Acta Geophysica最新文献

Water scarcity in developing counties in coastal areas is one of the difficulties that the local communities are facing despite the continuous effort made by the international communities to drive the local government to meet the sustainable development goal. To diffuse such difficulties, cost-effective geophysical techniques coupled with water quality assessment are being used as exploration tools. The study aims to identify groundwater potential zones and assess their quality for immediate use and consumption. The water quality index (WQI) map was produced for domestic and agricultural usage. The WQI was generally poor for domestic usage and needs treatment before consumption. The groundwater is adequate for agricultural use. The aquifer depth and thickness were identified and mapped. For shallow aquifers, a well can be drilled at a depth range of 35–40 m, and for deep aquifers at a depth range of 90–120 m, they were observed to have medium to high permeability. Anthropogenic activities are the main cause of the salinization observed in some of the shallow aquifers. An integrated approach enables to determination of the groundwater potential and quality within a wetland community and industrial area.

Applying the multichannel analysis of surface waves (MASW) test in sloping ground conditions is of significant interest in the geotechnical investigation when estimating a subsurface shear wave velocity (({V}_{s})) profile. The soil stratification in sloping ground violates the assumption of the horizontal soil layer in the vertically heterogeneous medium and results in misinterpretation of the ({V}_{s}) profile in a MASW test. One of the major challenges in this context is to identify an effective frequency range that can be used to invert the dispersion curves. This study presents a methodological framework to address the issues mentioned above. The analysis involves finite element (FE) simulations for a homogeneous sloping soil model and a six-layer sloping soil model, along with the field test validation. The wavefield was recorded for the duration of 0.3 s with a sampling frequency of 4000 Hz. Spectral characteristics of the recorded wavefield, such as attenuation of Fourier amplitudes as a function of offset distance and amplification/de-amplification of the wave amplitude (through different velocity layers), were examined. Moreover, the variation of unwrapped phases and cross power spectrum (CPS) between each pair of receivers was analyzed to identify the effective frequency range of dispersion curves. Finally, the proposed approach was successfully validated using a comparison of the ({V}_{s}) profiles obtained from field MASW and downhole seismic tests.

In geological exploration projects, well log curves, as the primary carriers of information, are prone to data defects due to geological conditions, logging equipment, and unexpected events. This paper proposes a low-cost curve synthesis method based on deep learning. The method in this paper is based on a recurrent neural network, which can preserve contextual information in signals, crucial for logging data that vary with depth. An attention mechanism is employed to enhance the vanilla long short-term memory network, enabling it to capture larger spatial dependencies, but introducing a significant amount of matrix operations. To simplify this computation, a selector is designed to reduce the time complexity from (O(n^{2} )) to (Oleft( {nlog n} right)). Two application scenarios are considered: predicting missing logging parameters using complete logging parameters and predicting missing segments of a well based on the original well data. Through validation and analysis, the proposed method demonstrates higher accuracy. This accurate, efficient, and cost-effective prediction method holds practical value in engineering applications.

First-arrival picking is a crucial and fundamental task in seismic data processing. Existing direct picking methods are often sensitive to background noise and complex near-surface conditions. In this paper, we propose a first-arrival picking through pattern matching and threshold adjustment (FPMA) method, which comprises two subroutines. The range detection subroutine obtains a first-arrival range with adaptive pattern selection and pattern matching techniques. The former selects an appropriate pattern, while the latter obtains the first-arrival range. The first-arrival detection subroutine determines first arrivals in the range with the threshold adjustment technique, which automatically selects an appropriate threshold for picking. Experiments on five datasets demonstrated that FPMA is more accurate and efficient than four popular methods.

The forward simulation of the viscous acoustic wave equation is essential for understanding wave propagation and seismic inversion. The viscous acoustic seismic wave equations are diverse, even if we limit the study scope to the fractional viscous wave equations. In present study, we consider three Riesz fractional viscous wave equations: the Fractional Viscous Acoustic Wave (FVAW) equation, Dispersion-Dominated Wave (DDW) equation, and Attenuation-Dominated Wave (ADW) equation. The Acoustic Wave (AW) equation, as a special fractional wave equation, is used to compare with the three fractional viscous acoustic equations. The Asymptotic Local Finite Difference (ALFD) method is adopted to solve the fractional derivative term; while, the Lax–Wendroff Correction (LWC) scheme is used to solve the integer derivative term. The analysis results indicate that the numerical scheme of the ADW equation exhibits the most rigorous stability condition, and that of the DDW equation is the most flexible. When the product of complex wavenumber k and spatial step size h equal to (pi), the maximum phase velocity errors of the FVAW equation, DDW equation, ADW equation, and AW equation are 27.78%, 28.02%, 2.25%, and 3.04%, respectively. Numerical experiments demonstrate that the FVAW equation not only governs the arrival time but also influences the amplitude. The DDW equation governs the arrival time but not amplitude; while, the ADW equation controls the amplitude but not arrival time. As the quality factor Q decreases, the viscous features of these three wave equations become pronounced. The change of amplitude is more noticeable than that of arrival time, suggesting that arrival time is more robust than amplitude. Based on these findings, we suggest incorporating the step for selecting the governing equations when dealing with practical Full–Waveform Inversion, which is helpful to improve the accuracy and reliability of the inversion results. Our results not only emphasize the importance of understanding the behavior of viscous wave equations, but also provide waveform evidence for selecting seismic governing equations in Full–Waveform Inversion.

In this experimental study, semi-circular end collars around semi-circular end abutments and rectangular collars around rectangular abutments were tested in order to investigate the efficiencies of the collars in reducing the local scour depth under unsteady-state clear-water approach flow conditions. Experiments were conducted in a rectangular sediment channel having a sediment pool filled with uniform sand as the bed material. Three different abutment lengths having constant widths were tested under three distinct successive flow intensities that were applied continuously for a duration of 2 h during each experiment. Varying sizes of collars were located at different elevations relative to the bed level. The effect of abutment length, collar width, collar elevation, flow intensity and temporal variation on local scour reduction performances of collars were tested. According to the experimental results, it can be stated that the application of collars around the semi-circular end and rectangular bridge abutments decreases the local scour depth by up to 72% and 51%, respectively. In addition, semi-circular end collars around semi-circular end abutments gave better results in reducing the scour depths than rectangular collars around rectangular abutments. Best collar performances were generally achieved for the largest collar width located around the bed level for semi-circular end abutments and below the bed level for rectangular abutments.

The district of Maçka in Trabzon, in the Eastern Black Sea Region of Turkey, frequently experiences landslides, resulting in the highest number of disaster victims. In this study, Landslide Susceptibility Maps (LSMs) were generated via the Statistical-based Frequency Ratio (FR) and Modified Information Value (MIV) models using 10 factors. Out of the 150 landslides in the region, 105 (70%) were utilized in creating the maps, and the remaining 45 (30%) were reserved for validation. The models demonstrated success rates of 87.5% and 84.9%, along with prediction rates of 84.8% and 83.1%, respectively, as determined by the receiver operating characteristics curve and area under the curve values. While both models achieved acceptable levels of accuracy, MIV outperformed FR. Additionally, the risk status of 5413 buildings and forested areas was examined. The results showed that 78.64% (FR) and 80.79% (MIV) of the buildings were situated in high landslide risk areas. Regarding forest areas, 39.30% (FR) and 41.35% (MIV) were observed in high-risk landslide areas. In the next step, neighborhood landslide risk statuses were examined, revealing risks ranging from 90 to 100% in some areas. The final step concentrated on risk analyses for construction plans in a chosen pilot neighborhood using two criteria. 88.75% of all parcels were observed in high-risk areas, with hazelnut groves at 79.67% in high-risk zones. Conversely, 71.89% of fruit trees were in low-risk areas. The results align with the literature, indicating that LSMs can serve as a versatile base map.

The Poisson’s ratio of hard rock exhibits a marked stress dependence, which is contrary to its mechanical definition as an elastic constant. Thus, it is of great importance to determine the Poisson’s ratio through a reasonable method. To investigate the Poisson effect of multiple types of hard rocks (sandstone, basalt, granite, and marble), the uniaxial loading–unloading tests are carried out. The test results indicate that whether the tangent Poisson’s ratio or the average Poisson’s ratio, all gradually increases with the stress level. And the stress dependence of the average Poisson’s ratio under the unloading path is reduced, which is significant in the low and medium stress intervals. Appropriately increasing the number of loading–unloading cycles can also improve the stability of the average Poisson’s ratio to some extent. Based on this, a new method for testing the average Poisson’s ratio is proposed, which can effectively exclude the effect of irreversible displacement of rocks and improve the stability of the average Poisson’s ratio. The test procedure is simple and has good application prospects.

Accurate prediction of soil liquefaction is important for preventing geological disasters. Soil liquefaction prediction models based on machine learning algorithms are efficient and accurate; however, some models fail to achieve highly precise soil liquefaction predictions in certain areas because of poor generalizability, which limits their applicability. Thus, a soil liquefaction prediction model was constructed using the CatBoost (CB) algorithm to support categorical features. The model was trained using standard liquefaction datasets from domestic and foreign sources and was optimized with Optuna hyperparameters. Additionally, the model was evaluated using five evaluation metrics and its performance was compared to that of other models that use multi-layer perceptron, support vector machine, random forest, and XGBoost algorithms. Finally, the prediction capability of the model was verified using three case studies. Experimental results demonstrated that the CB-based model generated more accurate soil liquefaction predictions than other comparison models and maintained their performance. Hence, the proposed model accurately predicts soil liquefaction and offers strong generalizability, demonstrating the potential to contribute toward the prevention and control of soil liquefaction in engineering projects, and toward ensuring the safety and stability of structures built on or near liquefiable soils.

This paper aims to present the mechanism of scour and empirical equations for evaluating local scour with and without a countermeasure around the bridge pier. A critical review of scour countermeasures, mainly hydraulic, structural, and biotechnical, extending to the present time is done. Hydraulic countermeasures consist of river training structures and bed armoring. Structures placed parallel, perpendicular, or at an angle to the flow aiming to modify it is the purpose of river training works. Armoring is done through the use of riprap, partially grouted riprap, cable-tied blocks, grout-filled containers, and gabions. Structural countermeasures include foundation strengthening and pier geometry modifications. Extending footings, underpinning, and pile- underpinning are related to foundation strengthening, while pier geometry modifications include different pier features such as shapes, textures, slots, and collars. Biotechnical countermeasures include using vegetation riprap, geosynthetic polymer, live staking, and bio-stabilization using extracellular polymeric substances. Different combinations of countermeasures are also discussed. In hydraulic and structural countermeasures, riprap and collars are most commonly used due to their efficiency in scour reduction and economic feasibility. Bio-stabilization using extracellular polymeric substances is a novel measure for scour prevention. From the literature, it is concluded that pier modifications are the most effective and active area of research in which lenticular pier shape, lenticular hooked, and airfoil-shaped collar are best suited for reducing the local scour around the pier. Finally, the limitations of the countermeasures mentioned above are presented.