Acta Geodaetica et Geophysica最新文献

The well-known, traditional way to extend P-wave acoustic impedance data between and beyond the well log locations is the post-stack inversion of seismic data usually available in the surroundings of the boreholes. A relatively new trend in the seismic exploration is based on the pre-stack inversion of the seismic CDP gathers providing both the P- and S-wave acoustic impedance sections (and volumes), as well as the estimated density data. This methodology is often called as simultaneous model-based inversion and can be utilized not only for hydrocarbon exploration, but it might also be a useful tool for the investigation of geothermal resources. In this study, we will compare the results of post-stack and pre-stack acoustic impedance inversions utilizing the same seismic volume. We will demonstrate and analyze the inverted attribute sections (and some of their derivatives) obtained by the pre-stack algorithm in detail. Finally, we will draw the conclusions about the lithological discrimination of the studied complex carbonate geothermal reservoir located in the pre-Cenozoic basement of the Little Hungarian Plain.

Road structure is composed of different pavement materials. These materials contain a large number of particles and pores with different sizes, shapes, dielectric properties and spatial locations, which determines the electromagnetic properties of roads. These feature multi-scale and discontinuous characteristics between layers, together with geometric irregularity and random non-uniformity characteristics within layers, therefore random structures will undoubtedly have a negative impact on GPR detection and data interpretation. As a supplement to the experimental observation, the forward modeling based on random media model can provide an economical and effective way for GPR detection of road hidden diseases. In this paper, discrete random media model and continuous random media model are established respectively by using digital image processing technology and stochastic process theory according to the structural characteristics of different layers of media in road structure. On the basis of the established random media model, the GPR response of holes and pipelines are simulated and analyzed by the Finite Difference Time Domain method, and the GPR signal is processed by the synthetic aperture focused imaging method. By comparing with homogeneous layered models, the results show that the forward modeling based on random media model can reflect the characteristics of ground penetrating radar signal of road structure more accurately. PVC pipe is accompanied by obvious multiple waves in the case of water filling. The polarity relationship between reflected wave and direct wave is the key to distinguish whether it is iron pipe or cavity. Synthetic aperture focused imaging algorithm can enhance the recognition of spatial location, size and dielectric properties of the target. The comparison with the field results shows that the simulated results are in reasonable agreement with the measured ones.

The seismicity of Romania is mostly represented by earthquakes produced by the Vrancea seismic source with intermediate depth events (3 shocks/century with magnitude M_W greater than 7.0). The seismic activity in Romania also includes crustal earthquakes. The crustal seismicity is more scattered and moderate compared to the intermediate-depth one. A stable and automatic method has been implemented in the real-time data acquisition and processing system ANTELOPE to estimate the seismic moment, the moment magnitude and the corner frequency of events recorded by the velocity sensors, using spectral analysis applied to S waves. The main goals are the independent estimation of the seismic moment and the common characterization for all events recorded by the National Seismic Network. The main target of this paper is represented by the fast estimation of moment magnitude M_W and ground motion parameters that are derived using Gallo et al. (Bull Earthquake Eng 12:185–202, 2014) methodology and their validation with other magnitude determination algorithms existing at the National Institute for Earth Physics (NIEP). To test this new methodology, we have analyzed 331 seismic events, most of them being automaticaly located, and afterwards added a new, manually processed solution for events with M_L ≥ 4.5, to obtain a larger interval of magnitudes.

Salt crystallization is the most important weathering processes that causes problems for rocks used as building stones. Therefore, assessment of the physico-mechanical properties of stones against cyclic salt crystallization is a critical issue for rock engineering applications in salty environmental conditions especially prone to abrasion. This research aims at investigating the relationship between the degradation of various physico-mechanical properties including apparent porosity, point load index, unconfined compression strength and abrasion loss rate for rocks during salt weathering process. For showing rock weathering in the salt crystallization process, five kinds of carbonate rocks were sampled from different areas of Egypt and subject to cyclic salt crystallization, up to twenty cycles. The variation rates of their physico-mechanical characteristics and abrasion loss values were calculated after each five cycles of salt weathering. The results showed that the studied rocks are suitable for use as building and decorative stones in areas prone to crystallization of salts, but attention must be paid to rocks with high porosity and low strength characteristics such as El-Minia limestone specimens. It was also found that there are strong linear correlations between the physico-mechanical degradation parameters and the abrasion loss rate of the studied rock samples at the end of the twentieth cycle of salt weathering. These relationships may be used to estimate the abrasion loss rate of the studied rock types against the cyclic salt weathering conditions and hence to make a rapid evaluation of the stone durability.

The Landsat program, which started in 1972 with Landsat-1, continues today with its newest satellite, Landsat-9, launched on 27 October 2021. The Landsat-9 data have been freely distributed since 10 February 2022 on the Earth Explorer platform. However, no scientific study on Landsat-9 for land use/land cover (LULC) mapping has yet been published, focusing on specific eco-systems. Therefore, the present study investigates the potential of Landsat-9 images for LULC classification in forest and agricultural systems. To achieve this, we selected two study areas, i.e. Kaynarca (forest-dominated) and Hocalar (agriculture-dominated), from different ecoregions of Turkey. Then, we mapped their LULCs using Landsat-8 and Landsat-9 data with the Support Vector Machine, K-Nearest Neighbors (K-NN), Light Gradient Boosting Machine (LightGBM), and 3D Convolutional Neural Network (3D-CNN) methods. The classification accuracies were assessed with the F1-score, taking the stand-types maps of the case areas as reference. It was seen that the best maps were generated by the 3D-CNN method with accuracy rates of 88.0% for Kaynarca (Landsat-8) and 87.4% for Hocalar (Landsat-9) at the landscape level. Unlike other methods, 3D-CNN removed the “salt-and-pepper effect” on the maps providing better spatial structure for further analyses. Regardless of the satellite missions, the mapping accuracies for the “productive forest” and “agriculture” classes were > 90% for Kaynarca and Hocalar, respectively. The comparative results suggest that Landsat-9 offers satisfactory LULC maps with similar classification accuracies as Landsat-8 and can be effectively used as a freely available remote sensing resource in monitoring and mapping forest- and agriculture-dominated landscapes.

This paper presents a method for parameter estimation of self-potential (SP) anomalies using neural networks. The General Regression Neural Network (GRNN) one-pass learning algorithm was performed to invert SP anomalies of simple shaped geometrical bodies approximation. The one-pass learning algorithm has a certain advantage in terms of computation time compared to classical neural networks because the classical neural networks use multiple learning steps. The presented algorithm was tested on noise-free and noise-corrupted synthetic data. In addition, the method was applied to three field examples: Süleymanköy, Weiss, and Sarıyer anomalies, respectively. The model parameters including electric dipole moment, polarization angle, depth, shape factor, distance from the origin of the anomaly, base slope and the base level were successfully estimated using the presented method. The frequency distribution of each model parameter was calculated to improve and overcome the ambiguity of the estimated model parameters. To investigate the correctness of the estimated model parameters, the obtained results were compared with previous studies. Thus, the agreement between the results obtained by the present method and other previous results is similar to most of the estimated model parameters in accordance with numerical values. The result of the present study shows that the GRNN can be used as a powerful parameter estimation tool in the interpretation of SP data in terms of computation time compared to artificial neural networks.

The Persistent Scatterer Interferometry (PSI) and Global Navigation Satellite System (GNSS) techniques were used to identify the deformation rates in the Saurashtra region, western India. A sizable number of mild to severe earthquakes (with up to M5.1) have been observed in this part of the Indian plate. In order to calculate the crustal deformation, 241 Sentinel 1A images of path 107 with frame numbers 518 and 523, acquired between 2017 and 2020, were used. Similarly, processing of the GNSS dataset was done for four sites between 2009 and 2020. The foremost geodetic results from Saurashtra indicate the existence of a significant amount of deformation. PSI results show movements towards the satellite line of sight (LOS) of up to 5.0 ± 2.0 mm/year at several places and GNSS results indicate horizontal movements of less than 1.0 ± 0.4 mm/year and vertical movements of up to 2.3 ± 0.5 mm/year in the Saurashtra region. The projected LOS displacement of the GNSS is closely comparable with the PSI derived displacement. The results highlight isolated deformation pockets in various parts of the study area. Further, two loci with significant linear displacement were observed in south and east Saurashtra. Considering the seismic activity of the region, the inferred deformation rates may pose increased seismic risk for the region.

China’s BeiDou navigation system has been completed and is currently in operation. As the newest constellation, BD-3 is composed of 30 satellite configurations. The application of BD-3 has improved rapidly, however, using the BD-3 signal as a signal resource in the global navigation satellite system (GNSS) passive radar domain to monitor deformation has not been proven to be feasible. The authors of his paper designed a BD-3 passive radar model and carried out a proof-of-concept experimental demonstration for deformation monitoring. As a result, a method based on the B3I signal as a signal resource for GNSS radar (GNSS-R) deformation monitoring is proven to be feasible. The experimental scenarios include laboratory simulation and proof of concept field displacement deformation. The test error reaches a value of 0.023 m for a simulation scenario, 0.0435 m for a field scene of deformation based on a target translation measurement, and 0.1011 m for a field scene of deformation based on a target rotation measurement.

A geophysical test site (GTS) is an all-important engine room in geophysics for pedagogical field-based exercises because it is a fundamental bridge builder that links the hypothetical information given in the classroom and the real problem-solving research. This paper examines the ability of 163 undergraduate and 84 postgraduate students in the identification and use of some selected geophysical equipment and geophysical data processing software to address the general decline in literacy, technical efficiency and field skills. The students' unfamiliarity with simple geophysical data processing software and geophysical equipment, which has left a question mark on the quality of national geophysical education. In addressing this, the authors applied empirical data using a diagnostic questionnaire and field-based exercise. The analysis shows that more than 70% of undergraduate and 50% of postgraduate students lack the requisite university skills to face real problem-solving in the industrial sectors. To standardize geophysical education, this study identified the establishment of GTS as one of the major factors that influence teaching, learning outcomes and research development. Student perception feedback, unemployable graduates and educational implications of GTSs were extensively examined to link up teaching and research in geophysics. Consequently, conclusions and recommendations were drawn to bridge the missing links and the shortcomings of the theoretical knowledge-based emphasized in the classroom with the real problem-solving research that will provide geophysics trainees and graduates with the kind of lifetime requisite and professional skills required to be successful in their future tasks.

The determination of Precipitable Water Vapor (PWV) using GNSS data with Precise Point Processing (PPP) is a useful alternative for precisely estimating atmospheric water vapor. The use of GNSS data allows for all-weather PWV tracking 24 h a day, 7 days a week. The weighted mean temperature (T_m) is an important variable in deriving GNSS-PWV values with high accuracy, especially in tropical zones. Unfortunately, the usual method of obtaining T_m is through expensive meteorological instruments such as radiosondes which are not available in every region of Thailand. This current research derives empirical models of T_m based on two data sets: one provided by the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua platform, and one provided in the European Centre for Medium-Range Weather Forecasts’ (ECMWF) ERA5 Reanalysis. GNSS-PWV was calculated for 76 GNSS CORS around Thailand using T_m values calculated by the developed models in conjunction with GipsyX software. Results were validated against AIRS-PWV values, and compared against other existing T_m models. Results based on the developed AIRS-Tm and ERA5-Tm models, as well as the existing Suwantong, Bevis, Mendes, Schueler, and GPT3 models, showed mean biases in PWV difference against AIRS-PWV values of 0.3, 0.2, − 0.3, 1.0, 0.8, 1.8, and 1.1 mm, respectively. These results conclude that the mean bias of GPS-PWV estimations can be reduced when a more localized countrywide T_m model is used versus a global model.