Journal of Applied Geophysics最新文献

{"title":"Calibration of seismic parameters in the Zagros region, an application of generalized inversion technique","authors":"Reza Davoudian ,&nbsp;Hamid Zafarani ,&nbsp;Ahmad Sadidkhouy","doi":"10.1016/j.jappgeo.2025.105785","DOIUrl":"10.1016/j.jappgeo.2025.105785","url":null,"abstract":"<div><div>In this study, the Generalized Inversion Technique (GIT) was used to find seismic parameters (source and site effects) in the Zagros region, Iran. To this end, 91 events recorded at 205 three component accelerometers located in the Zagros region were analyzed. The dataset includes 745 acceleration waveforms in hypocentral distance range between 6 and 363 km and magnitude range between <span><math><msub><mi>M</mi><mi>w</mi></msub></math></span> 5.0 and <span><math><msub><mi>M</mi><mi>w</mi></msub></math></span> 7.3. All events included in the dataset were recorded between May 1997 and July 2022.</div><div>After applying a suitable processing procedure to prepare the data, near-surface high-frequency attenuation coefficient (Kappa) for both horizontal and vertical components was derived as 0.043 and 0.031, respectively. In the next step, the GIT was used to solve a linearized relationship and find spectra of site amplification and seismic source.</div><div>To find a parametric form for seismic source spectrum (<span><math><msub><mi>f</mi><mi>c</mi></msub><mspace></mspace><mi>and</mi><mspace></mspace><mi>γ</mi></math></span>, based on <span><math><mi>ω</mi></math></span> squared source model of <span><span>Brune, 1970</span></span>) and stress drop for each event, a Simple Grid Search routine was applied. The computed stress drop values were between 4 and 48.4 MPa for the west Zagros and 2 and 35 MPa for the east Zagros. The averaged values of stress drop for the west and east Zagros were 11.27 and 9.05 MPa, respectively.</div><div>Also, site amplifications derived from the H/V method were compared with the GIT results of site amplification at each station. This comparison showed that in the most stations the H/V method presents different amplification values than those of the GIT method. However, in the most stations resonance frequency reported by the H/V and the GIT methods were compatible.</div><div>The path effects including the quality factor and geometrical spreading model were adopted from <span><span>Zafarani and Hassani (2013)</span></span>. Plotting seismic moment versus corner frequency showed that the Zagros events do not follow scaling rule of <span><span>Aki (1967)</span></span> completely. The decreasing rate of seismic moment versus corner frequency equals to 1.98 in logarithmic scale.</div><div>Derived between-event and within-event residual in each frequency through studied frequency range indicated that there is a negligible trend in residual values against magnitude and distance.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105785"},"PeriodicalIF":2.2,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of ground-airborne transient electromagnetic method with layered Green's function born approximation imaging in the Huang-ling coal mine goaf","authors":"Jie Ma ,&nbsp;Ziyuan Li ,&nbsp;Xiu Li ,&nbsp;Zhipeng Qi ,&nbsp;Qiding Wang","doi":"10.1016/j.jappgeo.2025.105784","DOIUrl":"10.1016/j.jappgeo.2025.105784","url":null,"abstract":"<div><div>The large-scale mining of coal resources has resulted in the formation of goaf areas, particularly the legacy issues caused by the disorderly mining of small coal mines in surrounding areas, which may lead to serious consequences such as ground subsidence, building damage, and casualties. Therefore, it is essential to conduct detailed exploration in these goaf areas. This study focuses on the goaf areas in the Huang-ling survey area, which have been preserved in the form of water filling, and the mountains are undulating, as well as the gullies are deep and wide, conventional ground geophysical methods are not suitable to carry out. In this paper, a Ground-Airborne Transient Electromagnetic (GATEM) method, which is highly sensitive to low-resistance anomalies, efficient in construction, and applicable to exploration in complex mountainous regions, is employed for detection. Aiming at the geophysical characteristics of coal mine goaf areas, a three-dimensional theoretical geoelectric model of low- and high-resistivity interlayers is established. The transient electromagnetic method (TEM) is used to define the apparent resistivity, and a comprehensive interpretation is performed through virtual wavefield imaging, proving the high effectiveness of this method. Finally, taking the exploration of the coal bed goaf zone in a mining area in Huang-ling, Shaanxi Province, as an example, the apparent resistivity is defined using TEM to delineate low-resistance, water-rich areas. The interface morphology of water-bearing structures is described by combining the results with virtual wavefield imaging. The results show that the combination of virtual wavefield imaging can suppress the volume effect and obtain richer geological information. This study offers a theoretical basis and practical reference for the application of the transient electromagnetic method in multi-layer goaf exploration.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105784"},"PeriodicalIF":2.2,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous estimation of basement depth and density contrast by gravity anomaly via multi-task deep learning","authors":"Lin Wang ,&nbsp;Giovanni Florio ,&nbsp;Maurizio Fedi ,&nbsp;Shengqing Xiong ,&nbsp;Wanyin Wang","doi":"10.1016/j.jappgeo.2025.105781","DOIUrl":"10.1016/j.jappgeo.2025.105781","url":null,"abstract":"<div><div>We propose a multi-task deep learning (DL) method to simultaneously estimate the basement depth and the density contrast from gravity field anomalies. The method is based on a specially designed hybrid architecture, which comprises a convolutional neural network branch and a Multilayer Perceptron branch. This hybrid architecture fully leverages the benefits of multi-task DL, enabling simultaneous estimation of basement depth and density contrast, where the input is a gravity map. In the training phase, useful statistical prior information is incorporated from a global basin dataset. Our idea is that the learning based on such dataset helps to restrict the solution to a limited domain, so leading to a reasonable estimation of the basement depth and the density contrast.</div><div>We utilize a Deep Convolutional Generative Adversarial Network (DCGAN) to generate high-quality maps of basement depths based on a global catalog of basins. The preliminary real basement maps originate from the re-interpolations and nonstandard coordinate transformations of the sediment data inside the global basins, and more additional basement samples are generated by the trained DCGAN architecture, thereby forming our dataset.</div><div>We apply the method to synthetic dataset and to two real cases, thus demonstrating the feasibility and effectiveness of our DL method. The results show good performance of our DL architecture not only for the estimated basement models, but also for the density contrast. The method candidates as a valid tool for practical applications, especially when there is a lack of constraint information in complex real cases.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105781"},"PeriodicalIF":2.2,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoupled elastic wave reverse time migration imaging for tunnel seismic data","authors":"Xuhua Liu ,&nbsp;Jun Wang ,&nbsp;Xinglin Lu ,&nbsp;Wei Wang ,&nbsp;Yufeng Liu ,&nbsp;Zhihong Fu","doi":"10.1016/j.jappgeo.2025.105786","DOIUrl":"10.1016/j.jappgeo.2025.105786","url":null,"abstract":"<div><div>Tunnel seismic advanced prediction is the main technique for identifying unusual geological bodies along the tunneling path. The investigation accuracy of hidden karst caves is still not ideal due to the limited tunnel observation space and the slight physical differences between fissure structures and surrounding rock. Tunnel seismic data consist of full-wave data, which includes both P-waves and S-waves. In contrast to the P-wave, the S-wave moves at a slower velocity, has a smaller wavelength, and provides better resolution. The current methods for processing tunnel data include the <em>F-K</em> method, τ-p transformation, and polarization filtering for separating P- and S-waves, followed by migration imaging. It is challenging to suggest only P wave and S wave for actual data. Reducing the accuracy of migration imaging will occur due to errors in separating the P- and S-waves. Migration imaging plays a crucial role in seismic data processing for tunnels. The decoupled elastic wave reverse time migration (DE-RTM) method utilizes both P- and S-waves effectively for high-resolution imaging, making it the most precise migration technique available. DE-RTM is employed in this paper for tunnel seismic data migration imaging, suggesting an interpretation approach for multi-wave multi-component tunnel seismic data and establishing a thorough process for processing tunnel seismic data. The tunnel seismic data is used to examine in depth the wavefield characteristics of the P- and S-wave. The results from the data simulation and actual data demonstrate that DE-RTM has the ability to prevent wavefield separation errors, enhance signal accuracy, and utilize the S-wave effectively for improved imaging resolution. The dot-sum migration data in multi-wave migration data can offer low-frequency contour details, whereas the dot-product migration data can offer high-frequency detail information. By merging the benefits of each, one can achieve more dependable interpretation results.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105786"},"PeriodicalIF":2.2,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using transfer learning to enhance void detection and shear wave velocity model inversion from near-surface seismic shot gathers","authors":"Yanwei Zhang ,&nbsp;Dmitry Borisov ,&nbsp;Salman Abbasi ,&nbsp;Richard D. Miller ,&nbsp;Steven D. Sloan","doi":"10.1016/j.jappgeo.2025.105780","DOIUrl":"10.1016/j.jappgeo.2025.105780","url":null,"abstract":"<div><div>A Convolutional Neural Network (CNN) has been designed to delineate the shear-wave velocity (<em>Vs</em>) models and detect subsurface void locations. Addressing the processing and interpretation challenges posed on real seismic data, our strategy emphasizes that leveraging the ground truth, which is the void location in this study, enables the CNN to catch the identical features in real waveforms. Initially, a synthetic dataset is employed, imparting foundational knowledge to the CNN regarding the <em>Vs</em> model and void locations. Drawing inspiration from transfer learning, this pre-trained CNN serves as an initial model and is refined using a real dataset focused on void locations. After refining, the CNN shows enhanced reliability to detect the void and extract the <em>Vs</em> model, as evidenced by the improved alignment between forward modeling and real waveforms. Our findings underscore how leveraging the ground truth can actualize the potential of CNN on velocity model extraction.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105780"},"PeriodicalIF":2.2,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated hydraulic flow unit determination using FZI-Z-score probability, K-means clustering with autoencoders, and machine learning classification: A case study of the Subei Basin, China","authors":"Stephen Adjei ,&nbsp;Deon Yeboah Takyi-Amponsem ,&nbsp;Jonathan Atuquaye Quaye ,&nbsp;Yen Adams Sokama-Neuyam ,&nbsp;John Ojuu Oleka ,&nbsp;George Kobla Asigbi ,&nbsp;Turkson Kwesi Duodu","doi":"10.1016/j.jappgeo.2025.105778","DOIUrl":"10.1016/j.jappgeo.2025.105778","url":null,"abstract":"<div><div>Subsurface characterization is fundamental to understanding key reservoir properties such as fluid flow through rock pores. The concept of Hydraulic Flow Units (HFUs) is a subsurface characterization technique that helps identify zones with similar flow characteristics. However, the conventional technique for HFU identification using probability by ranking is not statistically robust and is unsuitable for large datasets. This study utilizes RCAL data gathered from five selected wells in the Subei Basin oilfields, in China. The data consists of the sample's diameter, length, dry weight, particle volume, bulk volume, pore volume, particle density, porosity, volumetric density, location, and permeability. A <em>Z</em>-score probability approach is proposed as a statistically superior alternative to probability computation based on ranking. Additionally, the present study adopts an autoencoder-based K-means clustering approach to delineate HFUs. Subsequently, the identified HFUs are predicted using three supervised machine learning classification models: Neural Networks Multilayer Perceptron (MLP), Logistic Regression (LG), and Random Forest Classifier (RFC). The autoencoder-based K-means clustering method identified eight (8) HFUs. Feature selection was based on the strength of the relationship between features and targets and inter-feature correlations, as defined by the correlation coefficient. Using the random subsampling approach with an 80 %–20 % train-test split, the MLP emerged as the most effective and robust model for predicting HFUs, achieving a test accuracy of 94 %. By integrating the <em>Z</em>-score probability and autoencoder-based k-means approach into HFU prediction using machine learning approaches, subsurface characterization is greatly improved.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105778"},"PeriodicalIF":2.2,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DCNet: Full waveform inversion with difference convolution","authors":"Li-Sha Fu ,&nbsp;Chang-Yang Hu ,&nbsp;Leting Tan ,&nbsp;Huawei Liao ,&nbsp;Qiang Zhang ,&nbsp;Fan Min","doi":"10.1016/j.jappgeo.2025.105762","DOIUrl":"10.1016/j.jappgeo.2025.105762","url":null,"abstract":"<div><div>Deep learning full waveform inversion (DL-FWI) is attracting broad attention due to its powerful feature extraction and nonlinear mapping capabilities. It learns stratigraphic features from seismic data without the need for a high quality initial velocity model and manual intervention. However, popular DL-FWI methods often exhibit velocity deviations and boundary localization errors at geological boundaries. Thus, we propose a new encoder-decoder network based on two types of difference convolution modules to address these issues. First, we design a novel oblique difference convolution (ODConv) inspired by an existing central difference convolution (CDConv). It effectively extracts edge details by calculating the difference between pixel pairs along different directions. Second, we incorporate CDConv and ODConv into the depth-wise separable structure to obtain the CDConv module and ODConv module, respectively. These modules are lightweight, effective, and able to mitigate gradient vanishing. Finally, we introduce a focal frequency loss to focus on frequencies that are hard to synthesize by down-weighting easy frequencies. It effectively improves the recovery of high wavenumber components in the velocity model. Experiments on SEGSimulation, OpenFWI and Marmousi II datasets show that our method outperforms state-of-the-art data-driven methods. The source code is available at <span><span>github.com/FanSmale/DCNet</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105762"},"PeriodicalIF":2.2,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using PyTorch in seismic tomography with velocity-gradient layers and spline interfaces","authors":"Hui Qian ,&nbsp;James Mechie","doi":"10.1016/j.jappgeo.2025.105768","DOIUrl":"10.1016/j.jappgeo.2025.105768","url":null,"abstract":"<div><div>An analytical ray tracing and tomographic imaging inversion method is proposed for a layered seismic model with velocity gradients within the layers and cubic spline interfaces between the layers. The optimization tools of PyTorch have been used for automatic gradient calculation, thereby reducing code length and complexity. Ray tracing employs an analytical bending method based on the segmented Snell's law. Both reflected and first arrival refracted phases can be calculated by the ray tracing and used in the inversion. The tomographic inversion involves the calculation of the Jacobi matrix and utilizes damped least squares for optimization until the travel-time residual vector is minimized. A number of iterations is required, during which corrections for the velocities and interface depths are obtained simultaneously, until convergence is reached. Tests using synthetic travel-time data were carried out and a comparison was made with another tomographic inversion program. Reliable results were obtained from these tests. Adding noise to the travel-time data showed that the program is robust, making it applicable and useful in practice.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105768"},"PeriodicalIF":2.2,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison between vertical, lateral and multi coupling width of spatial constrained inversion techniques for DC resistivity data with estimation of investigation depth in Qelabshowah–Belqas, Egypt","authors":"Mohammed A. Ahmed,&nbsp;Mohamed A. Genedi","doi":"10.1016/j.jappgeo.2025.105763","DOIUrl":"10.1016/j.jappgeo.2025.105763","url":null,"abstract":"<div><div>This research investigates the effectiveness of 1D non-constrained, vertical-, lateral-, and spatially-constrained inversions (VCI-DC, LCI-DC, SCI-DC) on DC resistivity data for analyzing shallow subsurface layers in the Qelabshowah-Bilqas region, which is known for its Quaternary deposits. Fifteen VES-DC soundings were conducted along three profiles using Schlumberger arrays with electrode separations ranging from 1.5 to 100 m. The aim is to enhance the understanding of subsurface characteristics, improve boundary continuity, and evaluate the depth of investigation (DOI). By incorporating constraints on neighboring models, the SCI-DC technique improves resolution and provides reliable results with clearly defined model parameters. This is validated by a Standardized Deviation Factor (STDF) of less than 1.3 at a coupling width of 4 compared to other inversion methods. The SCI-DC technique offers significant advancements in geological analysis and subsurface mapping, surpassing traditional 1D inversion methods in resolution and data representation. The SCI-DC promotes spatial coherence among models, ensuring accuracy and reliability in subsurface mapping applications. The SCI-DC models have successfully identified four distinct geo-electric layers: unconsolidated variable resistive deposits, a conductive wet clayey-sand layer influenced by rainfall seepage, a conductive wet sand layer impacted by saline irrigation water infiltration, and a low to moderate resistive clay-rich sand layer. The DOI technique was applied using the Jacobian matrix of final models, establishing a sensitivity threshold value of 0.8 for optimal interpretation. Geo-statistical analysis was conducted to show 2D spatial distribution of DOI trends through spherical variogram modeling and ordinary Kriging interpolation. Results indicated strong spatial dependencies with higher accuracy (nugget/sill ratio up to 0.22 %) in 1D-DOI (7.66–26.85 m) compared to SCI-DC-DOI (13.26–86.48 m) results. DOI calculations indicated a decrease in DOI range as threshold values increased, with 1D inversion yielding more detailed outcomes compared to SCI-DC inversion due to constraints effects. DOI values with a sensitivity threshold value of 0.8 validated the interpretations. In the southwestern regions, the inclusion of conductive areas in the 1D-DOI maps has proven to be a valuable protective measure, effectively preventing signal penetration into deeper subsurface layers. By integrating DOI findings into geological interpretations, a deeper understanding of subsurface conditions achieved, improving resource assessments for environmental and engineering projects. Through the utilization of advanced inversion techniques and spatial analysis methods, more reliable subsurface models can be developed, enhancing the level of accuracy which leads to improved resource management.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105763"},"PeriodicalIF":2.2,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatigue engineering geophysical studies of bridge deck rebar corrosion and vibration intensity, utilizing integrated accelerometer vibration and self-potential devices","authors":"O.O. Falowo ,&nbsp;V. Oluwasegunfunmi ,&nbsp;O. Ajiboye","doi":"10.1016/j.jappgeo.2025.105766","DOIUrl":"10.1016/j.jappgeo.2025.105766","url":null,"abstract":"<div><div>This project investigated the application of spontaneous potential (SP) and vibration intensity measurement in assessing the integrity of cast-in-place concrete bridge deck in terms reinforcement corrosion and vibration, along Sobe – Owan Highway, Southern Nigeria. The ultimate objective was to map zones of corrosion and assess parts of bridge where vibration is above the normal threshold. The vibration data was taken from the two ends and center of the bridge, while measurement of SP was taken along 1 × 1 m grid established on the bridge infrastructure. The vibration intensity of two hundred sampled vehicles/automobiles were recorded in this study. The result showed the data are within the satisfactory velocity vibration intensity threshold according to ISO 20816-1, however the southwestern and inner part of the southeastern segments of the bridge received more impact than other segments in terms of acceleration (339 mm/s²/256.1 mm/s²), velocity (1005.4 mm/s/745.9 mm/s) and displacement (30.77 mm/20.89 mm) respectively. These anomalous segments are areas indicating probability of 50 % corrosion activity of the reinforcing steel (E_corr of −350 mV ≤ <em>E</em>_corr ≤ −200 mV), accounts for 24.5 % of the bridge deck. These anomalous zones are represented in each of the bridge span, and mostly within the location of the piers, except spans 6–8. This implies that there are corrosion contributions from the piers/piles reinforcements. The effects of the high impact speeds on the bridge especially at the southwestern and towards the inner zone of southeastern ends led to high distress on the concrete slab/deck, which culminated in cracks (traverse and longitudinal cracks), and spalling of concrete cover on some of the bridge's structural members. Thus, this failure allows passage of fluids into the reinforced concrete deck, hence the steel been corroded. These measurements have provided valuable insight into corrosion activity and overall stability of the bridge deck.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"240 ","pages":"Article 105766"},"PeriodicalIF":2.2,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}