dual low-pass filtering (DLP) improves the signal to noise ratio by more than 2% compared to the traditional efficient low-pass-filtering (ELP). When analyzing the uncertainty in the Yangtze River Basin using the three-cornered hat method, it is observed that the uncertainties of the DLP solution, traditional ELP solution, and mascon solution are comparable. Furthermore, the DLP solution exhibits the smallest uncertainty, measured at 4.89 cm. In terms of root mean square error, the DLP almost consistently yields the lowest values across various regions, with the difference from the smallest root mean square error value remaining within 2 mm in certain regions.

We provide a key magnetotelluric section, composed of archived magnetotelluric data along a NW-SE profile in Transdanubia, Hungary. For the interpretation of the key section, observations from raw magnetotelluric data and inversion results were used. In addition, other geophysical-geological information was also considered to confirm the conclusions based on the electrical resistivity sections. All this information was combined to identify the main structural lines and geologic units along the profile. Main structural lines observed on the resistivity sections are the Alpokalja line, Rába line, Balaton line, Kapos line, and Mecsekalja line. Geologic units that can be delineated due to their resistivity contrast include the Lower and Upper Austroalpine Units, the Transdanubian Range Unit, the Mid-Hungarian Megaunit, the Tisza Megaunit and sedimentary rocks filling the sub-basins of the Miocene Pannonian back-arc basin. The inversion results of the transverse magnetic (TM) polarization mode and the phase-depth sections of the raw data were found to be the most suitable for detecting the morphology and identifying the depth of the Pre-Cenozoic basement along the profile.

In this paper, we introduce the novel Chebyshev Polynomials Least-Squares Fourier Transformation (C-LSQ-FT) and its robust variant with the Iteratively Reweighted Least-Squares technique (C-IRLS-FT). These innovative techniques for Fourier transformation are predicated on the concept of inversion, and the C-LSQ-FT method establishes an overdetermined inverse problem within the realm of Fourier transformation. However, given the LSQ approach’s vulnerability to data outliers, we note the potential for considerable errors and potentially unrepresentative model estimations. To circumvent these shortcomings, we incorporate Steiner’s Most Frequent Value method into our framework, thereby providing a more reliable alternative. The fusion of the Iteratively Reweighted Least-Squares (IRLS) algorithm with Cauchy-Steiner weights enhances the robustness of our Fourier transformation process, culminating in the C-IRLS-FT method. We use Chebyshev polynomials as the basis functions in both methods, leading to the approximation of continuous Fourier spectra through a finite series of Chebyshev polynomials and their corresponding coefficients. The coefficients were obtained by solving an overdetermined non-linear inverse problem. We validated the performance of both the traditional Discrete Fourier Transform (DFT) and the newly developed C-IRLS-FT through numerical tests on synthetic datasets. The results distinctly exhibited the reduced sensitivity of the C-IRLS-FT method to outliers and dispersed noise, in comparison with the traditional DFT. We leveraged the newly proposed (C-IRLS-FT) technique in the application of low-pass filtering in the context of gravity data. The results corroborate the technique’s robustness and adaptability, making it a promising method for future applications in geophysical data processing.

The gravity field of the Earth is time-dependent due to several types of mass variations which take place on different time scales. Usually, the time-variability of the gravitational potential of the Earth is expressed by the monthly determination of a static geopotential model based on data from gravity field missions. In this paper, the variability of the potential is parameterized by a functional approach which contains a polynomial trend and periodic contributions. The respective parameters are estimated based on the monthly solutions derived from the GRACE and GRACE-FO gravity field mission up to a maximum degree of expansion (n_text {max}=96). As a preliminary data analysis, a Fourier analysis is performed on selected potential coefficients from the available monthly solutions of the GFZ. The indicated frequency components are then used to formulate a time-dependent analytical approach to describe each Stokes coefficient’s temporal behaviour. Different approaches are presented that include both polynomial and periodic components. The respective parameters for modelling the temporal variability of the coefficients are estimated in a Gauss-Markov model and tested for significance by statistical methods. Extensive comparative numerical studies are carried out between the newly generated model variants and the existing monthly GRACE, GRACE-FO and the existing time dependent EIGEN-6S4 solutions. The numerical comparisons make it clear that estimated models based on all available monthly solutions describe the essential periods very well, but such monthly events that deviate strongly from the mean behaviour of the signal show less precision in the space domain. Models that are estimated based on fourteen consecutive monthly solutions, covering one selected year, represent the amplitudes much more precise. The statements made apply to four initial data used, which are filtered to varying degrees. In particular, DDK2, DDK5 and DDK8, as well as unfiltered coefficients were used. For all the model approaches used, it can be seen that the potential coefficients contain up to about (napprox 40) in case of DDK5 periodically signals with annual, semi-annual or quarterly, as well as Luna nodal periods and do not vary significantly beyond that degree. Only an offset can be estimated significantly for all Stokes coefficients.

Reflectivity inversion is a critical step to joint reservoir parameters and seismic data. The sparse spike deconvolution is a widely used reflectivity inversion method based on the L₁ norm constraint. But the wavelet effect limits the resolution of the algorithm. The emergence of the odd–even decomposition algorithm has weakened the wavelet tuning effect, which makes the spectral inversion based on the L₁ norm further applied. Because of the instability of the spectral inversion algorithm, the lateral continuity of the inversion reflectivity is poor. Therefore, based on the conventional spectral inversion, we introduced a stability factor and proposed a robust spectral inversion method. The algorithm inherits the high-resolution characteristics of conventional spectral inversion and the robustness of sparse spiking deconvolution. The performances of three reflectivity inversion methods from synthetic and field data examples demonstrate the improvements in resolution and stability of the robust spectral inversion algorithm.

Tikhonov Regularization is the most widely used method for geophysical inversion problems. The result of previous and current research has shown that how to estimate the regularization parameter has a dramatic effect on inversion results. In the present research, conventional methods, including L-curve, Discrepancy principle, GCV, and ACB are compared with an innovative technique called Unbiased Predictive Risk Estimator (UPRE) in the inversion of 2D magnetotelluric data. For this purpose, MT2DInvMatlab is applied as the main program. It uses the Levenberg–Marquardt method as the inversion core and the ACB method to estimate the regularization parameter. Then, this program was developed in a way that it could estimate the regularization parameter using all of the above-mentioned methods. Next, a relatively complex model consisting of two layers and three blocks was used as a synthetic model. Comparing the results of all methods in TM, TE, and joint modes showed that the UPRE method, which previously provided desirable results in the inversion of potential field data in terms of convergence rate, time, and accuracy of results, here along with the ACB method, presented more acceptable results in the same indicators. Therefore, these two methods were used in a geothermal case in the North-West of Iran as a real test. In this case, the UPRE presented results at the same level as the ACB method and better than it in terms of some indicators. So, the UPRE method, especially in large-scale problems, could be a suitable alternative to the ACB method.

Recently, high accuracy and low-cost navigation hardware is becoming increasingly available that can be efficiently used for the control of autonomous vehicles. We present a sensor fusion method providing tightly coupled integration of pseudorange, carrier phase, and Doppler satellite measurements taken at multiple vehicle-mounted GNSS antennas with onboard inertial sensor observations. The key of accurate GNSS position and orientation estimation is the successful integer ambiguity resolution. We propose a method that uses the quaternion states as constraints to improve ambiguity resolution and to increase the accuracy of the GNSS based attitude determination. Generally, the low-cost hardware neither allows a hardware-level time synchronization between the GNSS receivers due to a lack of a common external oscillator nor provides the clock steering function available in geodetic GNSS receivers. The lack of observation synchronization causes several degrees of error in attitude estimation. To eliminate this effect, a dynamics-based solution is presented that synchronizes the observations by taking the dynamics of the moving platform into account. Compared to common external oscillator based sensor setups, our solution allows to increase both the number of rover receivers on the platform and the baselines between them easily, thus it opens up new possibilities in the attitude determination of large vehicles. We validate our approach against a tactical grade inertial navigation system. The results show that our approach using low-cost sensors provides the ambiguity success rate of 100% for the moving baselines, and the positioning and attitude error reached the centimeter and half a degree level, respectively.

Precise imaging of formed fractures and delineation of a reservoir’s boundaries within a scattered seismic cloud is complicated by inaccuracies in event location. Accurate estimate of stimulated reservoir volume (SRV) is key to evaluate fracturing performance. When reservoir volume is assessed based on dispersed locations, values tend to be overestimated. The aim of the article was to calculate SRV via seismicity induced during the course of hydraulic fracturing, solely on the basis of hypocenters and location errors. The methods for three-dimensional (3D) reservoir reconstruction combine the collapsing method, density-based spatial clustering of applications with noise, and alpha-shape estimation technique using synthetic data. The method we proposed for calculating reservoir volume based on the location of microseismic events allows for a more precise and realistic estimation. The SRV obtained using the proposed approach is approximately 14 times smaller than that obtained from the original cloud.

An earthquake of local magnitude M_L = 4.6 occurred on November 7, 2010, 4.5 km northwest of the Aswan High Dam on the Spillway Fault. In the Aswan metropolitan region this earthquake was felt intensely. As no surface rupture was found, the focal mechanism and the distribution of seismic activity was one of the tools used for finding fault dimensions. The composite fault-plane solutions for the observed events on the Spillway Fault showed a left lateral strike-slip faulting with normal-fault component striking NNW-SSE. Also, remote sensing techniques were applied for the detection and identification of the geomorphology and geometry of the Spillway Fault. In this research, sub-surface layers and structures are delineated utilizing near-surface seismic techniques. Furthermore, the area’s supposed path and position of the Spillway Fault are also investigated. Two active seismic techniques, Seismic Refraction and Multi-Channel Analysis of Surface Waves (MASW), are utilized for recording near-surface seismic wave data at 9 sites. The seismic refraction profiles are conducted as a 2D cross-section on the trace of the detected Spillway Fault in the study area to evaluate the maximum depth of penetration of the P-wave for fault investigation. The constructed 2D seismic and structural sections from P-wave results show that the obtained average depth of about 30 m. In addition, the estimated P-wave velocities extend from 600 m/s to over 6500 m/s. Some lateral variation in the seismic wave velocities in all layers may represent fault zones. Moreover, the 1D MASW technique is conducted to estimate the velocities of the shear wave for the upper 30 m (Vs30) to provide the site classes and soil characteristics along both sides of the detected Spillway Fault trace in the study area. The calculated Vs30 values emphasized the idea of the existence of a normal dip-slip fault trace which divides the study area into two different lithological parts. The first part is located on the eastern side and characterized by almost class B (hard rock, according to NEHRP classification), while the other part is located to the west, and shows almost class type C (denoted as dense soil and soft rock soil).