Subsurface Structure Research Articles

Extracting Multimodal Surface-Wave Dispersion Curves from Ambient Seismic Noise Using High-Resolution Linear Radon Transform

Abstract In the past two decades or so, ambient noise tomography (ANT) has emerged as an established method for imaging subsurface seismic velocity structures. One of the key steps in ANT is to extract surface-wave dispersion curves. The predominant approach for subsurface shear-wave velocity structure inversion involves utilizing fundamental-mode surface waves in ANT. Nevertheless, a notable challenge encountered is the issue of nonuniqueness when employing the dispersion information of fundamental-mode surface waves to invert for shear-wave velocity models. The inclusion of higher-mode dispersion curves in the inversion offers several benefits, including the reduction of nonuniqueness, enhancement of inversion stability, and decreased dependence on the initial model. In this study, we illustrate the applicability of the high-resolution linear radon transform method (HRLRT) for extracting multimodal surface-wave dispersion energy from ambient seismic noise data. We apply HRLRT to both the synthetic noise data and real data recorded by USArray. Our results of applications show that the HRLRT method can extract multimodal surface-wave dispersion information. Compared with established methods such as the frequency–Bessel transform and multicomponent frequency–Bessel transform, the HRLRT exhibits an advantage in suppressing “crossed” artifacts and the second-/third-type artifacts caused by sparse spatial sampling, and the resulting dispersion energy from HRLRT has narrower peaks, meaning high resolution of dispersion curves based on the HRLRT method.

A Deep Learning Estimation for Probing Depth of Transient Electromagnetic Observation

The probing depth of the transient electromagnetic method (TEM) refers to the depth range at which the underground conductivity changes can be effectively detected. It typically ranges from tens of meters to several kilometers and is influenced by factors such as instrument parameters and the conductivity of the subsurface structure. Rapid and accurate probing depth is useful for the selection of appropriate inversion parameters and improving survey accuracy. However, mainstream methods suffer from issues such as low computational precision, large uncertainties, or high computational requirements, making them unsuitable for processing massive airborne electromagnetic data. In this study, we propose a prediction model based on deep learning that can directly compute the probing depth from the TEM responses, and its effectiveness and accuracy are validated through synthetic models and field measurements. We compared the performance of classic deep learning models, including CNN, RESNET, and RNN, and found that RNN performed the best overall on both synthetic and field data. Furthermore, we apply this algorithm to deep learning-based ATEM inversion by constraining the one-dimensional resistivity model depths in the training set, to reduce the non-uniqueness of the inversion, accelerate the convergence, and improve its prediction accuracy.

Response of semicircular canyons and movable cylindrical cavities to SH waves in anisotropic half-space geology

The development of tunnels or the laying of underground pipelines are essential engineering projects in modern society, and in canyon tunnels and underground pipeline projects, the surface motion and cavity edge motion have been topics of concern in ground vibration problems. We investigate the wave scattering problem in an elastic half-space anisotropic medium containing a semicircular canyon and a subsurface movable cylindrical cavity by using the wave function expansion method, the complex function method, and the mirror method. By deriving the governing equation and transforming it into the standard form of the Helmholtz equation satisfying the zero-stress boundary condition, we solve the corresponding displacement functions. Introducing a position correction coefficient, the scattered wavefield in a half-space anisotropic medium is constructed by the mirror method, which improves the problem of scattered wave source singularity in anisotropic half-space media. Then, combining the free boundary conditions with a Fourier series expansion method, we solve the unknown coefficients in the equations. The correctness of the method is verified by degenerating it to a classical analytic solution. Finally, using frequency- and time-domain analysis, we investigate the effects of the relevant parameters on the surface motion [Formula: see text], the dynamic stress concentration factor, and the displacement amplitude [Formula: see text]. The results indicate that rock anisotropy and the presence of semicircular canyons have a significant effect on the dynamic response of subsurface structures. This not only provides a theoretical basis for practical unlined tunnels or pipeline projects but also can provide a basis for seismic design of underground structures.

Wave height reduction through the under surface pipe structure model

The model of the subsurface pipe structure is designed as a reducer of the height of an incident wave generated. Part of the wave will be reflected, and some will be transmitted through the pipe structure. Experiments on the calculation of reflection and transmission coefficients on the subsurface pipe structure model were carried out with variations in the depth of water in the flume. This experimental study aims to determine the effect of changes in incident waves on variations in water depth above the subsurface pipe structure (d-h = 0.0h; 0.1h; 0.2h). This research was conducted at the Hydraulics Laboratory of the Department of Civil Engineering, Faculty of Engineering, Hasanuddin University. Experimental laboratory research method using a wave generator flume with the characteristics of the generated waves consisting of 3 variations of the period (T=1.0 seconds, T=1.1 seconds, T=1.2 seconds) with three variations of water depth (d) which used, i.e., d=1.0h; d=1,1h and d=1,2h, where h is the height of the pipe structure. The results of this study indicate that the deeper water above the structure, the smaller the reflection coefficient and the greater the transmission coefficient.

Analysis of a large buried impact crater and vertical mineral composition at the Chang'E-4 landing site by multi-source remote sensing data

Exploring the concealed subsurface structures and materials beneath the lunar surface can reveal significant insights into geological history. This study offers a comprehensive analysis of the stratigraphic interpretation and subsurface material composition at the Chang'E-4 landing site, integrating both in-situ and orbital radar with multispectral datasets. We report the identification of a subsurface structure, which resembles a buried impact crater (∼420 m in diameter) under the Yutu-2 rover's path. This crater could degrade over a period of 0.42 to 0.53 Ga, with an initial diameter of 293 to 323 m and an initial depth of 45.9 to 51.4 m. Surface material above the buried crater, evaluated by the in-situ visible and near-infrared imaging spectrometer (VNIS) detector, shows a higher abundance of clinopyroxene compared to surrounding areas, where a near-equal mix of clinopyroxene and orthopyroxene is observed. Assessment of crater diameters in proximity to the Chang'E-4 landing site, along with the mineral compositions at their epicenters, reveals a decrease in the abundance of clinopyroxene and plagioclase with depth. Conversely, the quantities of orthopyroxene and olivine increase, implying that orthopyroxene-rich Finsen ejecta significantly influenced the Chang'E-4 landing site's geological composition. Two potential stratigraphic boundary depths are identified at 13.5 and 22 m, based on pronounced variations in mineral abundance, offering fresh insights into subsurface delineation beyond radar data. Considering the VNIS and vertical mineral composition, we propose the buried crater's formation resulted from Finsen crater's ejecta. Also, we identify eight potential historical impacts by comparing subsurface relief variations with mineral composition ratios between clinopyroxene and orthopyroxene. The integration of subsurface structure, along with surface and subsurface mineral composition, enables a more robust stratigraphic interpretation, facilitates shallow material source analysis, and allows for historical impact tracing.

Investigation of microstructure, mechanical, and tribological properties of MoSi2-reinforced copper-graphene composites

The MoSi2-reinforced copper-graphene composites (Cu-MoSi2-GNS) were prepared using mechanical ball milling and spark plasma sintering techniques. The effects of MoSi2 content on the microstructure, electrical conductivity, mechanical performance, and tribological properties were systematically investigated. Results indicate that the addition of MoSi2 significantly enhanced strength and hardness, although slightly reducing electrical conductivity. When the MoSi2 content does not exceed 5 wt%, MoSi2 is uniformly dispersed, refining copper matrix grains and improving GNS dispersion. Optimal MoSi2 addition facilitates the formation of a stable subsurface structure with complete mechanical mixture layer, improving wear resistance and self-lubricating properties. The main wear mechanism shifts from adhesive to abrasive wear. At 5 wt% MoSi2, the Cu-MoSi2-GNS composites exhibits superior mechanical properties, electrical conductivity, and tribological performance.

Visualizing Surface-Subsurface Cu Atom Exchange at the FeO/Pt(111) Surface Induced by CO Adsorption at 150 K.

Structural evolution of solid catalyst surfaces induced by direct exposure to reaction gas has been extensively studied and is well understood. However, whether and how subsurface atomic structures are affected by the reaction atmosphere require further exploration. In this work, our results confirm that Cu clusters supported on FeO/Pt(111) (Cun/FeO/Pt) transform into surface CuCO complexes (CuCO/FeO/Pt) with exposure to CO at 78 K. Surprisingly, Cu clusters on Pt(111) buried under monolayer FeO film (FeO/Cun/Pt) can also transform into surface CuCO complexes on FeO/Pt(111) upon CO adsorption at 150 K. The place exchange of surface and subsurface Cu atoms at the FeO/Pt(111) surface can be mediated by exposing to CO at 150 K and keeping in ultrahigh vacuum at 300 K, alternatively. Calculation results reveal that CO adsorption induces restructuring of the FeO film above the Cu clusters, generating a diffusion channel for Cu atoms to pass through the FeO film and form surface CuCO, while Cu atoms remaining at the FeO-Pt interface are more thermodynamically favored without CO. Our work suggests that buried subsurface atoms may be involved in strong restructuring processes driven by reaction gas, which could strongly influence the catalytic performance.

Decoupled approximate qP‐ and qSV‐wave equations in attenuated transversely isotropic media

AbstractAccurate seismic models with anisotropy and attenuation characteristics are crucial to accurately imaging subsurface structures. However, the anisotropic viscoelastic equations are complex and require significant computational resources. In addition, the single‐mode waves have been sufficient for most practical exploration needs. However, separating the qP‐ and qSV‐waves in anisotropic viscoelastic wavefields is challenging. Thus, we propose a new method to approximate and efficiently separate the qP‐ and qSV‐waves in attenuated transversely isotropic media. First, we obtain the decoupled approximate phase velocities of qP‐ and qSV‐waves by a curve‐fitting method. Consequently, based on the average and maximum relative error analysis, our approximate qP‐ and qSV‐wave phase velocities are more accurate than the existing approximations. Additionally, our approximations have broader applicability, resulting in acceptable errors during their application. Second, based on the approximate qP‐ and qSV‐wave phase velocities, we derive the corresponding qP‐ and qSV‐wave equations for a complete decoupling of the qP‐ and qSV‐wave components in transversely isotropic media. Third, to combine the attenuation and anisotropy characteristics, we incorporate the Kelvin–Voigt attenuation model and obtain the decoupled qP‐ and qSV‐wave equations in attenuated transversely isotropic media. Then, we use an efficient and stable hybrid finite‐difference and pseudo‐spectral method to solve the new decoupled qP‐ and qSV‐wave equations. Finally, several numerical examples demonstrate the separability and high accuracy of the proposed qP‐ and qSV‐wave equations. We obtain a qP‐wave wavefield entirely devoid of SV‐wave artefacts. In addition, the decoupled approximate qP‐ and qSV‐wave equations are accurate and stable in heterogeneous media with different velocities and attenuation. The decoupled, approximated qP‐wave and qSV‐wave equations proposed in this paper can effectively separate the qP‐wave and qSV‐wave components, resulting in fully decoupled qP‐ and qSV‐wave wavefields in attenuated transversely isotropic media.

Controllable Seismic Velocity Synthesis Using Generative Diffusion Models

AbstractAccurate seismic velocity estimations are vital to understanding Earth's subsurface structures, assessing natural resources, and evaluating seismic hazards. Machine learning‐based inversion algorithms have shown promising performance in regional (i.e., for exploration) and global velocity estimations, while their effectiveness hinges on access to large and diverse training data sets whose distributions generally cover the target solutions. Additionally, enhancing the precision and reliability of velocity estimation also requires incorporating prior information, for example, geological classes, well logs, and subsurface structures, but current statistical or neural network‐based methods are not flexible enough to handle such multimodal information. To address both challenges, we propose to use conditional generative diffusion models for seismic velocity synthesis in which we readily incorporate those priors. This approach enables the generation of seismic velocities that closely match the expected target distribution, offering data sets informed by both expert knowledge and measured data to support training for data‐driven geophysical methods. We demonstrate the flexibility and effectiveness of our method through training diffusion models on the OpenFWI data set under various conditions, including class labels, well logs, reflectivity images, and the combination of these priors. The performance of the approach under out‐of‐distribution conditions further underscores its generalization ability, showcasing its potential to provide tailored priors for velocity inverse problems and create specific training data sets for machine learning‐based geophysical applications.

Insights into Afikpo Synclinorium structures: Subsurface analysis and intrusion outlining from airborne magnetic data

The airborne magnetic data over Afikpo Synclinorium were used to highlight subsurface structures and establish the orientations of tectonic features and their influence on the hydrocarbon play of the area. The characteristic trends of the lineaments were achieved through the center for exploration targeting of grid data analysis. The results of the TMI, residual magnetic field, first vertical, horizontal derivative, Analytic signal, and Tilt angle derivative classified the area into regions of high magnetic intensity observed around the northeastern, southwestern, and central portions of the study area. These areas characterized by anomalous signatures of short magnetic wavelengths delineate shallow magnetic sources. Conversely, regions with medium to low magnetic intensities are characterized by long magnetic wavelengths which indicates deep-seated magnetic source(s) and prospect for hydrocarbon (if other play concepts are emplace); due the thick sediment cover at the southern portion of the area (around, southern part of Nguzu, Ohafia, Biakpan, Abriba and Bende areas). The sediment thickness decreases towards north, west, North-east and north-west (dominated by Benue Trough deposit). Depth to the anomaly sources is of two categories, namely, shallow <1.0 km (dominated by NE trending structures) and deep ≥2.5 km. Ground-truthing confirmed the anomalous zone of high magnetic sources in the northeastern and central regions as Tertiary related tectonic-magmatic intrusion. The most prominent intrusion cuts across Amangwu Edda in Afikpo South through Amaeta-Oziza to Cross River State in a fissure form. This intrusion occurrence conformed to the high magnetic signature identified as a dolerite sill within the Afikpo Sub-basin. It stretches over 16 km in length with an average width of about 1.2 km, having its widest part in the northern parts of Mata Hospital Afikpo. The subsurface topographic model indicated that no fewer than 50% of the study area is characterized by sporadically distributed intrusive rocks. The result revealed several structural lineaments with high lineament density at the northcentral corner of the area trending NE-SW with fault lines (slip fault) perpendicular to it, offsetting the Akpoha, Ibii, Amasiri. and Ozara-ukwu ridges. The major drainage systems across the area followed major structural trends perpendicular to the identified major lineaments, passing through the major regional structural displacement pattern of the Basin. The emplacement of these intrusions might have impacted the hydrocarbon potential of the basin.

Subsurface interconnection beneath the Mio-Plio-Quaternary volcanoes of the Ain Leuh causse (Middle Atlas, Morocco): Structural framework and emplacement mechanisms

In the Ain Leuh causse, located southwest of the Middle Atlas Volcanic Province (MAVP), a combined study using aeromagnetic data, fieldwork, and remote sensing is carried out to improve our understanding of the subsurface structure and its correlation with surface structural and volcanic features. The tectonically controlled emplacement mechanisms of the MAVP, which continue to hold undisclosed aspects, were investigated as well. Numerous techniques and mathematical filters for edge detection and 2D modelling were used. The main observations show that the positive magnetic anomalies in the study area are mainly related to the magmatic activity, which was organized into two main episodes: i) Triassic, with a tholeiitic affinity, well recorded along the NE-SW inherited Variscan faults; and ii) Mio-Plio-Quaternary, with an alkaline affinity, forming scoria cones, maars, and lava flows. They are also expressed as hidden domes, laccoliths, and interconnected magma bodies revealed by 2D modelling of the aeromagnetic data. Uncommon coarse-grained undersaturated alkaline rocks crop out in Talzast dome (Talzastite, Fasinites, and Ankaratrite). They are unique in the MAVP and restricted to this part of the Middle Atlas. 2D aeromagnetic modelling has revealed the presence of shallow magmatic rocks bodies beneath Talzast dome. The extracted structural lineaments using aeromagnetic data and remote sensing reveal that the structural framework of the study area is controlled by NE-trending faults reaching depths of up to 3000 m, which is the depth of the magnetic signature of the faults. Additionally, NNE, NNW and N-trending short-length lineaments are defined and rooted at depths up to 3000 m. The predominant NE-SW structural trend may be linked to the reactivation of Hercynian faults during Alpine tectonics. These faults likely controlled the emplacement of the Mio-Plio-Quaternary volcanism in the area. The magma reservoirs that would have fed the various volcanic edifices are located at a shallow depth of less than 500–2000 m.

The 3‐D Density Structure of the Large Shield Volcanic Structure in the Gardner Region Revealed by a New Gravity Inversion

AbstractThe Gardner region is a well‐known shield volcanic complex on the Moon. Its magma origin and formation mechanism are of significant interest but still enigmatic. To reveal the subsurface structure of this volcanic complex, we propose a new 3‐D inversion method of the gravity field based on the regularizations of the L1 norm of the model and its gradients. The model test indicates that our proposed method can recover the density structures with high resolution. Subsequently, we apply it to the Bouguer gravity data in the Gardner region. Our result shows a large, dense body with a volume of about 45 × 45 × 13 km3 centered under the topographic bulge of the Gardner Plateau. We infer that this structure is most likely dense basalts trapped at the crust‐mantle boundary as a sill and acted as the magma reservoir that has fed the volcanic complex in the Gardner area.

Integrating remote sensing and geophysical data for mapping potential gold mineralization localities at Abu Marawat area, central Eastern Desert, Egypt

Abu Marawat area in the Central Eastern Desert of Egypt is a very promising mineralization district located in the Golden Triangle area. The current study provides an integrated approach from multisource datasets including; remote sensing, airborne geophysical spectrometry and magnetic data supported by field studies and spectroscopic analyses for delineating potential mineralization localities. Several remote sensing techniques were adopted including; Band Ratios, Relative Band Depth, Mineralogical Indices, Spectral Angle Mapper, and Constrained Energy Minimization. These techniques showed that the alteration mineral assemblage is mainly, kaolinite, sericite, and iron oxides, with less abundant chlorite, epidote, and carbonates. In addition, the radiometry data were processed to map the localities with the highest possibility of potassic alteration abundance by integrating the potassium distribution, K/eTh ratio, and the F-parameter maps. The surface and subsurface linear structural features were also mapped using Digital Elevation Model (DEM) and aeromagnetic data, respectively. The surface linear structures were found exhibiting E-W and NE-SW trends, while, the subsurface structures showed dominant NW–SE trend. All the depicted fault trends match well with the local and regional geological and tectonic setting of the study area suggesting structural control on the mineralization in this area. Integration between the results obtained from both the remote sensing and the geophysical data was conducted by a GIS weighted overlay model. The obtained mineralization potentiality map highlights eight potential localities for mineralization. The accuracy of the adopted methodology was demonstrated through fieldwork and spectral analyses; several alteration indicators were observed, including quartz veins, iron oxides, kaolinite, malachite, montmorillonite, chlorite, talc, and sericite alteration indicator minerals. The adopted remote sensing-geophysical approach showed being very effective for mapping the hydrothermal gold-related alteration zones, and is recommended for other similar investigations.

Imaging Biomarkers of Oral Dysplasia and Carcinoma Measured with In Vivo Endoscopic Optical Coherence Tomography.

Optical coherence tomography is a noninvasive imaging technique that provides three-dimensional visualization of subsurface tissue structures. OCT has been proposed and explored in the literature as a tool to assess oral cancer status, select biopsy sites, or identify surgical margins. Our endoscopic OCT device can generate widefield (centimeters long) imaging of lesions at any location in the oral cavity-but it is challenging for raters to quantitatively assess and score large volumes of data. Leveraging a previously developed epithelial segmentation network, this work develops quantifiable biomarkers that provide direct measurements of tissue properties in three dimensions. We hypothesize that features related to morphology, tissue attenuation, and contrast between tissue layers will be able to provide a quantitative assessment of disease status (dysplasia through carcinoma). This work retrospectively assesses seven biomarkers on a lesion-contralateral matched OCT dataset of the lateral and ventral tongue (40 patients, 70 sites). Epithelial depth and loss of epithelial-stromal boundary visualization provide the strongest discrimination between disease states. The stroma optical attenuation coefficient provides a distinction between benign lesions from dysplasia and carcinoma. The stratification biomarkers visualize subsurface changes, which provides potential for future utility in biopsy site selection or treatment margin delineation.

Enhancing subsurface seismic profiling with distributed acoustic sensing and optimization algorithms

The distribution of shear-wave velocities in the subsurface is generally used to assess the potential for seismic liquefaction and soil amplification effects and to classify seismic sites. Newly developed distributed acoustic sensing (DAS) technology enables estimation of the shear-wave distribution as a high-density seismic observation system. This technology is characterized by low maintenance costs, high-resolution outputs, and real-time data transmission capabilities, albeit with the challenge of managing massive data generation. Rapid and efficient interpretation of data is the key to advancing application of the DAS technology. In this study, field tests were carried out to record ambient noise over a short period using DAS technology, from which the surface-wave dispersion curves were extracted. In order to reduce the influence of directional effects on the results, an unsupervised clustering method is used to select appropriate clusters to extract the Green's function. A combination of a genetic algorithm and Monte Carlo (GA-MC) simulation is proposed to invert the subsurface velocity structure. The stratigraphic profiles obtained by the GA-MC method are in agreement with the borehole profiles. Compared to other methods, the proposed optimization method not only improves the solution quality but also reduces the solution time.

Comparative Study of the Effect of Volcanic Activity and the El Niño Phenomenon on Surface Thermal Changes in the Arjuno-Welirang Crater Area Using GEE Cloud Computing

The increasing seismic activity of Arjuno Welirang on February 7, 2018, warned about the dangers of volcanic eruptions that must be watched out for, so that activity needs to be monitored continuously. There is little information available about seismic activity at the Arjuno Welirang complex. Most studies have investigated geothermal potential and subsurface structures. Due to the limitations of this data, land surface temperature (LST) analysis was carried out in this research to monitor the development of Arjuno-Welirang volcanic activity. Several volcano studies have used LST criteria in remote sensing applications to detect volcanic activity. However, the performance of LST has not been tested in the case of normal volcanic activity, which is influenced by external thermal disturbances. This study aims to show the performance of LST detection on changes in the normal volcanic activity of Arjuno Welirang, which is disturbed by temperature noise caused by the El Niño phenomenon. The LST calculations are carried out by including surface emissivity corrections obtained based on Normalized Difference Vegetation Index (NDVI) values. The LST calculation algorithm is implemented with the Google Earth Engine (GEE) platform. LST analysis was carried out on Landsat 8 images for the May-August 2023 time period obtained from the United States Geological Survey (USGS) database via GEE cloud computing. The reason for determining this time period is because the release of the daily Arjuno Welirang volcanic activity report by Magma Indonesia coincided with the Meteorology Climatology and Geophysical Agency (BMKG) notification regarding the occurrence of El Niño phenomenon. The output is an LST curve against time, which shows a tendency for the surface temperature of the Arjuno-Welirang crater to increase in July. This is similar to the trend of increasing seismic activity reported on the Magma Indonesia website and conversely is not similar to the increase in temperature due to the El Niño effect predicted by BMKG. The highest temperature increase occurred on July 24 2023, reaching 31.78 ⁰C, and then the temperature decreased. The method used in this research has proven that LST analysis is able to detect changes in normal volcanic activity in the Arjuno-Welirang crater even though there is thermal noise due to the influence of the impact of El Niño. LST values are more dominantly influenced by volcanic activity than by extreme El Niño weather.

EIT probe based intraoperative tissue inspection for minimally invasive surgery

Abstract Electrical impedance tomography (EIT) has become an integral component in the repertoire of medical imaging techniques, particularly due to its non-invasive nature and real-time imaging capabilities. Despite its potential, the application of EIT in minimally invasive surgery (MIS) has been hindered by a lack of specialized electrode probes. Existing designs often compromise between invasiveness and spatial sensitivity: probes small enough for MIS often fail to provide detailed imaging, while those offering greater sensitivity are impractically large for use through a surgical trocar. Addressing this challenge, our study presents a breakthrough in EIT probe design. The open electrode probe we have developed features a line of 16 electrodes, thoughtfully arrayed to balance the spatial demands of MIS with the need for precise imaging. Employing an advanced EIT reconstruction algorithm, our probe not only captures images that reflect the electrical characteristics of the tissues but also ensures the homogeneity of the test material is accurately represented. The versatility of our probe is demonstrated by its capacity to generate high-resolution images of subsurface anatomical structures, a feature particularly valuable during MIS where direct visual access is limited. Surgeons can rely on intraoperative EIT imaging to inform their navigation of complex anatomical landscapes, enhancing both the safety and efficacy of their procedures. Through rigorous experimental validation using ex vivo tissue phantoms, we have established the probe’s proficiency. The experiments confirmed the system’s high sensitivity and precision, particularly in the critical tasks of subsurface tissue detection and surgical margin delineation. These capabilities manifest the potential of our probe to revolutionize the field of surgical imaging, providing a previously unattainable level of detail and assurance in MIS procedures.

Integration of Geophysical and Hydrochemical Methods to Determine the Groundwater Contamination in Al-Hosayniat Landfill South East Mafraq City, Jordan

An integration of Geophysical – Electromagnetic and hydro-chemical methods was used to investigate the potential of groundwater contamination due to Al-Hosayniat Municipal Landfill (HL) southeast of Mafraq city. Twenty-five Time Domain Electromagnetic (TDEM) soundings were carried out inside and outside the HL in addition to one WNW-ESE Very Low Frequency (VLF) profile. The TDEM's results help to define the subsurface geology and structures down to 240m depth. The results also depict the presence of a major fault striking NW-SE that crosses the whole landfill, this fault is documented in the surface geological map, and it was delineated and imaged by TDEM measurements and detected at larger depths. VLF results also detected the presence of a major fault beneath the landfill. The presence of the fault just beneath the HL may enhance the leachate movement which can imply groundwater contamination hazards for a longer period as it is a preferential pathway for contaminants. The results of water quality analyses of adjacent wells show higher concentrations of Na+, SO-24, TDS in some wells and this can be ascribed to agricultural activities and over-pumping in the area rather than landfill leachate. The heavy metal concentrations were found to be within the permissible limits and did't indicate direct contamination due to the HL. However, Fluorite (F-) shows a high concentration of (1.3mg/l) in WS4 and WS5 wells and approaches the permissible limit (1.5mg/l) according to the Jordan Water Standards (JWS). Bromide (Br) shows high concentration of (0.6mg/l) in well Al-2462.

Frequency‐Bessel Transform Method for Multimodal Dispersion Measurement of Surface Waves From Distributed Acoustic Sensing Data

AbstractThe array‐based frequency‐Bessel transform method has been demonstrated to effectively extract dispersion curves of higher‐mode surface waves from the empirical Green's functions (EGFs) of displacement fields reconstructed by ambient noise interferometry. Distributed acoustic sensing (DAS), a novel dense array observation technique, has been widely implemented in surface wave imaging to estimate subsurface velocity structure in practice. However, there is still no clear understanding in theory about how to accurately extract surface‐wave dispersion curves directly from DAS strain (or strain rate) data. To address this, we extend the frequency‐Bessel transform method by deriving Green’s functions (GFs) for horizontal strain fields, making it applicable to DAS data. First, we test its performance using synthetic GFs and verify the correctness of extracted dispersion spectrograms with theoretical results. Then, we apply it to three field DAS ambient‐noise data sets, two recorded on land and one in the seabed. The reliability and advantages of the method are confirmed by comparing results with the widely used phase shift method. The results demonstrate that our extended frequency‐Bessel transform method is reliable and can provide more abundant and higher‐quality dispersion information of surface waves. Moreover, our method is also adaptable for active‐source DAS data with simple modifications to the derived transform formulas. We also find that the gauge length in the DAS system significantly impacts the polarity and value of extracted dispersion energy. Overall, our study provides a theoretical framework and practical tool for multimodal surface wave dispersion measurement using DAS data.

An unsupervised machine learning algorithm approach using K-Means Clustering for optimizing Surface Wave Filtering in seismic reflection data

Surface waves often cause significant noise in seismic data, complicating the interpretation of subsurface structures. Traditional filtering methods, such as FK filtering, usually struggle with non-stationary noise and require extensive manual parameter tuning. This study explores the effectiveness of using K-means clustering, incorporating attributes such as amplitude, frequency, and phase to filter surface waves from seismic data. Synthetic seismic data were first generated to test the proposed method, ensuring its robustness before application to real field data. Attributes were extracted from each seismic trace, including instantaneous amplitude, frequency, and phase. These attributes were used as input parameters for the K-means clustering algorithm. The identified clusters corresponding to surface waves were then used to filter these waves from the seismic data. The K-Means clustering effectively differentiated surface waves from reflected waves in both synthetic and real seismic datasets. The method demonstrated that by including phase as an attribute, alongside amplitude and frequency, the accuracy of surface wave detection and filtering significantly improved. The synthetic data showed a clear separation of wave types, validating the method. When applied to real field data, the approach consistently removed surface waves, clarity of seismic reflections crucial for subsurface analysis.